Based on the iterative bit-filling procedure, a computationally efficient bit and power allocation algorithm is presented. The algorithm improves the conventional bit-filling algorithms by maintaining only a subset of...Based on the iterative bit-filling procedure, a computationally efficient bit and power allocation algorithm is presented. The algorithm improves the conventional bit-filling algorithms by maintaining only a subset of subcarriers for computation in each iteration, which reduces the complexity without any performance degradation. Moreover, a modified algorithm with even lower complexity is developed, and equal power allocation is introduced as an initial allocation to accelerate its convergence. Simulation results show that the modified algorithm achieves a considerable complexity reduction while causing only a minor drop in performance.展开更多
Computational time complexity analyzes of evolutionary algorithms （EAs） have been performed since the mid-nineties. The first results were related to very simple algorithms, such as the （1＋1）-EA, on toy problems....Computational time complexity analyzes of evolutionary algorithms （EAs） have been performed since the mid-nineties. The first results were related to very simple algorithms, such as the （1＋1）-EA, on toy problems. These efforts produced a deeper understanding of how EAs perform on different kinds of fitness landscapes and general mathematical tools that may be extended to the analysis of more complicated EAs on more realistic problems. In fact, in recent years, it has been possible to analyze the （1＋1）-EA on combinatorial optimization problems with practical applications and more realistic population-based EAs on structured toy problems. This paper presents a survey of the results obtained in the last decade along these two research lines. The most common mathematical techniques are introduced, the basic ideas behind them are discussed and their elective applications are highlighted. Solved problems that were still open are enumerated as are those still awaiting for a solution. New questions and problems arisen in the meantime are also considered.展开更多
In this work,the computational complexity of a spin-glass three-dimensional(3D)Ising model(for the lattice sizeN=lmn,wherel,m,n are thenumbersof lattice points along three crystallographic directions)is studied.We pro...In this work,the computational complexity of a spin-glass three-dimensional(3D)Ising model(for the lattice sizeN=lmn,wherel,m,n are thenumbersof lattice points along three crystallographic directions)is studied.We prove that an absolute minimum core(AMC)model consisting of a spin-glass 2D Ising model interacting with its nearest neighboring plane,has its computational complexity O(2mn).Any algorithms to make the model smaller(or simpler)than the AMC model will cut the basic element of the spin-glass 3D Ising model and lost many important information of the original model.Therefore,the computational complexity of the spin-glass 3D Ising model cannot be reduced to be less than O(2mn)by any algorithms,which is in subexponential time,superpolynomial.展开更多
For future wireless communication systems,Power Domain Non-Orthogonal Multiple Access(PD-NOMA)using an advanced receiver has been considered as a promising radio access technology candidate.Power allocation plays an i...For future wireless communication systems,Power Domain Non-Orthogonal Multiple Access(PD-NOMA)using an advanced receiver has been considered as a promising radio access technology candidate.Power allocation plays an important role in the PD-NOMA system because it considerably affects the total throughput and Geometric Mean User Throughput(GMUT)performance.However,most existing studies have not completely accounted for the computational complexity of the power allocation process when the User Terminals(UTs)move in a slow fading channel environment.To resolve such problems,a power allocation method is proposed to considerably reduce the search space of a Full Search Power(FSP)allocation algorithm.The initial power reallocation coefficients will be set to start with former optimal values by the proposed Lemma before searching for optimal power reallocation coefficients based on total throughput performance.Step size and correction granularity will be adjusted within a much narrower power search range while invalid power combinations may be reasonably discarded during the search process.The simulation results show that the proposed power reallocation scheme can greatly reduce computational complexity while the total throughput and GMUT performance loss are not greater than 1.5%compared with the FSP algorithm.展开更多
The prediction of intrinsically disordered proteins is a hot research area in bio-information.Due to the high cost of experimental methods to evaluate disordered regions of protein sequences,it is becoming increasingl...The prediction of intrinsically disordered proteins is a hot research area in bio-information.Due to the high cost of experimental methods to evaluate disordered regions of protein sequences,it is becoming increasingly important to predict those regions through computational methods.In this paper,we developed a novel scheme by employing sequence complexity to calculate six features for each residue of a protein sequence,which includes the Shannon entropy,the topological entropy,the sample entropy and three amino acid preferences including Remark 465,Deleage/Roux,and Bfactor(2STD).Particularly,we introduced the sample entropy for calculating time series complexity by mapping the amino acid sequence to a time series of 0-9.To our knowledge,the sample entropy has not been previously used for predicting IDPs and hence is being used for the first time in our study.In addition,the scheme used a properly sized sliding window in every protein sequence which greatly improved the prediction performance.Finally,we used seven machine learning algorithms and tested with 10-fold cross-validation to get the results on the dataset R80 collected by Yang et al.and of the dataset DIS1556 from the Database of Protein Disorder(DisProt)(https://www.disprot.org)containing experimentally determined intrinsically disordered proteins(IDPs).The results showed that k-Nearest Neighbor was more appropriate and an overall prediction accuracy of 92%.Furthermore,our method just used six features and hence required lower computational complexity.展开更多
The variable block-size motion estimation(ME) and disparity estimation(DE) are adopted in multi-view video coding(MVC) to achieve high coding efficiency. However, much higher computational complexity is also introduce...The variable block-size motion estimation(ME) and disparity estimation(DE) are adopted in multi-view video coding(MVC) to achieve high coding efficiency. However, much higher computational complexity is also introduced in coding system, which hinders practical application of MVC. An efficient fast mode decision method using mode complexity is proposed to reduce the computational complexity. In the proposed method, mode complexity is firstly computed by using the spatial, temporal and inter-view correlation between the current macroblock(MB) and its neighboring MBs. Based on the observation that direct mode is highly possible to be the optimal mode, mode complexity is always checked in advance whether it is below a predefined threshold for providing an efficient early termination opportunity. If this early termination condition is not met, three mode types for the MBs are classified according to the value of mode complexity, i.e., simple mode, medium mode and complex mode, to speed up the encoding process by reducing the number of the variable block modes required to be checked. Furthermore, for simple and medium mode region, the rate distortion(RD) cost of mode 16×16 in the temporal prediction direction is compared with that of the disparity prediction direction, to determine in advance whether the optimal prediction direction is in the temporal prediction direction or not, for skipping unnecessary disparity estimation. Experimental results show that the proposed method is able to significantly reduce the computational load by 78.79% and the total bit rate by 0.07% on average, while only incurring a negligible loss of PSNR(about 0.04 d B on average), compared with the full mode decision(FMD) in the reference software of MVC.展开更多
The title complex is widely used as an efficient key component of Ziegler-Natta catalyst for stereospecific polymerization of dienes to produce synthetic rubbers. However, the quantitative structure-activity relations...The title complex is widely used as an efficient key component of Ziegler-Natta catalyst for stereospecific polymerization of dienes to produce synthetic rubbers. However, the quantitative structure-activity relationship（QSAR） of this kind of complexes is still not clear mainly due to the difficulties to obtain their geometric molecular structures through laboratory experiments. An alternative solution is the quantum chemistry calculation in which the comformational population shall be determined. In this study, ten conformers of the title complex were obtained with the function of molecular dynamics conformational search in Gabedit 2.4.8, and their geometry optimization and thermodynamics calculation were made with a Sparkle/PM7 approach in MOPAC 2012. Their Gibbs free energies at 1 atm. and 298.15 K were calculated. Population of the conformers was further calculated out according to the theory of Boltzmann distribution, indicating that one of the ten conformers has a dominant population of 77.13%.展开更多
The state-of-art Computational Fluid Dynamics （CFD） codes FLUENT is applied in a fine-scale simulation of the wind field over a complex terrain. Several numerical tests are performed to validate the capability of FL...The state-of-art Computational Fluid Dynamics （CFD） codes FLUENT is applied in a fine-scale simulation of the wind field over a complex terrain. Several numerical tests are performed to validate the capability of FLUENT on describing the wind field details over a complex terrain. The results of the numerical tests show that FLUENT can simulate the wind field over extremely complex terrain, which cannot be simulated by mesoscale models. The reason why FLUENT can cope with extremely complex terrain, which can not be coped with by mesoscale models, relies on some particular techniques adopted by FLUENT, such as computer-aided design （CAD） technique, unstructured grid technique and finite volume method. Compared with mesoscale models, FLUENT can describe terrain in much more accurate details and can provide wind simulation results with higher resolution and more accuracy.展开更多
In this advanced exploration, we focus on multiple parameters estimation in bistatic Multiple-Input Multiple-Output(MIMO) radar systems, a crucial technique for target localization and imaging. Our research innovative...In this advanced exploration, we focus on multiple parameters estimation in bistatic Multiple-Input Multiple-Output(MIMO) radar systems, a crucial technique for target localization and imaging. Our research innovatively addresses the joint estimation of the Direction of Departure(DOD), Direction of Arrival(DOA), and Doppler frequency for incoherent targets. We propose a novel approach that significantly reduces computational complexity by utilizing the TemporalSpatial Nested Sampling Model(TSNSM). Our methodology begins with a multi-linear mapping mechanism to efficiently eliminate unnecessary virtual Degrees of Freedom(DOFs) and reorganize the remaining ones. We then employ the Toeplitz matrix triple iteration reconstruction method, surpassing the traditional Temporal-Spatial Smoothing Window(TSSW) approach, to mitigate the single snapshot effect and reduce computational demands. We further refine the highdimensional ESPRIT algorithm for joint estimation of DOD, DOA, and Doppler frequency, eliminating the need for additional parameter pairing. Moreover, we meticulously derive the Cramér-Rao Bound(CRB) for the TSNSM. This signal model allows for a second expansion of DOFs in time and space domains, achieving high precision in target angle and Doppler frequency estimation with low computational complexity. Our adaptable algorithm is validated through simulations and is suitable for sparse array MIMO radars with various structures, ensuring higher precision in parameter estimation with less complexity burden.展开更多
Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pP...Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.展开更多
Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems,such as thermal power plants being studied in this work.Industrial processes are inherently d...Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems,such as thermal power plants being studied in this work.Industrial processes are inherently dynamic and need to be monitored using dynamic algorithms.Mainstream dynamic algorithms rely on concatenating current measurement with past data.This work proposes a new,alternative dynamic process monitoring algorithm,using dot product feature analysis(DPFA).DPFA computes the dot product of consecutive samples,thus naturally capturing the process dynamics through temporal correlation.At the same time,DPFA's online computational complexity is lower than not just existing dynamic algorithms,but also classical static algorithms(e.g.,principal component analysis and slow feature analysis).The detectability of the new algorithm is analyzed for three types of faults typically seen in process systems:sensor bias,process fault and gain change fault.Through experiments with a numerical example and real data from a thermal power plant,the DPFA algorithm is shown to be superior to the state-of-the-art methods,in terms of better monitoring performance(fault detection rate and false alarm rate)and lower computational complexity.展开更多
Safety maintenance of power equipment is of great importance in power grids,in which image-processing-based defect recognition is supposed to classify abnormal conditions during daily inspection.However,owing to the b...Safety maintenance of power equipment is of great importance in power grids,in which image-processing-based defect recognition is supposed to classify abnormal conditions during daily inspection.However,owing to the blurred features of defect images,the current defect recognition algorithm has poor fine-grained recognition ability.Visual attention can achieve fine-grained recognition with its abil-ity to model long-range dependencies while introducing extra computational complexity,especially for multi-head attention in vision transformer structures.Under these circumstances,this paper proposes a self-reduction multi-head attention module that can reduce computational complexity and be easily combined with a Convolutional Neural Network(CNN).In this manner,local and global fea-tures can be calculated simultaneously in our proposed structure,aiming to improve the defect recognition performance.Specifically,the proposed self-reduction multi-head attention can reduce redundant parameters,thereby solving the problem of limited computational resources.Experimental results were obtained based on the defect dataset collected from the substation.The results demonstrated the efficiency and superiority of the proposed method over other advanced algorithms.展开更多
A central problem in the study of complexity is the measure of nonuniform complexity classes. BPPP/poly has been proved by Aldman, and EXPSPACEP/poly by Kannan. We propose the definition of approximate acceptance with...A central problem in the study of complexity is the measure of nonuniform complexity classes. BPPP/poly has been proved by Aldman, and EXPSPACEP/poly by Kannan. We propose the definition of approximate acceptance with which we discuss the nonuniform complexity of the K sized complete subgraph problem. The method of modal theory is used and the K sized complete subgraph problemP/poly, co NPP/poly and NPP/poly is proved. This paper solves the Karp Lipton′s open problem: “NPP/poly?”展开更多
Unmanned aerial vehicles(UAVs) may play an important role in data collection and offloading in vast areas deploying wireless sensor networks, and the UAV’s action strategy has a vital influence on achieving applicabi...Unmanned aerial vehicles(UAVs) may play an important role in data collection and offloading in vast areas deploying wireless sensor networks, and the UAV’s action strategy has a vital influence on achieving applicability and computational complexity. Dynamic programming(DP) has a good application in the path planning of UAV, but there are problems in the applicability of special terrain environment and the complexity of the algorithm.Based on the analysis of DP, this paper proposes a hierarchical directional DP(DDP) algorithm based on direction determination and hierarchical model. We compare our methods with Q-learning and DP algorithm by experiments, and the results show that our method can improve the terrain applicability, meanwhile greatly reduce the computational complexity.展开更多
Inertial navigation system/visual navigation system(INS/VNS) integrated navigation is a commonly used autonomous navigation method for planetary rovers. Since visual measurements are related to the previous and curren...Inertial navigation system/visual navigation system(INS/VNS) integrated navigation is a commonly used autonomous navigation method for planetary rovers. Since visual measurements are related to the previous and current state vectors(position and attitude) of planetary rovers, the performance of the Kalman filter(KF) will be challenged by the time-correlation problem. A state augmentation method, which augments the previous state value to the state vector, is commonly used when dealing with this problem. However, the augmenting of state dimensions will result in an increase in computation load. In this paper, a state dimension reduced INS/VNS integrated navigation method based on coordinates of feature points is presented that utilizes the information obtained through INS/VNS integrated navigation at a previous moment to overcome the time relevance problem and reduce the dimensions of the state vector. Equations of extended Kalman filter(EKF) are used to demonstrate the equivalence of calculated results between the proposed method and traditional state augmented methods. Results of simulation and experimentation indicate that this method has less computational load but similar accuracy when compared with traditional methods.展开更多
Recently, network coding has been applied to the loss recovery of reliable broadcast transmission in wireless networks. Since it was proved that fi nding the optimal set of lost packets for XOR-ing is a complex NP-com...Recently, network coding has been applied to the loss recovery of reliable broadcast transmission in wireless networks. Since it was proved that fi nding the optimal set of lost packets for XOR-ing is a complex NP-complete problem, the available time-based retransmission scheme and its enhanced retransmission scheme have exponential computational complexity and thus are not scalable to large networks. In this paper, we present an efficient heuristic scheme based on hypergraph coloring and also its enhanced heuristic scheme to improve the transmission efficiency. Basically, our proposed schemes fi rst create a hypergraph according to the packet-loss matrix. Then our schemes solve the problem of generating XORed packets by coloring the edges of hypergraph. Extensive simulation results demonstrate that, the heuristic scheme based on hypergraph coloring and its enhanced scheme can achieve almost the same transmission efficiency as the available ones, but have much lower computational complexity, which is very important for the wireless devices without high computation capacity.展开更多
The maximum likelihood （ML） estimator demonstrates remarkable performance in direction of arrival （DOA） estimation for the multiple input multiple output （MIMO） sonar. However, this advantage comes with prohibit...The maximum likelihood （ML） estimator demonstrates remarkable performance in direction of arrival （DOA） estimation for the multiple input multiple output （MIMO） sonar. However, this advantage comes with prohibitive computational complexity. In order to solve this problem, an ant colony optimization （ACO） is incorporated into the MIMO ML DOA estimator. Based on the ACO, a novel MIMO ML DOA estimator named the MIMO ACO ML （ML DOA estimator based on ACO for MIMO sonar） with even lower computational complexity is proposed. By extending the pheromone remaining process to the pheromone Gaussian kernel probability distribution function in the continuous space, the pro- posed algorithm achieves the global optimum value of the MIMO ML DOA estimator. Simulations and experimental results show that the computational cost of MIMO ACO ML is only 1/6 of the MIMO ML algorithm, while maintaining similar performance with the MIMO ML method.展开更多
In order to reduce the computational complexity of the high efficiency video coding(HEVC) standard, a new algorithm for HEVC intra prediction, namely, fast prediction unit(PU) size selection method for HEVC based on s...In order to reduce the computational complexity of the high efficiency video coding(HEVC) standard, a new algorithm for HEVC intra prediction, namely, fast prediction unit(PU) size selection method for HEVC based on salient regions is proposed in this paper. We first build a saliency map for each largest coding unit(LCU) to reduce its texture complexity. Secondly, the optimal PU size is determined via a scheme that implements an information entropy comparison among sub-blocks of saliency maps. Finally, we apply the partitioning result of saliency map on the original LCUs, obtaining the optimal partitioning result. Our algorithm can determine the PU size in advance to the angular prediction in intra coding, reducing computational complexity of HEVC. The experimental results show that our algorithm achieves a 37.9% reduction in encoding time, while producing a negligible loss in Bjontegaard delta bit rate(BDBR) of 0.62%.展开更多
In this paper,a two-stage semi-hybrid flowshop problem which appears in graphics processing is studied. For this problem, there are two machines M1 and M2, and a set of independent jobs J= {J1 ,J2 ,…,Jn }. Each Ji co...In this paper,a two-stage semi-hybrid flowshop problem which appears in graphics processing is studied. For this problem, there are two machines M1 and M2, and a set of independent jobs J= {J1 ,J2 ,…,Jn }. Each Ji consists of two tasks Ai and Bi ,and task Ai must be completed before task Bi can start. Furthermore ,task Ai can be processed on M1 for ai time units ,or on Mw for ai^J time units ,while task Bi can only be processed on M2 for bi time units. Jobs and machines are available at time zero and no preemption is allowed. The objective is to minimize the maximum job completion time. It is showed that this problem is NP-hard. And a pseudo-polynomial time optimal algorithm is presented. A polynomial time approximation algorithm with worst-case ratio 2 is also presented.展开更多
基金The National High Technology Research and Devel-opment Program of China (863Program) (No2006AA01Z263)the National Natural Science Foundation of China (No60496311)
文摘Based on the iterative bit-filling procedure, a computationally efficient bit and power allocation algorithm is presented. The algorithm improves the conventional bit-filling algorithms by maintaining only a subset of subcarriers for computation in each iteration, which reduces the complexity without any performance degradation. Moreover, a modified algorithm with even lower complexity is developed, and equal power allocation is introduced as an initial allocation to accelerate its convergence. Simulation results show that the modified algorithm achieves a considerable complexity reduction while causing only a minor drop in performance.
基金This work was supported by an EPSRC grant (No.EP/C520696/1).
文摘Computational time complexity analyzes of evolutionary algorithms （EAs） have been performed since the mid-nineties. The first results were related to very simple algorithms, such as the （1＋1）-EA, on toy problems. These efforts produced a deeper understanding of how EAs perform on different kinds of fitness landscapes and general mathematical tools that may be extended to the analysis of more complicated EAs on more realistic problems. In fact, in recent years, it has been possible to analyze the （1＋1）-EA on combinatorial optimization problems with practical applications and more realistic population-based EAs on structured toy problems. This paper presents a survey of the results obtained in the last decade along these two research lines. The most common mathematical techniques are introduced, the basic ideas behind them are discussed and their elective applications are highlighted. Solved problems that were still open are enumerated as are those still awaiting for a solution. New questions and problems arisen in the meantime are also considered.
基金This work has been supported by the National Natural Science Foundation of China under grant numbers 51590883 and 51331006by the State Key Project of Research and Development of China(No.2017YFA0206302).
文摘In this work,the computational complexity of a spin-glass three-dimensional(3D)Ising model(for the lattice sizeN=lmn,wherel,m,n are thenumbersof lattice points along three crystallographic directions)is studied.We prove that an absolute minimum core(AMC)model consisting of a spin-glass 2D Ising model interacting with its nearest neighboring plane,has its computational complexity O(2mn).Any algorithms to make the model smaller(or simpler)than the AMC model will cut the basic element of the spin-glass 3D Ising model and lost many important information of the original model.Therefore,the computational complexity of the spin-glass 3D Ising model cannot be reduced to be less than O(2mn)by any algorithms,which is in subexponential time,superpolynomial.
基金supported in part by the Science and Technology Research Program of the National Science Foundation of China(61671096)Chongqing Research Program of Basic Science and Frontier Technology(cstc2017jcyjBX0005)+1 种基金Chongqing Municipal Education Commission(KJQN201800642)Doctoral Student Training Program(BYJS2016009).
文摘For future wireless communication systems,Power Domain Non-Orthogonal Multiple Access(PD-NOMA)using an advanced receiver has been considered as a promising radio access technology candidate.Power allocation plays an important role in the PD-NOMA system because it considerably affects the total throughput and Geometric Mean User Throughput(GMUT)performance.However,most existing studies have not completely accounted for the computational complexity of the power allocation process when the User Terminals(UTs)move in a slow fading channel environment.To resolve such problems,a power allocation method is proposed to considerably reduce the search space of a Full Search Power(FSP)allocation algorithm.The initial power reallocation coefficients will be set to start with former optimal values by the proposed Lemma before searching for optimal power reallocation coefficients based on total throughput performance.Step size and correction granularity will be adjusted within a much narrower power search range while invalid power combinations may be reasonably discarded during the search process.The simulation results show that the proposed power reallocation scheme can greatly reduce computational complexity while the total throughput and GMUT performance loss are not greater than 1.5%compared with the FSP algorithm.
文摘The prediction of intrinsically disordered proteins is a hot research area in bio-information.Due to the high cost of experimental methods to evaluate disordered regions of protein sequences,it is becoming increasingly important to predict those regions through computational methods.In this paper,we developed a novel scheme by employing sequence complexity to calculate six features for each residue of a protein sequence,which includes the Shannon entropy,the topological entropy,the sample entropy and three amino acid preferences including Remark 465,Deleage/Roux,and Bfactor(2STD).Particularly,we introduced the sample entropy for calculating time series complexity by mapping the amino acid sequence to a time series of 0-9.To our knowledge,the sample entropy has not been previously used for predicting IDPs and hence is being used for the first time in our study.In addition,the scheme used a properly sized sliding window in every protein sequence which greatly improved the prediction performance.Finally,we used seven machine learning algorithms and tested with 10-fold cross-validation to get the results on the dataset R80 collected by Yang et al.and of the dataset DIS1556 from the Database of Protein Disorder(DisProt)(https://www.disprot.org)containing experimentally determined intrinsically disordered proteins(IDPs).The results showed that k-Nearest Neighbor was more appropriate and an overall prediction accuracy of 92%.Furthermore,our method just used six features and hence required lower computational complexity.
基金Project(08Y29-7)supported by the Transportation Science and Research Program of Jiangsu Province,ChinaProject(201103051)supported by the Major Infrastructure Program of the Health Monitoring System Hardware Platform Based on Sensor Network Node,China+1 种基金Project(61100111)supported by the National Natural Science Foundation of ChinaProject(BE2011169)supported by the Scientific and Technical Supporting Program of Jiangsu Province,China
文摘The variable block-size motion estimation(ME) and disparity estimation(DE) are adopted in multi-view video coding(MVC) to achieve high coding efficiency. However, much higher computational complexity is also introduced in coding system, which hinders practical application of MVC. An efficient fast mode decision method using mode complexity is proposed to reduce the computational complexity. In the proposed method, mode complexity is firstly computed by using the spatial, temporal and inter-view correlation between the current macroblock(MB) and its neighboring MBs. Based on the observation that direct mode is highly possible to be the optimal mode, mode complexity is always checked in advance whether it is below a predefined threshold for providing an efficient early termination opportunity. If this early termination condition is not met, three mode types for the MBs are classified according to the value of mode complexity, i.e., simple mode, medium mode and complex mode, to speed up the encoding process by reducing the number of the variable block modes required to be checked. Furthermore, for simple and medium mode region, the rate distortion(RD) cost of mode 16×16 in the temporal prediction direction is compared with that of the disparity prediction direction, to determine in advance whether the optimal prediction direction is in the temporal prediction direction or not, for skipping unnecessary disparity estimation. Experimental results show that the proposed method is able to significantly reduce the computational load by 78.79% and the total bit rate by 0.07% on average, while only incurring a negligible loss of PSNR(about 0.04 d B on average), compared with the full mode decision(FMD) in the reference software of MVC.
基金supported by the National Natural Science Foundation of China(No.21476119)
文摘The title complex is widely used as an efficient key component of Ziegler-Natta catalyst for stereospecific polymerization of dienes to produce synthetic rubbers. However, the quantitative structure-activity relationship（QSAR） of this kind of complexes is still not clear mainly due to the difficulties to obtain their geometric molecular structures through laboratory experiments. An alternative solution is the quantum chemistry calculation in which the comformational population shall be determined. In this study, ten conformers of the title complex were obtained with the function of molecular dynamics conformational search in Gabedit 2.4.8, and their geometry optimization and thermodynamics calculation were made with a Sparkle/PM7 approach in MOPAC 2012. Their Gibbs free energies at 1 atm. and 298.15 K were calculated. Population of the conformers was further calculated out according to the theory of Boltzmann distribution, indicating that one of the ten conformers has a dominant population of 77.13%.
基金supported by the National Natural Science Foundation of China(40805004, 40705039 and 90715031)the "Mini-projecton detailed survey and evaluation of wind energy resources"supported by National Climate Center of Chinese Meteoro-logical Administration (CWERA2010002)
文摘The state-of-art Computational Fluid Dynamics （CFD） codes FLUENT is applied in a fine-scale simulation of the wind field over a complex terrain. Several numerical tests are performed to validate the capability of FLUENT on describing the wind field details over a complex terrain. The results of the numerical tests show that FLUENT can simulate the wind field over extremely complex terrain, which cannot be simulated by mesoscale models. The reason why FLUENT can cope with extremely complex terrain, which can not be coped with by mesoscale models, relies on some particular techniques adopted by FLUENT, such as computer-aided design （CAD） technique, unstructured grid technique and finite volume method. Compared with mesoscale models, FLUENT can describe terrain in much more accurate details and can provide wind simulation results with higher resolution and more accuracy.
基金supported in part by the National Natural Science Foundation of China(No.62071476)in part by China Postdoctoral Science Foundation(No.2022M723879)in part by the Science and Technology Innovation Program of Hunan Province,China(No.2021RC3080)。
文摘In this advanced exploration, we focus on multiple parameters estimation in bistatic Multiple-Input Multiple-Output(MIMO) radar systems, a crucial technique for target localization and imaging. Our research innovatively addresses the joint estimation of the Direction of Departure(DOD), Direction of Arrival(DOA), and Doppler frequency for incoherent targets. We propose a novel approach that significantly reduces computational complexity by utilizing the TemporalSpatial Nested Sampling Model(TSNSM). Our methodology begins with a multi-linear mapping mechanism to efficiently eliminate unnecessary virtual Degrees of Freedom(DOFs) and reorganize the remaining ones. We then employ the Toeplitz matrix triple iteration reconstruction method, surpassing the traditional Temporal-Spatial Smoothing Window(TSSW) approach, to mitigate the single snapshot effect and reduce computational demands. We further refine the highdimensional ESPRIT algorithm for joint estimation of DOD, DOA, and Doppler frequency, eliminating the need for additional parameter pairing. Moreover, we meticulously derive the Cramér-Rao Bound(CRB) for the TSNSM. This signal model allows for a second expansion of DOFs in time and space domains, achieving high precision in target angle and Doppler frequency estimation with low computational complexity. Our adaptable algorithm is validated through simulations and is suitable for sparse array MIMO radars with various structures, ensuring higher precision in parameter estimation with less complexity burden.
基金supported by the Deanship of Graduate Studies and Scientific Research at Qassim University(QU-APC-2024-9/1).
文摘Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.
基金supported in part by the National Science Fund for Distinguished Young Scholars of China(62225303)the National Natural Science Fundation of China(62303039,62433004)+2 种基金the China Postdoctoral Science Foundation(BX20230034,2023M730190)the Fundamental Research Funds for the Central Universities(buctrc202201,QNTD2023-01)the High Performance Computing Platform,College of Information Science and Technology,Beijing University of Chemical Technology
文摘Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems,such as thermal power plants being studied in this work.Industrial processes are inherently dynamic and need to be monitored using dynamic algorithms.Mainstream dynamic algorithms rely on concatenating current measurement with past data.This work proposes a new,alternative dynamic process monitoring algorithm,using dot product feature analysis(DPFA).DPFA computes the dot product of consecutive samples,thus naturally capturing the process dynamics through temporal correlation.At the same time,DPFA's online computational complexity is lower than not just existing dynamic algorithms,but also classical static algorithms(e.g.,principal component analysis and slow feature analysis).The detectability of the new algorithm is analyzed for three types of faults typically seen in process systems:sensor bias,process fault and gain change fault.Through experiments with a numerical example and real data from a thermal power plant,the DPFA algorithm is shown to be superior to the state-of-the-art methods,in terms of better monitoring performance(fault detection rate and false alarm rate)and lower computational complexity.
基金supported in part by Major Program of the National Natural Science Foundation of China under Grant 62127803.
文摘Safety maintenance of power equipment is of great importance in power grids,in which image-processing-based defect recognition is supposed to classify abnormal conditions during daily inspection.However,owing to the blurred features of defect images,the current defect recognition algorithm has poor fine-grained recognition ability.Visual attention can achieve fine-grained recognition with its abil-ity to model long-range dependencies while introducing extra computational complexity,especially for multi-head attention in vision transformer structures.Under these circumstances,this paper proposes a self-reduction multi-head attention module that can reduce computational complexity and be easily combined with a Convolutional Neural Network(CNN).In this manner,local and global fea-tures can be calculated simultaneously in our proposed structure,aiming to improve the defect recognition performance.Specifically,the proposed self-reduction multi-head attention can reduce redundant parameters,thereby solving the problem of limited computational resources.Experimental results were obtained based on the defect dataset collected from the substation.The results demonstrated the efficiency and superiority of the proposed method over other advanced algorithms.
文摘A central problem in the study of complexity is the measure of nonuniform complexity classes. BPPP/poly has been proved by Aldman, and EXPSPACEP/poly by Kannan. We propose the definition of approximate acceptance with which we discuss the nonuniform complexity of the K sized complete subgraph problem. The method of modal theory is used and the K sized complete subgraph problemP/poly, co NPP/poly and NPP/poly is proved. This paper solves the Karp Lipton′s open problem: “NPP/poly?”
基金supported by the National Natural Science Foundation of China(91648204 61601486)+1 种基金State Key Laboratory of High Performance Computing Project Fund(1502-02)Research Programs of National University of Defense Technology(ZDYYJCYJ140601)
文摘Unmanned aerial vehicles(UAVs) may play an important role in data collection and offloading in vast areas deploying wireless sensor networks, and the UAV’s action strategy has a vital influence on achieving applicability and computational complexity. Dynamic programming(DP) has a good application in the path planning of UAV, but there are problems in the applicability of special terrain environment and the complexity of the algorithm.Based on the analysis of DP, this paper proposes a hierarchical directional DP(DDP) algorithm based on direction determination and hierarchical model. We compare our methods with Q-learning and DP algorithm by experiments, and the results show that our method can improve the terrain applicability, meanwhile greatly reduce the computational complexity.
基金supported by the National Natural Science Foundation of China (Nos. 61233005 and 61503013)the National Basic Research Program of China (No. 2014CB744202)+2 种基金Beijing Youth Talent ProgramFundamental Science on Novel Inertial Instrument & Navigation System Technology LaboratoryProgram for Changjiang Scholars and Innovative Research Team in University (IRT1203) for their valuable comments
文摘Inertial navigation system/visual navigation system(INS/VNS) integrated navigation is a commonly used autonomous navigation method for planetary rovers. Since visual measurements are related to the previous and current state vectors(position and attitude) of planetary rovers, the performance of the Kalman filter(KF) will be challenged by the time-correlation problem. A state augmentation method, which augments the previous state value to the state vector, is commonly used when dealing with this problem. However, the augmenting of state dimensions will result in an increase in computation load. In this paper, a state dimension reduced INS/VNS integrated navigation method based on coordinates of feature points is presented that utilizes the information obtained through INS/VNS integrated navigation at a previous moment to overcome the time relevance problem and reduce the dimensions of the state vector. Equations of extended Kalman filter(EKF) are used to demonstrate the equivalence of calculated results between the proposed method and traditional state augmented methods. Results of simulation and experimentation indicate that this method has less computational load but similar accuracy when compared with traditional methods.
基金supported by the National Natural Science Foundation of China (60502046, 60573034)863 Foundation of China (2007AA01Z215)
文摘Recently, network coding has been applied to the loss recovery of reliable broadcast transmission in wireless networks. Since it was proved that fi nding the optimal set of lost packets for XOR-ing is a complex NP-complete problem, the available time-based retransmission scheme and its enhanced retransmission scheme have exponential computational complexity and thus are not scalable to large networks. In this paper, we present an efficient heuristic scheme based on hypergraph coloring and also its enhanced heuristic scheme to improve the transmission efficiency. Basically, our proposed schemes fi rst create a hypergraph according to the packet-loss matrix. Then our schemes solve the problem of generating XORed packets by coloring the edges of hypergraph. Extensive simulation results demonstrate that, the heuristic scheme based on hypergraph coloring and its enhanced scheme can achieve almost the same transmission efficiency as the available ones, but have much lower computational complexity, which is very important for the wireless devices without high computation capacity.
基金supported by the National Natural Science Foundation of China (60972152)the National Laboratory Foundation of China (9140C2304080607)+1 种基金the Aviation Science Fund (2009ZC53031)the Doctoral Foundation of Northwestern Polytechnical University (CX201002)
文摘The maximum likelihood （ML） estimator demonstrates remarkable performance in direction of arrival （DOA） estimation for the multiple input multiple output （MIMO） sonar. However, this advantage comes with prohibitive computational complexity. In order to solve this problem, an ant colony optimization （ACO） is incorporated into the MIMO ML DOA estimator. Based on the ACO, a novel MIMO ML DOA estimator named the MIMO ACO ML （ML DOA estimator based on ACO for MIMO sonar） with even lower computational complexity is proposed. By extending the pheromone remaining process to the pheromone Gaussian kernel probability distribution function in the continuous space, the pro- posed algorithm achieves the global optimum value of the MIMO ML DOA estimator. Simulations and experimental results show that the computational cost of MIMO ACO ML is only 1/6 of the MIMO ML algorithm, while maintaining similar performance with the MIMO ML method.
文摘In order to reduce the computational complexity of the high efficiency video coding(HEVC) standard, a new algorithm for HEVC intra prediction, namely, fast prediction unit(PU) size selection method for HEVC based on salient regions is proposed in this paper. We first build a saliency map for each largest coding unit(LCU) to reduce its texture complexity. Secondly, the optimal PU size is determined via a scheme that implements an information entropy comparison among sub-blocks of saliency maps. Finally, we apply the partitioning result of saliency map on the original LCUs, obtaining the optimal partitioning result. Our algorithm can determine the PU size in advance to the angular prediction in intra coding, reducing computational complexity of HEVC. The experimental results show that our algorithm achieves a 37.9% reduction in encoding time, while producing a negligible loss in Bjontegaard delta bit rate(BDBR) of 0.62%.
文摘In this paper,a two-stage semi-hybrid flowshop problem which appears in graphics processing is studied. For this problem, there are two machines M1 and M2, and a set of independent jobs J= {J1 ,J2 ,…,Jn }. Each Ji consists of two tasks Ai and Bi ,and task Ai must be completed before task Bi can start. Furthermore ,task Ai can be processed on M1 for ai time units ,or on Mw for ai^J time units ,while task Bi can only be processed on M2 for bi time units. Jobs and machines are available at time zero and no preemption is allowed. The objective is to minimize the maximum job completion time. It is showed that this problem is NP-hard. And a pseudo-polynomial time optimal algorithm is presented. A polynomial time approximation algorithm with worst-case ratio 2 is also presented.
