A conventional global contrast enhancement is difficult to apply in various images because image quality and contrast enhancement are dependent on image characteristics largely. And a local contrast enhancement not on...A conventional global contrast enhancement is difficult to apply in various images because image quality and contrast enhancement are dependent on image characteristics largely. And a local contrast enhancement not only causes a washed-out effect, but also blocks. To solve these drawbacks, this paper derives an optimal global equalization function with variable size block based local contrast enhancement. The optimal equalization function makes it possible to get a good quality image through the global contrast enhancement. The variable size block segmentation is firstly exeoated using intensity differences as a measure of similarity. In the second step, the optimal global equalization function is obtained from the enhanced contrast image having variable size blocks. Conformed experiments have showed that the proposed algorithm produces a visually comfortable result image.展开更多
Path planning is crucial for autonomous flight of fixed-wing Unmanned Aerial Vehicles(UAVs).However,due to the high-speed flight and complex control of fixed-wing UAVs,ensuring the feasibility and safety of planned pa...Path planning is crucial for autonomous flight of fixed-wing Unmanned Aerial Vehicles(UAVs).However,due to the high-speed flight and complex control of fixed-wing UAVs,ensuring the feasibility and safety of planned paths in complex environments is challenging.This paper proposes a feasible path planning algorithm named Closed-loop Radial Ray A^(*)(CL-RaA^(*)).The core components of the CL-RaA^(*)include an adaptive variable-step-size path search and a just-in-time expansion primitive.The former enables fast path search in complex environments,while the latter ensures the feasibility of the generated paths.By integrating these two components and conducting safety checks on the trajectories to be expanded,the CL-RaA^(*)can rapidly generate safe and feasible paths that satisfy the differential constraints that comprehensively consider the dynamics and control characteristics of six-degree-of-freedom fixed-wing UAVs.The final performance tests and simulation validations demonstrate that the CL-RaA^(*)can generate safe and feasible paths in various environments.Compared to feasible path planning algorithms that use the rapidlyexploring random trees,the CL-RaA^(*)not only ensures deterministic planning results in the same scenarios but also generates smoother feasible paths for fixed-wing UAVs more efficiently.In environments with dense grid obstacles,the feasible paths generated by the CL-RaA^(*)are more conducive to UAV tracking compared to those planned using Dubins curves.展开更多
By analyzing algorithms available for variable step size least mean square(LMS)adaptive filter,a new modified LMS adaptive filtering algorithm with variable step size is proposed,along with performance analysis based ...By analyzing algorithms available for variable step size least mean square(LMS)adaptive filter,a new modified LMS adaptive filtering algorithm with variable step size is proposed,along with performance analysis based on different parameters.Compared with the existing algorithms through the simulation,the proposed algorithm has faster convergence speed and smaller steady state error.展开更多
The new features of H. 264 video coding standard make the motion estimation module much more time consuming than before. Especially, the motion search is required for each of the 4 modes for inter prediction. In order...The new features of H. 264 video coding standard make the motion estimation module much more time consuming than before. Especially, the motion search is required for each of the 4 modes for inter prediction. In order to reduce the computational complexity, we analyze the statistics of results of motion estimation, such as the continuity of best modes of blocks in successive frames and the chance to give up a sub-partition mode （smaller than 16 × 16） after integer-pixel motion estimation, from which we suggest to make mode prediction based on the motion information of the previous frame and skip sub-pixel motion estimation in subpartition mode selectively. According to the experimental result, the proposed algorithm can save 75 % of the computational time with a slight degradation （0.03 dB） on PSNR compared with the pseudocode of fast search motion estimation in JM12.2.展开更多
This paper puts forward a new variable step size LMS adaptive algorithm based on variable region. The step size p（k） in the algorithm varies with the variation of the region of deviation e （k） to ensure the optimi...This paper puts forward a new variable step size LMS adaptive algorithm based on variable region. The step size p（k） in the algorithm varies with the variation of the region of deviation e （k） to ensure the optimization of the three performance objectives including initial convergent speed, trace ability of the time-varying system and steady disregulation. The paper demonstrates the convergence of the algorithm accompanied by random noise,展开更多
The problem of inter symbol interference（ ISI） in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn＇t require a ...The problem of inter symbol interference（ ISI） in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn＇t require a training sequence,a blind equalization channel is implemented in the receiver to increase the throughput of the system. To improve the performances of both the blind equalizer and the system,a joint receiving mechanismincluding variable step size（ VSS） modified constant modulus algorithms（ MC-MA） and modified decision directed modulus algorithms（ MD DMA） is proposed to ameliorate the convergence speed and mean square error（ MSE） performance and combat the phase error when using high order QAM modulation. The VSS scheme is based on the selection of step size according to the distance between the output of the equalizer and the desired output in the constellation plane. Analysis and simulations showthat the performance of the proposed VSS-MCMA-MD DMA mechanismis better than that of algorithms with a fixed step size. In addition,the MCMA-MDDMA with VSS can performthe phase recovery by itself.展开更多
The soil packing,influenced by variations in grain size and the gradation pattern within the soil matrix,plays a crucial role in constituting the mechanical properties of sandy soils.However,previous modeling approach...The soil packing,influenced by variations in grain size and the gradation pattern within the soil matrix,plays a crucial role in constituting the mechanical properties of sandy soils.However,previous modeling approaches have overlooked incorporating the full range of representative parameters to accurately predict the soaked California bearing ratio(CBR_(s))of sandy soils by precisely articulating soil packing in the modeling framework.This study presents an innovative artificial intelligence(AI)-based approach for modeling the CBR_(s)of sandy soils,considering grain size variability meticulously.By synthesizing extensive data from multiple sources,i.e.extensive tailored testing program undertaking multiple tests and extant literature,various modeling techniques including genetic expression programming(GEP),multi-expression programming(MEP),support vector machine(SVM),and multi-linear regression(MLR)are utilized to develop models.The research explores two modeling strategies,namely simplified and composite,with the former incorporating only sieve analysis test parameters,while the latter includes compaction test parameters alongside sieve analysis data.The models'performance is assessed using statistical key performance indicators(KPIs).Results indicate that genetic AI-based algorithms,particularly GEP,outperform SVM and conventional regression techniques,effectively capturing complex relationships between input parameters and CBR_(s).Additionally,the study reveals insights into model performance concerning the number of input parameters,with GEP consistently outperforming other models.External validation and Taylor diagram analysis demonstrate the GEP models'superiority over existing literature models on an independent dataset from the literature.Parametric and sensitivity analyses highlight the intricate relationships between grain sizes and CBR_(s),further emphasizing GEP's efficacy in modeling such complexities.This study contributes to enhancing CBR_(s)modeling accuracy for sandy soils,crucial for pertinent infrastructure design and construction rapidly and cost-effectively.展开更多
Understanding how population sizes vary over time is a key aspect of ecological research. Unfortunately, our under- standing of population dynamics has historically been based on an assumption that individuals are ide...Understanding how population sizes vary over time is a key aspect of ecological research. Unfortunately, our under- standing of population dynamics has historically been based on an assumption that individuals are identical with homogenous life-history properties. This assumption is certainly false for most natural systems, raising the question of what role individual variation plays in the dynamics of populations. While there has been an increase of interest regarding the effects of within popula- tion variation on the dynamics of single populations, there has been little study of the effects of differences in within population variation on patterns observed across populations. We found that life-history differences （clutch size） among individuals ex- plained the majority of the variation observed in the degree to which population sizes of eastern fence lizards Sceloporus undula- tus fluctuated. This finding suggests that differences across populations cannot be understood without an examination of differences at the level of a system rather than at the level of the individual展开更多
In order to improve the problem that the filtered-x least mean square(FxLMS)algorithm cannot take into account the convergence speed,steady-state error during active noise control.A piecewise variable step size FxLMS ...In order to improve the problem that the filtered-x least mean square(FxLMS)algorithm cannot take into account the convergence speed,steady-state error during active noise control.A piecewise variable step size FxLMS algorithm based on logarithmic function(PLFxLMS)is proposed,and the genetic algorithm are introduced to optimize the parameters of logarithmic variable step size FxLMS(LFxLMS),improved logarithmic variable step size Films(IFxLMS),and PLFxLMS algorithms.Bandlimited white noise is used as the input signal,FxLMS,LFxLMS,ILFxLMS,and PLFxLMS algorithms are used to conduct active noise control simulation,and the convergence speed and steady-state characteristic of four algorithms are comparatively analyzed.Compared with the other three algorithms,the PLFxLMS algorithm proposed in this paper has the fastest convergence speed,and small steady-state error.The PLFxLMS algorithm can effectively improve the convergence speed and steady-state error of the FxLMS algorithm that cannot be controlled at the same time,and achieve the optimal effect.展开更多
An improved finite difference method （FDM）is described to solve existing problems such as low efficiency and poor convergence performance in the traditional method adopted to derive the pressure distribution of aero...An improved finite difference method （FDM）is described to solve existing problems such as low efficiency and poor convergence performance in the traditional method adopted to derive the pressure distribution of aerostatic bearings. A detailed theoretical analysis of the pressure distribution of the orifice-compensated aerostatic journal bearing is presented. The nonlinear dimensionless Reynolds equation of the aerostatic journal bearing is solved by the finite difference method. Based on the principle of flow equilibrium, a new iterative algorithm named the variable step size successive approximation method is presented to adjust the pressure at the orifice in the iterative process and enhance the efficiency and convergence performance of the algorithm. A general program is developed to analyze the pressure distribution of the aerostatic journal bearing by Matlab tool. The results show that the improved finite difference method is highly effective, reliable, stable, and convergent. Even when very thin gas film thicknesses （less than 2 Win）are considered, the improved calculation method still yields a result and converges fast.展开更多
Acoustic echo cancellation is often applied in communication and video call system to reduce unnecessary echoes generated between speakers and microphones.In these systems,the speech input signal of the adaptive filte...Acoustic echo cancellation is often applied in communication and video call system to reduce unnecessary echoes generated between speakers and microphones.In these systems,the speech input signal of the adaptive filter is often colored and unstable,which decays the convergence rate of the adaptive filter if the NLMS algorithm is used.In this paper,an improved nonparametric variable step-size subband(NPVSS-NSAF)algorithm is proposed to address the problem.The variable step-size is derived by minimizing the sum of the square Euclidean norm of the difference between the optimal weight vectors to be updated and the past estimated weight vectors.Then the parameters are eliminated by using the power of subband signal noise equal to the power of subband posteriori error.The performance of the proposed algorithm is simulated in the aspects of misalignment and return loss enhancement.Experiment results show a fast convergence rate and low misalignment of the proposed algorithm in system identification.展开更多
In issues like hearing impairment,speech therapy and hearing aids play a major role in reducing the impairment.Removal of noise signals from speech signals is a key task in hearing aids as well as in speech therapy.Du...In issues like hearing impairment,speech therapy and hearing aids play a major role in reducing the impairment.Removal of noise signals from speech signals is a key task in hearing aids as well as in speech therapy.During the transmission of speech signals,several noise components contaminate the actual speech components.This paper addresses a new adaptive speech enhancement(ASE)method based on a modified version of singular spectrum analysis(MSSA).The MSSA generates a reference signal for ASE and makes the ASE is free from feeding reference component.The MSSA adopts three key steps for generating the reference from the contaminated speech only.These are decomposition,grouping and reconstruction.The generated reference is taken as a reference for variable size adaptive learning algorithms.In this work two categories of adaptive learning algorithms are used.They are step variable adaptive learning(SVAL)algorithm and time variable step size adaptive learning(TVAL).Further,sign regressor function is applied to adaptive learning algorithms to reduce the computational complexity of the proposed adaptive learning algorithms.The performance measures of the proposed schemes are calculated in terms of signal to noise ratio improvement(SNRI),excess mean square error(EMSE)and misadjustment(MSD).For cockpit noise these measures are found to be 29.2850,-27.6060 and 0.0758 dB respectively during the experiments using SVAL algorithm.By considering the reduced number of multiplications the sign regressor version of SVAL based ASE method is found to better then the counter parts.展开更多
Background: Benign prostate hyperplasia (BPH) is the most common benign disease of human prostate. Currently BPH is associated with unregulated proliferation of connective tissue and glandular epithelium within the pr...Background: Benign prostate hyperplasia (BPH) is the most common benign disease of human prostate. Currently BPH is associated with unregulated proliferation of connective tissue and glandular epithelium within the prostatic transition zone, and it has been described as relevant characteristic of BPH—the increase of the total number of cells, and not only an increase in cell size. To date, there are few studies on the quantitative morphology of glandular tree of BPH compared with normal prostate. The scarce investigations about this particular suggest that the glandular tree branches and expands as the hyperplastic transformation occurs in the prostate. Methods: To verify if this gland expansion and branching was similar to that occurs in the normal prostate, this study deals with the estimation of several stereological parameters as: labeling index for the proliferating cell nuclear antigen to quantify the rate of proliferation of prostate epithelium, average thickness of glandular epithelium, fraction of the volume occupied by the epithelium relative to the total prostate volume, connectivity density of prostate glands, to quantify the branching of prostate glands, and the average volume and the volume-weighted mean glandular volume of prostate acini to assess the mean size of the prostate acini and its variability. Results: All these estimates have been performed in prostate specific antigen immunostained sections from prostates of young men (controls) and in adenomectomy specimens from the adenofibromiomatous variety of BPH. Conclusion: We conclude that the epithelial proliferation is not the only factor intervening in the development of BPH. In addition, a more prolonged survival of epithelial population, together with some degree of hypertrophy of acini expressed by the increase of volume fraction and thickness of acinar epithelium, is relevant in order to the growth and expansion of the BPH glandular tree that shows more abundant and heterogeneous acinar sprouts than in normal prostate.展开更多
According to the relationship between truncation error and step size of two implicit second-order-derivative multistep formulas based on Hermite interpolation polynomial,a variable-order and variable-step-size numeric...According to the relationship between truncation error and step size of two implicit second-order-derivative multistep formulas based on Hermite interpolation polynomial,a variable-order and variable-step-size numerical method for solving differential equations is designed.The stability properties of the formulas are discussed and the stability regions are analyzed.The deduced methods are applied to a simulation problem.The results show that the numerical method can satisfy calculation accuracy,reduce the number of calculation steps and accelerate calculation speed.展开更多
Addressing the impact of capacitor mismatch on the conversion accuracy of successive approximation register analog-to-digital converter(SAR ADC),a 12-bit 1 MS/s sub-binary SAR ADC designed using variable step size dig...Addressing the impact of capacitor mismatch on the conversion accuracy of successive approximation register analog-to-digital converter(SAR ADC),a 12-bit 1 MS/s sub-binary SAR ADC designed using variable step size digital calibration was proposed.The least mean square(LMS)calibration algorithm was employed with a ramp signal used as the calibration input.Weight errors,extracted under injected disturbances,underwent iterative training to optimize weight values.To address the trade-off between conversion accuracy and speed caused by a fixed step size,a novel variable step size algorithm tailored for SAR ADC calibration was proposed.The core circuit and layout of the SAR ADC were implemented using the Taiwan Semiconductor Manufacturing Company(TSMC)0.35μm complementary metal-oxide-semiconductor(CMOS)commercial process.Simulation of the SAR ADC calibration algorithm was conducted using Simulink,demonstrating quick convergence and meeting conversion accuracy requirements compared to fixed step size simulation.The results indicated that the convergence speed of the LMS digital calibration algorithm with variable step size was approximately eight times faster than that with a fixed step size,also yielding a lower mean square error(MSE).After calibration,the simulation results for the SAR ADC exhibited an effective number of bit(ENOB)of 11.79 bit and a signal-to-noise and distortion ratio(SNDR)of 72.72 dB,signifying a notable enhancement in the SAR ADC performance.展开更多
Near infrared spectroscopy(NIRS),coupled with principal component analysis and wavelength selection techniques,has been sed to develop a robust and reliable reduced-spectrum classifi-cation model for determining the g...Near infrared spectroscopy(NIRS),coupled with principal component analysis and wavelength selection techniques,has been sed to develop a robust and reliable reduced-spectrum classifi-cation model for determining the geographical origins of Nanfeng mandarins.The application of the changeable size moving window principal component analysis(CSMWPCA)provided a notably improved lassification model,with correct classification rates of 92.00%,100.00%,90.00%,100.00%,100.00%,100.00%and 100.00%for Fujian,Guangxi,Hunan,Baishe,Baofeng,Qiawan,Sanxi samples,respectively,as well as,a total dassification rate of 97.52%in the wavelength range from 1007 to 1296 nm.To test and apply the proposed method,the procedure was applied to the analysis of 59 samples in an independent test set.Good identification results(correct rate of 96.61%)were also received.The improvement achieved by the application of CSMWPCA method was particularly remarkable when taking the low complexities of the final model(290 variables)into account.The results of the study showed the great potential of NIRS as a fast,nondestructive and environmentally acceptable method for the rapid and reliable determination for geographical classifcation of Nanfeng mandarins.展开更多
For medium and high permeability oilfields, filling sand control technology is one of the main measures to prevent formation sand production and achieve stable production and increase production.As the largest oil-bea...For medium and high permeability oilfields, filling sand control technology is one of the main measures to prevent formation sand production and achieve stable production and increase production.As the largest oil-bearing block in Qudi oilfield, Qu9 fault block has serious sand production in Guan3 formation, and sand control is required to meet normal production.Through the continuous development and optimization of sand control technology, in recent years, the commonly used sand control technologies in Qudi oilfield include squeeze filling sand control, chemical sand control, cyclic filling and other processes. It is found that the squeeze filling process can better meet the needs of Qu9 Guan3 block.At the same time, Qu9 Guan3 block has problems such as high shale content, strong sensitivity and thick crude oil viscosity. It is necessary to optimize the squeeze filling sand control process, and put forward supporting technologies such as pre reservoir cleaning agent and variable particle size graded sand addition, so as to better transform the formation, improve seepage efficiency and enhance the productivity of single wells while doing a good job in reservoir protection.展开更多
In order to change the path candidates, reduce the average list size, and make more paths pass cyclic redundancy check （CRC）, multiple CRC-aided variable successive cancellation list （SCL） decoding algorithm is pr...In order to change the path candidates, reduce the average list size, and make more paths pass cyclic redundancy check （CRC）, multiple CRC-aided variable successive cancellation list （SCL） decoding algorithm is proposed. In the decoding algorithm, the whole unfrozen bits are divided into several parts and each part is concatenated with a corresponding CRC code, except the last part which is concatenated with a whole unfrozen CRC code. Each CRC detection is performed, and only those satisfying each part CRC become the path candidates. A variable list is setup for each part to reduce the time complexity. Variable list size is setup for each part to reduce the time complexity until one survival path in each part can pass its corresponding CRC. The results show that the proposed algorithm can reduce the average list size, and the frame error rate （FER） performance, and has a better performance with the increase of the part number.展开更多
An important production planning problem is how to best schedule jobs(or lots)when each job consists of a large number of identical parts.This problem is often approached by breaking each job/lot into sublots(termed l...An important production planning problem is how to best schedule jobs(or lots)when each job consists of a large number of identical parts.This problem is often approached by breaking each job/lot into sublots(termed lot streaming).When the total number of transfer sublots in lot streaming is large,the computational effort to calculate job completion time can be significant.However,researchers have largely neglected this computation time issue.To provide a practical method for production scheduling for this situation,we propose a method to address the n-job,m-machine,and lot streaming flow-shop scheduling problem.We consider the variable sublot sizes,setup time,and the possibility that transfer sublot sizes may be bounded because of capacity constrained transportation activities.The proposed method has three stages:initial lot splitting,job sequencing optimization with efficient calculation of the makespan/total flow time criterion,and transfer adjustment.Computational experiments are conducted to confirm the effectiveness of the three-stage method.The experiments reveal that relative to results reported on lot streaming problems for five standard datasets,the proposed method saves substantial computation time and provides better solutions,especially for large-size problems.展开更多
A study was conducted on the effect of atmospheric parameters, including temperature, wind speed, and relative humidity, on fine particulate mass concentrations measured in Jiading District of Shanghai, China, during ...A study was conducted on the effect of atmospheric parameters, including temperature, wind speed, and relative humidity, on fine particulate mass concentrations measured in Jiading District of Shanghai, China, during the period from January 2009 to January 2010. A sensitivity analysis was applied to investigate the interaction between atmospheric parameters and particulate mass concentration. The experiment revealed that the concentration of particulates increased with particle size from 0.1 to 1.0 μm, and decreased with the increase of particle size from 1.0 to 2.5 μm. The effects of atmospheric parameters on fine mass concentrations were significantly particle size-dependent. The PM1.0-2.5 may come from the size increase of smaller particulates after moisture absorption, And the variation of concentrations of PM0.1-l.0 was mainly attributed to the accumulation of PM0.1. The ventilation index and dilution index were calcu- lated on the basis of data collected in December 2009. A correlation analysis indicated that there was a significant relation between these two indexes and the particulate concentration by examining the three particle size ranges, 0.0-0.1, 0.1-1.0, and 1,0-2.5 μm. The Spearman correlation coefficients that related the ventilation index to the concentration for the three particle size ranges were -0.45, -0.56 and -0.47, respectively, while the coefficients that related the dilution index to the concentration were -0.36, -0.42 and -0.45, respectively.展开更多
文摘A conventional global contrast enhancement is difficult to apply in various images because image quality and contrast enhancement are dependent on image characteristics largely. And a local contrast enhancement not only causes a washed-out effect, but also blocks. To solve these drawbacks, this paper derives an optimal global equalization function with variable size block based local contrast enhancement. The optimal equalization function makes it possible to get a good quality image through the global contrast enhancement. The variable size block segmentation is firstly exeoated using intensity differences as a measure of similarity. In the second step, the optimal global equalization function is obtained from the enhanced contrast image having variable size blocks. Conformed experiments have showed that the proposed algorithm produces a visually comfortable result image.
基金supported by the National Natural Science Foundation of China(No.52272382)the Fundamental Research Funds for the Central Universities,China。
文摘Path planning is crucial for autonomous flight of fixed-wing Unmanned Aerial Vehicles(UAVs).However,due to the high-speed flight and complex control of fixed-wing UAVs,ensuring the feasibility and safety of planned paths in complex environments is challenging.This paper proposes a feasible path planning algorithm named Closed-loop Radial Ray A^(*)(CL-RaA^(*)).The core components of the CL-RaA^(*)include an adaptive variable-step-size path search and a just-in-time expansion primitive.The former enables fast path search in complex environments,while the latter ensures the feasibility of the generated paths.By integrating these two components and conducting safety checks on the trajectories to be expanded,the CL-RaA^(*)can rapidly generate safe and feasible paths that satisfy the differential constraints that comprehensively consider the dynamics and control characteristics of six-degree-of-freedom fixed-wing UAVs.The final performance tests and simulation validations demonstrate that the CL-RaA^(*)can generate safe and feasible paths in various environments.Compared to feasible path planning algorithms that use the rapidlyexploring random trees,the CL-RaA^(*)not only ensures deterministic planning results in the same scenarios but also generates smoother feasible paths for fixed-wing UAVs more efficiently.In environments with dense grid obstacles,the feasible paths generated by the CL-RaA^(*)are more conducive to UAV tracking compared to those planned using Dubins curves.
基金Natural Science Foundation of Shandong Province of China(No.ZR2012FM011)Shandong University of Science and Technology Research Fund(No.2010KYTD101)
文摘By analyzing algorithms available for variable step size least mean square(LMS)adaptive filter,a new modified LMS adaptive filtering algorithm with variable step size is proposed,along with performance analysis based on different parameters.Compared with the existing algorithms through the simulation,the proposed algorithm has faster convergence speed and smaller steady state error.
基金Sponsored by the National Natural Science Foundation of China(60772066)
文摘The new features of H. 264 video coding standard make the motion estimation module much more time consuming than before. Especially, the motion search is required for each of the 4 modes for inter prediction. In order to reduce the computational complexity, we analyze the statistics of results of motion estimation, such as the continuity of best modes of blocks in successive frames and the chance to give up a sub-partition mode （smaller than 16 × 16） after integer-pixel motion estimation, from which we suggest to make mode prediction based on the motion information of the previous frame and skip sub-pixel motion estimation in subpartition mode selectively. According to the experimental result, the proposed algorithm can save 75 % of the computational time with a slight degradation （0.03 dB） on PSNR compared with the pseudocode of fast search motion estimation in JM12.2.
基金Supported by Natural Science Foundation of Beijing of China (No.2005AA501140)
文摘This paper puts forward a new variable step size LMS adaptive algorithm based on variable region. The step size p（k） in the algorithm varies with the variation of the region of deviation e （k） to ensure the optimization of the three performance objectives including initial convergent speed, trace ability of the time-varying system and steady disregulation. The paper demonstrates the convergence of the algorithm accompanied by random noise,
基金Supported by the National Natural Science Foundation of China(6100201461101129+1 种基金6122700161072050)
文摘The problem of inter symbol interference（ ISI） in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn＇t require a training sequence,a blind equalization channel is implemented in the receiver to increase the throughput of the system. To improve the performances of both the blind equalizer and the system,a joint receiving mechanismincluding variable step size（ VSS） modified constant modulus algorithms（ MC-MA） and modified decision directed modulus algorithms（ MD DMA） is proposed to ameliorate the convergence speed and mean square error（ MSE） performance and combat the phase error when using high order QAM modulation. The VSS scheme is based on the selection of step size according to the distance between the output of the equalizer and the desired output in the constellation plane. Analysis and simulations showthat the performance of the proposed VSS-MCMA-MD DMA mechanismis better than that of algorithms with a fixed step size. In addition,the MCMA-MDDMA with VSS can performthe phase recovery by itself.
文摘The soil packing,influenced by variations in grain size and the gradation pattern within the soil matrix,plays a crucial role in constituting the mechanical properties of sandy soils.However,previous modeling approaches have overlooked incorporating the full range of representative parameters to accurately predict the soaked California bearing ratio(CBR_(s))of sandy soils by precisely articulating soil packing in the modeling framework.This study presents an innovative artificial intelligence(AI)-based approach for modeling the CBR_(s)of sandy soils,considering grain size variability meticulously.By synthesizing extensive data from multiple sources,i.e.extensive tailored testing program undertaking multiple tests and extant literature,various modeling techniques including genetic expression programming(GEP),multi-expression programming(MEP),support vector machine(SVM),and multi-linear regression(MLR)are utilized to develop models.The research explores two modeling strategies,namely simplified and composite,with the former incorporating only sieve analysis test parameters,while the latter includes compaction test parameters alongside sieve analysis data.The models'performance is assessed using statistical key performance indicators(KPIs).Results indicate that genetic AI-based algorithms,particularly GEP,outperform SVM and conventional regression techniques,effectively capturing complex relationships between input parameters and CBR_(s).Additionally,the study reveals insights into model performance concerning the number of input parameters,with GEP consistently outperforming other models.External validation and Taylor diagram analysis demonstrate the GEP models'superiority over existing literature models on an independent dataset from the literature.Parametric and sensitivity analyses highlight the intricate relationships between grain sizes and CBR_(s),further emphasizing GEP's efficacy in modeling such complexities.This study contributes to enhancing CBR_(s)modeling accuracy for sandy soils,crucial for pertinent infrastructure design and construction rapidly and cost-effectively.
文摘Understanding how population sizes vary over time is a key aspect of ecological research. Unfortunately, our under- standing of population dynamics has historically been based on an assumption that individuals are identical with homogenous life-history properties. This assumption is certainly false for most natural systems, raising the question of what role individual variation plays in the dynamics of populations. While there has been an increase of interest regarding the effects of within popula- tion variation on the dynamics of single populations, there has been little study of the effects of differences in within population variation on patterns observed across populations. We found that life-history differences （clutch size） among individuals ex- plained the majority of the variation observed in the degree to which population sizes of eastern fence lizards Sceloporus undula- tus fluctuated. This finding suggests that differences across populations cannot be understood without an examination of differences at the level of a system rather than at the level of the individual
文摘In order to improve the problem that the filtered-x least mean square(FxLMS)algorithm cannot take into account the convergence speed,steady-state error during active noise control.A piecewise variable step size FxLMS algorithm based on logarithmic function(PLFxLMS)is proposed,and the genetic algorithm are introduced to optimize the parameters of logarithmic variable step size FxLMS(LFxLMS),improved logarithmic variable step size Films(IFxLMS),and PLFxLMS algorithms.Bandlimited white noise is used as the input signal,FxLMS,LFxLMS,ILFxLMS,and PLFxLMS algorithms are used to conduct active noise control simulation,and the convergence speed and steady-state characteristic of four algorithms are comparatively analyzed.Compared with the other three algorithms,the PLFxLMS algorithm proposed in this paper has the fastest convergence speed,and small steady-state error.The PLFxLMS algorithm can effectively improve the convergence speed and steady-state error of the FxLMS algorithm that cannot be controlled at the same time,and achieve the optimal effect.
基金The National Natural Science Foundation of China(No50475073,50775036)the High Technology Research Program of Jiangsu Province(NoBG2006035)
文摘An improved finite difference method （FDM）is described to solve existing problems such as low efficiency and poor convergence performance in the traditional method adopted to derive the pressure distribution of aerostatic bearings. A detailed theoretical analysis of the pressure distribution of the orifice-compensated aerostatic journal bearing is presented. The nonlinear dimensionless Reynolds equation of the aerostatic journal bearing is solved by the finite difference method. Based on the principle of flow equilibrium, a new iterative algorithm named the variable step size successive approximation method is presented to adjust the pressure at the orifice in the iterative process and enhance the efficiency and convergence performance of the algorithm. A general program is developed to analyze the pressure distribution of the aerostatic journal bearing by Matlab tool. The results show that the improved finite difference method is highly effective, reliable, stable, and convergent. Even when very thin gas film thicknesses （less than 2 Win）are considered, the improved calculation method still yields a result and converges fast.
基金This work was supported by the National Key Research and Development Program of China(Grant No.2018YFF0213602).
文摘Acoustic echo cancellation is often applied in communication and video call system to reduce unnecessary echoes generated between speakers and microphones.In these systems,the speech input signal of the adaptive filter is often colored and unstable,which decays the convergence rate of the adaptive filter if the NLMS algorithm is used.In this paper,an improved nonparametric variable step-size subband(NPVSS-NSAF)algorithm is proposed to address the problem.The variable step-size is derived by minimizing the sum of the square Euclidean norm of the difference between the optimal weight vectors to be updated and the past estimated weight vectors.Then the parameters are eliminated by using the power of subband signal noise equal to the power of subband posteriori error.The performance of the proposed algorithm is simulated in the aspects of misalignment and return loss enhancement.Experiment results show a fast convergence rate and low misalignment of the proposed algorithm in system identification.
文摘In issues like hearing impairment,speech therapy and hearing aids play a major role in reducing the impairment.Removal of noise signals from speech signals is a key task in hearing aids as well as in speech therapy.During the transmission of speech signals,several noise components contaminate the actual speech components.This paper addresses a new adaptive speech enhancement(ASE)method based on a modified version of singular spectrum analysis(MSSA).The MSSA generates a reference signal for ASE and makes the ASE is free from feeding reference component.The MSSA adopts three key steps for generating the reference from the contaminated speech only.These are decomposition,grouping and reconstruction.The generated reference is taken as a reference for variable size adaptive learning algorithms.In this work two categories of adaptive learning algorithms are used.They are step variable adaptive learning(SVAL)algorithm and time variable step size adaptive learning(TVAL).Further,sign regressor function is applied to adaptive learning algorithms to reduce the computational complexity of the proposed adaptive learning algorithms.The performance measures of the proposed schemes are calculated in terms of signal to noise ratio improvement(SNRI),excess mean square error(EMSE)and misadjustment(MSD).For cockpit noise these measures are found to be 29.2850,-27.6060 and 0.0758 dB respectively during the experiments using SVAL algorithm.By considering the reduced number of multiplications the sign regressor version of SVAL based ASE method is found to better then the counter parts.
文摘Background: Benign prostate hyperplasia (BPH) is the most common benign disease of human prostate. Currently BPH is associated with unregulated proliferation of connective tissue and glandular epithelium within the prostatic transition zone, and it has been described as relevant characteristic of BPH—the increase of the total number of cells, and not only an increase in cell size. To date, there are few studies on the quantitative morphology of glandular tree of BPH compared with normal prostate. The scarce investigations about this particular suggest that the glandular tree branches and expands as the hyperplastic transformation occurs in the prostate. Methods: To verify if this gland expansion and branching was similar to that occurs in the normal prostate, this study deals with the estimation of several stereological parameters as: labeling index for the proliferating cell nuclear antigen to quantify the rate of proliferation of prostate epithelium, average thickness of glandular epithelium, fraction of the volume occupied by the epithelium relative to the total prostate volume, connectivity density of prostate glands, to quantify the branching of prostate glands, and the average volume and the volume-weighted mean glandular volume of prostate acini to assess the mean size of the prostate acini and its variability. Results: All these estimates have been performed in prostate specific antigen immunostained sections from prostates of young men (controls) and in adenomectomy specimens from the adenofibromiomatous variety of BPH. Conclusion: We conclude that the epithelial proliferation is not the only factor intervening in the development of BPH. In addition, a more prolonged survival of epithelial population, together with some degree of hypertrophy of acini expressed by the increase of volume fraction and thickness of acinar epithelium, is relevant in order to the growth and expansion of the BPH glandular tree that shows more abundant and heterogeneous acinar sprouts than in normal prostate.
基金supported by the National Natural Science Foundation of China Under Grant No.61773008.
文摘According to the relationship between truncation error and step size of two implicit second-order-derivative multistep formulas based on Hermite interpolation polynomial,a variable-order and variable-step-size numerical method for solving differential equations is designed.The stability properties of the formulas are discussed and the stability regions are analyzed.The deduced methods are applied to a simulation problem.The results show that the numerical method can satisfy calculation accuracy,reduce the number of calculation steps and accelerate calculation speed.
基金the Natural Science Basic Research Project of Shaanxi Province,China(2020JM-583)。
文摘Addressing the impact of capacitor mismatch on the conversion accuracy of successive approximation register analog-to-digital converter(SAR ADC),a 12-bit 1 MS/s sub-binary SAR ADC designed using variable step size digital calibration was proposed.The least mean square(LMS)calibration algorithm was employed with a ramp signal used as the calibration input.Weight errors,extracted under injected disturbances,underwent iterative training to optimize weight values.To address the trade-off between conversion accuracy and speed caused by a fixed step size,a novel variable step size algorithm tailored for SAR ADC calibration was proposed.The core circuit and layout of the SAR ADC were implemented using the Taiwan Semiconductor Manufacturing Company(TSMC)0.35μm complementary metal-oxide-semiconductor(CMOS)commercial process.Simulation of the SAR ADC calibration algorithm was conducted using Simulink,demonstrating quick convergence and meeting conversion accuracy requirements compared to fixed step size simulation.The results indicated that the convergence speed of the LMS digital calibration algorithm with variable step size was approximately eight times faster than that with a fixed step size,also yielding a lower mean square error(MSE).After calibration,the simulation results for the SAR ADC exhibited an effective number of bit(ENOB)of 11.79 bit and a signal-to-noise and distortion ratio(SNDR)of 72.72 dB,signifying a notable enhancement in the SAR ADC performance.
基金supported by General Administration of Quality Supervision,Inspection and Quarantine of the People's Republic of China (2012IK169)National Natural Science Youth Foundation of China (21205053).
文摘Near infrared spectroscopy(NIRS),coupled with principal component analysis and wavelength selection techniques,has been sed to develop a robust and reliable reduced-spectrum classifi-cation model for determining the geographical origins of Nanfeng mandarins.The application of the changeable size moving window principal component analysis(CSMWPCA)provided a notably improved lassification model,with correct classification rates of 92.00%,100.00%,90.00%,100.00%,100.00%,100.00%and 100.00%for Fujian,Guangxi,Hunan,Baishe,Baofeng,Qiawan,Sanxi samples,respectively,as well as,a total dassification rate of 97.52%in the wavelength range from 1007 to 1296 nm.To test and apply the proposed method,the procedure was applied to the analysis of 59 samples in an independent test set.Good identification results(correct rate of 96.61%)were also received.The improvement achieved by the application of CSMWPCA method was particularly remarkable when taking the low complexities of the final model(290 variables)into account.The results of the study showed the great potential of NIRS as a fast,nondestructive and environmentally acceptable method for the rapid and reliable determination for geographical classifcation of Nanfeng mandarins.
文摘For medium and high permeability oilfields, filling sand control technology is one of the main measures to prevent formation sand production and achieve stable production and increase production.As the largest oil-bearing block in Qudi oilfield, Qu9 fault block has serious sand production in Guan3 formation, and sand control is required to meet normal production.Through the continuous development and optimization of sand control technology, in recent years, the commonly used sand control technologies in Qudi oilfield include squeeze filling sand control, chemical sand control, cyclic filling and other processes. It is found that the squeeze filling process can better meet the needs of Qu9 Guan3 block.At the same time, Qu9 Guan3 block has problems such as high shale content, strong sensitivity and thick crude oil viscosity. It is necessary to optimize the squeeze filling sand control process, and put forward supporting technologies such as pre reservoir cleaning agent and variable particle size graded sand addition, so as to better transform the formation, improve seepage efficiency and enhance the productivity of single wells while doing a good job in reservoir protection.
基金supported by the National Natural Science Foundation of China (61475075,61271238)the Open Research Fund of Key Laboratory of Broadband Wireless Communication and Sensor Network Technology,Ministry of Education (NYKL2015011)
文摘In order to change the path candidates, reduce the average list size, and make more paths pass cyclic redundancy check （CRC）, multiple CRC-aided variable successive cancellation list （SCL） decoding algorithm is proposed. In the decoding algorithm, the whole unfrozen bits are divided into several parts and each part is concatenated with a corresponding CRC code, except the last part which is concatenated with a whole unfrozen CRC code. Each CRC detection is performed, and only those satisfying each part CRC become the path candidates. A variable list is setup for each part to reduce the time complexity. Variable list size is setup for each part to reduce the time complexity until one survival path in each part can pass its corresponding CRC. The results show that the proposed algorithm can reduce the average list size, and the frame error rate （FER） performance, and has a better performance with the increase of the part number.
基金Project supported by the National Natural Science Foundation of China(No.61403163)the Zhejiang Provincial Natural Science Foundation of China(Nos.LQ14G010008 and LY15F030021)
文摘An important production planning problem is how to best schedule jobs(or lots)when each job consists of a large number of identical parts.This problem is often approached by breaking each job/lot into sublots(termed lot streaming).When the total number of transfer sublots in lot streaming is large,the computational effort to calculate job completion time can be significant.However,researchers have largely neglected this computation time issue.To provide a practical method for production scheduling for this situation,we propose a method to address the n-job,m-machine,and lot streaming flow-shop scheduling problem.We consider the variable sublot sizes,setup time,and the possibility that transfer sublot sizes may be bounded because of capacity constrained transportation activities.The proposed method has three stages:initial lot splitting,job sequencing optimization with efficient calculation of the makespan/total flow time criterion,and transfer adjustment.Computational experiments are conducted to confirm the effectiveness of the three-stage method.The experiments reveal that relative to results reported on lot streaming problems for five standard datasets,the proposed method saves substantial computation time and provides better solutions,especially for large-size problems.
基金supported by the Knowledge Innovation Project of the Chinese Academy of Sciences(KJCX-3SYW-N3)the National Natural Science Foundation of China(10775174)+2 种基金the National Natural Science Foundation of China(11005144)Basic Research Key Project of Shanghai Committee of Science and Technology (10JC1417200)the Shanghai Natural Science Foundation (3109ZR1438200)
文摘A study was conducted on the effect of atmospheric parameters, including temperature, wind speed, and relative humidity, on fine particulate mass concentrations measured in Jiading District of Shanghai, China, during the period from January 2009 to January 2010. A sensitivity analysis was applied to investigate the interaction between atmospheric parameters and particulate mass concentration. The experiment revealed that the concentration of particulates increased with particle size from 0.1 to 1.0 μm, and decreased with the increase of particle size from 1.0 to 2.5 μm. The effects of atmospheric parameters on fine mass concentrations were significantly particle size-dependent. The PM1.0-2.5 may come from the size increase of smaller particulates after moisture absorption, And the variation of concentrations of PM0.1-l.0 was mainly attributed to the accumulation of PM0.1. The ventilation index and dilution index were calcu- lated on the basis of data collected in December 2009. A correlation analysis indicated that there was a significant relation between these two indexes and the particulate concentration by examining the three particle size ranges, 0.0-0.1, 0.1-1.0, and 1,0-2.5 μm. The Spearman correlation coefficients that related the ventilation index to the concentration for the three particle size ranges were -0.45, -0.56 and -0.47, respectively, while the coefficients that related the dilution index to the concentration were -0.36, -0.42 and -0.45, respectively.
