Advancements in artificial intelligence and big data technologies have led to the gradual emergence of intelligent ships,which are expected to dominate the future of maritime transportation.Supporting the navigation o...Advancements in artificial intelligence and big data technologies have led to the gradual emergence of intelligent ships,which are expected to dominate the future of maritime transportation.Supporting the navigation of intelligent ships,route planning technologies have developed many route planning algorithms that prioritize economy and safety.This paper conducts an in-depth study of algorithm efficiency for a route planning problem,proposing an intelligent ship route planning algorithm based on the adaptive step size Informed-RRT^(*).This algorithm can quickly plan a short route according to automatic obstacle avoidance and is suitable for planning the routes of intelligent ships.Results show that the adaptive step size Informed-RRT^(*) algorithm can shorten the optimal route length by approximately 13.05%while ensuring the running time of the planning algorithm and avoiding approximately 23.64%of redundant sampling nodes.The improved algorithm effectively circumvents unnecessary calculations and reduces a large amount of redundant sampling data,thus improving the efficiency of route planning.In a complex water environment,the unique adaptive step size mechanism enables this algorithm to prevent restricted search tree expansion,showing strong search ability and robustness,which is of practical significance for the development of intelligent ships.展开更多
Filter bank multicarrier quadrature amplitude modulation(FBMC-QAM)will encounter inter-ference and noise during the process of channel transmission.In order to suppress the interference in the communication system,cha...Filter bank multicarrier quadrature amplitude modulation(FBMC-QAM)will encounter inter-ference and noise during the process of channel transmission.In order to suppress the interference in the communication system,channel equalization is carried out at the receiver.Given that the con-ventional least mean square(LMS)equilibrium algorithm usually suffer from drawbacks such as the inability to converge quickly in large step sizes and poor stability in small step sizes when searching for optimal weights,in this paper,a design scheme for adaptive equalization with dynamic step size LMS optimization is proposed,which can further improve the convergence and error stability of the algorithm by calling the Sigmoid function and introducing three new parameters to control the range of step size values,adjust the steepness of step size,and reduce steady-state errors in small step sta-ges.Theoretical analysis and simulation results demonstrate that compared with the conventional LMS algorithm and the neural network-based residual deep neural network(Res-DNN)algorithm,the adopted dynamic step size LMS optimization scheme can not only obtain faster convergence speed,but also get smaller error values in the signal recovery process,thereby achieving better bit error rate(BER)performance.展开更多
A growing interest has been devoted to the contra-rotating propellers （CRPs） due to their high propulsive efficiency, torque balance, low fuel consumption, low cavitations, low noise performance and low hull vibrati...A growing interest has been devoted to the contra-rotating propellers （CRPs） due to their high propulsive efficiency, torque balance, low fuel consumption, low cavitations, low noise performance and low hull vibration. Compared with the single-screw system, it is more difficult for the open water performance prediction because forward and aft propellers interact with each other and generate a more complicated flow field around the CRPs system. The current work focuses on the open water performance prediction of contra-rotating propellers by RANS and sliding mesh method considering the effect of computational time step size and turbulence model. The validation study has been performed on two sets of contra-rotating propellers developed by David W Taylor Naval Ship R ＆ D center. Compared with the experimental data, it shows that RANS with sliding mesh method and SST k-ω turbulence model has a good precision in the open water performance prediction of contra-rotating propellers, and small time step size can improve the level of accuracy for CRPs with the same blade number of forward and aft propellers, while a relatively large time step size is a better choice for CRPs with different blade numbers.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
In four—dimensional variational data assimilation (4DVAR) technology, how to calculate the optimal step size is always a very important and indeed difficult task. It is directly related to the computational efficienc...In four—dimensional variational data assimilation (4DVAR) technology, how to calculate the optimal step size is always a very important and indeed difficult task. It is directly related to the computational efficiency. In this research, a new method is proposed to calculate the optimal step size more effectively. Both nonlinear one—dimensional advection equation and two—dimensional inertial wave equation are used to test and compare the influence of different methods of the optimal step size calculations on the iteration steps, as well as the simulation results of 4DVAR processes. It is in evidence that the different methods have different influences. The calculating method is very important to determining whether the iteration is convergent or not and whether the convergence rate is large or small. If the calculating method of optimal step size is properly determined as demonstrated in this paper, then it can greatly enlarge the convergence rate and further greatly decrease the iteration steps. This research is meaningful since it not only makes an important improvement on 4DVAR theory, but also has useful practical application in improving the computational efficiency and saving the computational time. Key words 4DVAR - Optimal step size - Iterative convergence rate This work was supported by the National Natural Science Foundation under grants: 49735180 and 49675259, the “973 Project? CHERES(G 1998040907), the Project of Natural Science Foundation of Jiangsu Province(BK99020), and the Project Sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars.展开更多
The computational uncertainty principle states that the numerical computation of nonlinear ordinary differential equations（ODEs） should use appropriately sized time steps to obtain reliable solutions.However,the int...The computational uncertainty principle states that the numerical computation of nonlinear ordinary differential equations（ODEs） should use appropriately sized time steps to obtain reliable solutions.However,the interval of effective step size（IES） has not been thoroughly explored theoretically.In this paper,by using a general estimation for the total error of the numerical solutions of ODEs,a method is proposed for determining an approximate IES by translating the functions for truncation and rounding errors.It also illustrates this process with an example.Moreover,the relationship between the IES and its approximation is found,and the relative error of the approximation with respect to the IES is given.In addition,variation in the IES with increasing integration time is studied,which can provide an explanation for the observed numerical results.The findings contribute to computational step-size choice for reliable numerical solutions.展开更多
A newly proposed competent population-based optimization algorithm called RUN,which uses the principle of slope variations calculated by applying the Runge Kutta method as the key search mechanism,has gained wider int...A newly proposed competent population-based optimization algorithm called RUN,which uses the principle of slope variations calculated by applying the Runge Kutta method as the key search mechanism,has gained wider interest in solving optimization problems.However,in high-dimensional problems,the search capabilities,convergence speed,and runtime of RUN deteriorate.This work aims at filling this gap by proposing an improved variant of the RUN algorithm called the Adaptive-RUN.Population size plays a vital role in both runtime efficiency and optimization effectiveness of metaheuristic algorithms.Unlike the original RUN where population size is fixed throughout the search process,Adaptive-RUN automatically adjusts population size according to two population size adaptation techniques,which are linear staircase reduction and iterative halving,during the search process to achieve a good balance between exploration and exploitation characteristics.In addition,the proposed methodology employs an adaptive search step size technique to determine a better solution in the early stages of evolution to improve the solution quality,fitness,and convergence speed of the original RUN.Adaptive-RUN performance is analyzed over 23 IEEE CEC-2017 benchmark functions for two cases,where the first one applies linear staircase reduction with adaptive search step size(LSRUN),and the second one applies iterative halving with adaptive search step size(HRUN),with the original RUN.To promote green computing,the carbon footprint metric is included in the performance evaluation in addition to runtime and fitness.Simulation results based on the Friedman andWilcoxon tests revealed that Adaptive-RUN can produce high-quality solutions with lower runtime and carbon footprint values as compared to the original RUN and three recent metaheuristics.Therefore,with its higher computation efficiency,Adaptive-RUN is a much more favorable choice as compared to RUN in time stringent applications.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
We develop error-control based time integration algorithms for compressible fluid dynam-ics(CFD)applications and show that they are efficient and robust in both the accuracy-limited and stability-limited regime.Focusi...We develop error-control based time integration algorithms for compressible fluid dynam-ics(CFD)applications and show that they are efficient and robust in both the accuracy-limited and stability-limited regime.Focusing on discontinuous spectral element semidis-cretizations,we design new controllers for existing methods and for some new embedded Runge-Kutta pairs.We demonstrate the importance of choosing adequate controller parameters and provide a means to obtain these in practice.We compare a wide range of error-control-based methods,along with the common approach in which step size con-trol is based on the Courant-Friedrichs-Lewy(CFL)number.The optimized methods give improved performance and naturally adopt a step size close to the maximum stable CFL number at loose tolerances,while additionally providing control of the temporal error at tighter tolerances.The numerical examples include challenging industrial CFD applications.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
Nano-volt magnetic resonance sounding(MRS) signals are sufficiently weak so that during the actual measurement, they are affected by environmental electromagnetic noise, leading to inaccuracy of the extracted characte...Nano-volt magnetic resonance sounding(MRS) signals are sufficiently weak so that during the actual measurement, they are affected by environmental electromagnetic noise, leading to inaccuracy of the extracted characteristic parameters and hindering effective inverse interpretation. Considering the complexity and non-homogeneous spatial distribution of environmental noise and based on the theory of adaptive noise cancellation, a model system for noise cancellation using multi-reference coils was constructed to receive MRS signals. The feasibility of this system with theoretical calculation and experiments was analyzed and a modified sigmoid variable step size least mean square(SVSLMS) algorithm for noise cancellation was presented. The simulation results show that, the multi-reference coil method performs better than the single one on both signal-to-noise ratio(SNR) improvement and signal waveform optimization after filtering, under the condition of different noise correlations in the reference coils and primary detecting coils and different SNRs. In particular, when the noise correlation is poor and the SNR<0, the SNR can be improved by more than 8 dB after filtering with multi-reference coils. And the average fitting errors for initial amplitude and relaxation time are within 5%. Compared with the normalized least mean square(NLMS) algorithm and multichannel Wiener filter and processing field test data, the effectiveness of the proposed method is verified.展开更多
According to the exact expression of the maladjustment, an equation for calculating the boundary of step-size in MLMS algorithm is derived and the relationship between the convergence rate and step-size is discussed i...According to the exact expression of the maladjustment, an equation for calculating the boundary of step-size in MLMS algorithm is derived and the relationship between the convergence rate and step-size is discussed in detail. It is shown that the threshold of the step-size is constrained by maladjustment. Three different properties are presented between the LMS and MLMS algorithms based on comparison. It is indicated that MLMS does not differ significantly from LMS when the given maladjustment is small.展开更多
In this paper, we propose a novel warm restart technique using a new logarithmic step size for the stochastic gradient descent (SGD) approach. For smooth and non-convex functions, we establish an O(1/√T) convergence ...In this paper, we propose a novel warm restart technique using a new logarithmic step size for the stochastic gradient descent (SGD) approach. For smooth and non-convex functions, we establish an O(1/√T) convergence rate for the SGD. We conduct a comprehensive implementation to demonstrate the efficiency of the newly proposed step size on the FashionMinst, CIFAR10, and CIFAR100 datasets. Moreover, we compare our results with nine other existing approaches and demonstrate that the new logarithmic step size improves test accuracy by 0.9% for the CIFAR100 dataset when we utilize a convolutional neural network (CNN) model.展开更多
We study a temporal step size control of explicit Runge-Kutta(RK)methods for com-pressible computational fuid dynamics(CFD),including the Navier-Stokes equations and hyperbolic systems of conservation laws such as the...We study a temporal step size control of explicit Runge-Kutta(RK)methods for com-pressible computational fuid dynamics(CFD),including the Navier-Stokes equations and hyperbolic systems of conservation laws such as the Euler equations.We demonstrate that error-based approaches are convenient in a wide range of applications and compare them to more classical step size control based on a Courant-Friedrichs-Lewy(CFL)number.Our numerical examples show that the error-based step size control is easy to use,robust,and efcient,e.g.,for(initial)transient periods,complex geometries,nonlinear shock captur-ing approaches,and schemes that use nonlinear entropy projections.We demonstrate these properties for problems ranging from well-understood academic test cases to industrially relevant large-scale computations with two disjoint code bases,the open source Julia pack-ages Trixi.jl with OrdinaryDiffEq.jl and the C/Fortran code SSDC based on PETSc.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
In this paper,we develop an active set identification technique.By means of the active set technique,we present an active set adaptive monotone projected Barzilai-Borwein method(ASAMPBB)for solving nonnegative matrix ...In this paper,we develop an active set identification technique.By means of the active set technique,we present an active set adaptive monotone projected Barzilai-Borwein method(ASAMPBB)for solving nonnegative matrix factorization(NMF)based on the alternating nonnegative least squares framework,in which the Barzilai-Borwein(BB)step sizes can be adaptively picked to get meaningful convergence rate improvements.To get optimal step size,we take into account of the curvature information.In addition,the larger step size technique is exploited to accelerate convergence of the proposed method.The global convergence of the proposed method is analysed under mild assumption.Finally,the results of the numerical experiments on both synthetic and real-world datasets show that the proposed method is effective.展开更多
Symmetric alternating directionmethod of multipliers(ADMM)is an efficient method for solving a class of separable convex optimization problems.This method updates the Lagrange multiplier twice with appropriate step si...Symmetric alternating directionmethod of multipliers(ADMM)is an efficient method for solving a class of separable convex optimization problems.This method updates the Lagrange multiplier twice with appropriate step sizes at each iteration.However,such step sizes were conservatively shrunk to guarantee the convergence in recent studies.In this paper,we are devoted to seeking larger step sizes whenever possible.The logarithmic-quadratic proximal(LQP)terms are applied to regularize the symmetric ADMM subproblems,allowing the constrained subproblems to then be converted to easier unconstrained ones.Theoretically,we prove the global convergence of such LQP-based symmetric ADMM by specifying a larger step size domain.Moreover,the numerical results on a traffic equilibrium problem are reported to demonstrate the advantage of the method with larger step sizes.展开更多
We present a new least-mean-square algorithm of adaptive filtering to improve the signal to noise ratio for magneto-cardiography data collected with high-temperature SQUID-based magnetometers. By frequently adjusting ...We present a new least-mean-square algorithm of adaptive filtering to improve the signal to noise ratio for magneto-cardiography data collected with high-temperature SQUID-based magnetometers. By frequently adjusting the adaptive parameter a go systematic optimum values in the course of the programmed procedure, the convergence is accelerated with a highest speed and the minimum steady-state error is obtained simultaneously. This algorithm may be applied to eliminate other non-steady relevant noises as well.展开更多
In this paper a model of transversal filter is presented to study the adaptive match of the time variant channel. The least mean square error filtering method is used to obtain the weighting coefficients of the filter...In this paper a model of transversal filter is presented to study the adaptive match of the time variant channel. The least mean square error filtering method is used to obtain the weighting coefficients of the filter. With the purpose of speeding up the convergence of the iteration equation of adaptive filtering, an adaptive factor of the iteration step size μa is derived in this paper. The result of computer simulation shows that in the case of using adaptive μa, the convergence speed of the iteration equation is increased 2 times approximately in comparison with constant μ1. The study suggests that the adaptive filter with adaptive μa have the performance to follow the change of time-variant characteristics of the channel.展开更多
文摘Advancements in artificial intelligence and big data technologies have led to the gradual emergence of intelligent ships,which are expected to dominate the future of maritime transportation.Supporting the navigation of intelligent ships,route planning technologies have developed many route planning algorithms that prioritize economy and safety.This paper conducts an in-depth study of algorithm efficiency for a route planning problem,proposing an intelligent ship route planning algorithm based on the adaptive step size Informed-RRT^(*).This algorithm can quickly plan a short route according to automatic obstacle avoidance and is suitable for planning the routes of intelligent ships.Results show that the adaptive step size Informed-RRT^(*) algorithm can shorten the optimal route length by approximately 13.05%while ensuring the running time of the planning algorithm and avoiding approximately 23.64%of redundant sampling nodes.The improved algorithm effectively circumvents unnecessary calculations and reduces a large amount of redundant sampling data,thus improving the efficiency of route planning.In a complex water environment,the unique adaptive step size mechanism enables this algorithm to prevent restricted search tree expansion,showing strong search ability and robustness,which is of practical significance for the development of intelligent ships.
基金the National Natural Science Foundation of China(No.61601296,61701295)the Science and Technology Innovation Action Plan Project of Shanghai Science and Technology Commission(No.20511103500)the Talent Program of Shanghai University of Engineering Science(No.2018RC43).
文摘Filter bank multicarrier quadrature amplitude modulation(FBMC-QAM)will encounter inter-ference and noise during the process of channel transmission.In order to suppress the interference in the communication system,channel equalization is carried out at the receiver.Given that the con-ventional least mean square(LMS)equilibrium algorithm usually suffer from drawbacks such as the inability to converge quickly in large step sizes and poor stability in small step sizes when searching for optimal weights,in this paper,a design scheme for adaptive equalization with dynamic step size LMS optimization is proposed,which can further improve the convergence and error stability of the algorithm by calling the Sigmoid function and introducing three new parameters to control the range of step size values,adjust the steepness of step size,and reduce steady-state errors in small step sta-ges.Theoretical analysis and simulation results demonstrate that compared with the conventional LMS algorithm and the neural network-based residual deep neural network(Res-DNN)algorithm,the adopted dynamic step size LMS optimization scheme can not only obtain faster convergence speed,but also get smaller error values in the signal recovery process,thereby achieving better bit error rate(BER)performance.
基金supported by the National Natural Science Foundation of China(Grant No.51079157)
文摘A growing interest has been devoted to the contra-rotating propellers （CRPs） due to their high propulsive efficiency, torque balance, low fuel consumption, low cavitations, low noise performance and low hull vibration. Compared with the single-screw system, it is more difficult for the open water performance prediction because forward and aft propellers interact with each other and generate a more complicated flow field around the CRPs system. The current work focuses on the open water performance prediction of contra-rotating propellers by RANS and sliding mesh method considering the effect of computational time step size and turbulence model. The validation study has been performed on two sets of contra-rotating propellers developed by David W Taylor Naval Ship R ＆ D center. Compared with the experimental data, it shows that RANS with sliding mesh method and SST k-ω turbulence model has a good precision in the open water performance prediction of contra-rotating propellers, and small time step size can improve the level of accuracy for CRPs with the same blade number of forward and aft propellers, while a relatively large time step size is a better choice for CRPs with different blade numbers.
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.
文摘In four—dimensional variational data assimilation (4DVAR) technology, how to calculate the optimal step size is always a very important and indeed difficult task. It is directly related to the computational efficiency. In this research, a new method is proposed to calculate the optimal step size more effectively. Both nonlinear one—dimensional advection equation and two—dimensional inertial wave equation are used to test and compare the influence of different methods of the optimal step size calculations on the iteration steps, as well as the simulation results of 4DVAR processes. It is in evidence that the different methods have different influences. The calculating method is very important to determining whether the iteration is convergent or not and whether the convergence rate is large or small. If the calculating method of optimal step size is properly determined as demonstrated in this paper, then it can greatly enlarge the convergence rate and further greatly decrease the iteration steps. This research is meaningful since it not only makes an important improvement on 4DVAR theory, but also has useful practical application in improving the computational efficiency and saving the computational time. Key words 4DVAR - Optimal step size - Iterative convergence rate This work was supported by the National Natural Science Foundation under grants: 49735180 and 49675259, the “973 Project? CHERES(G 1998040907), the Project of Natural Science Foundation of Jiangsu Province(BK99020), and the Project Sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars.
基金supported by the National Natural Science Foundation of China[grant numbers 41375110,11471244]
文摘The computational uncertainty principle states that the numerical computation of nonlinear ordinary differential equations（ODEs） should use appropriately sized time steps to obtain reliable solutions.However,the interval of effective step size（IES） has not been thoroughly explored theoretically.In this paper,by using a general estimation for the total error of the numerical solutions of ODEs,a method is proposed for determining an approximate IES by translating the functions for truncation and rounding errors.It also illustrates this process with an example.Moreover,the relationship between the IES and its approximation is found,and the relative error of the approximation with respect to the IES is given.In addition,variation in the IES with increasing integration time is studied,which can provide an explanation for the observed numerical results.The findings contribute to computational step-size choice for reliable numerical solutions.
文摘A newly proposed competent population-based optimization algorithm called RUN,which uses the principle of slope variations calculated by applying the Runge Kutta method as the key search mechanism,has gained wider interest in solving optimization problems.However,in high-dimensional problems,the search capabilities,convergence speed,and runtime of RUN deteriorate.This work aims at filling this gap by proposing an improved variant of the RUN algorithm called the Adaptive-RUN.Population size plays a vital role in both runtime efficiency and optimization effectiveness of metaheuristic algorithms.Unlike the original RUN where population size is fixed throughout the search process,Adaptive-RUN automatically adjusts population size according to two population size adaptation techniques,which are linear staircase reduction and iterative halving,during the search process to achieve a good balance between exploration and exploitation characteristics.In addition,the proposed methodology employs an adaptive search step size technique to determine a better solution in the early stages of evolution to improve the solution quality,fitness,and convergence speed of the original RUN.Adaptive-RUN performance is analyzed over 23 IEEE CEC-2017 benchmark functions for two cases,where the first one applies linear staircase reduction with adaptive search step size(LSRUN),and the second one applies iterative halving with adaptive search step size(HRUN),with the original RUN.To promote green computing,the carbon footprint metric is included in the performance evaluation in addition to runtime and fitness.Simulation results based on the Friedman andWilcoxon tests revealed that Adaptive-RUN can produce high-quality solutions with lower runtime and carbon footprint values as compared to the original RUN and three recent metaheuristics.Therefore,with its higher computation efficiency,Adaptive-RUN is a much more favorable choice as compared to RUN in time stringent applications.
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Open Access funding enabled and organized by Projekt DEAL.
文摘We develop error-control based time integration algorithms for compressible fluid dynam-ics(CFD)applications and show that they are efficient and robust in both the accuracy-limited and stability-limited regime.Focusing on discontinuous spectral element semidis-cretizations,we design new controllers for existing methods and for some new embedded Runge-Kutta pairs.We demonstrate the importance of choosing adequate controller parameters and provide a means to obtain these in practice.We compare a wide range of error-control-based methods,along with the common approach in which step size con-trol is based on the Courant-Friedrichs-Lewy(CFL)number.The optimized methods give improved performance and naturally adopt a step size close to the maximum stable CFL number at loose tolerances,while additionally providing control of the temporal error at tighter tolerances.The numerical examples include challenging industrial CFD applications.
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.
基金Projects(41204079,41504086)supported by the National Natural Science Foundation of ChinaProject(20160101281JC)supported by the Natural Science Foundation of Jilin Province,ChinaProjects(2016M590258,2015T80301)supported by the Postdoctoral Science Foundation of China
文摘Nano-volt magnetic resonance sounding(MRS) signals are sufficiently weak so that during the actual measurement, they are affected by environmental electromagnetic noise, leading to inaccuracy of the extracted characteristic parameters and hindering effective inverse interpretation. Considering the complexity and non-homogeneous spatial distribution of environmental noise and based on the theory of adaptive noise cancellation, a model system for noise cancellation using multi-reference coils was constructed to receive MRS signals. The feasibility of this system with theoretical calculation and experiments was analyzed and a modified sigmoid variable step size least mean square(SVSLMS) algorithm for noise cancellation was presented. The simulation results show that, the multi-reference coil method performs better than the single one on both signal-to-noise ratio(SNR) improvement and signal waveform optimization after filtering, under the condition of different noise correlations in the reference coils and primary detecting coils and different SNRs. In particular, when the noise correlation is poor and the SNR<0, the SNR can be improved by more than 8 dB after filtering with multi-reference coils. And the average fitting errors for initial amplitude and relaxation time are within 5%. Compared with the normalized least mean square(NLMS) algorithm and multichannel Wiener filter and processing field test data, the effectiveness of the proposed method is verified.
文摘According to the exact expression of the maladjustment, an equation for calculating the boundary of step-size in MLMS algorithm is derived and the relationship between the convergence rate and step-size is discussed in detail. It is shown that the threshold of the step-size is constrained by maladjustment. Three different properties are presented between the LMS and MLMS algorithms based on comparison. It is indicated that MLMS does not differ significantly from LMS when the given maladjustment is small.
基金first author is partially supported by the University of Kashan(1143902/2).
文摘In this paper, we propose a novel warm restart technique using a new logarithmic step size for the stochastic gradient descent (SGD) approach. For smooth and non-convex functions, we establish an O(1/√T) convergence rate for the SGD. We conduct a comprehensive implementation to demonstrate the efficiency of the newly proposed step size on the FashionMinst, CIFAR10, and CIFAR100 datasets. Moreover, we compare our results with nine other existing approaches and demonstrate that the new logarithmic step size improves test accuracy by 0.9% for the CIFAR100 dataset when we utilize a convolutional neural network (CNN) model.
基金Open Access funding enabled and organized by Projekt DEAL.Andrew Winters was funded through Vetenskapsrådet,Sweden Grant Agreement 2020-03642 VR.Some computations were enabled by resources provided by the Swedish National Infrastructure for Computing(SNIC)at Tetralith,par-tially funded by the Swedish Research Council under Grant Agreement No.2018-05973Hugo Guillermo Castro was funded through the award P2021-0004 of King Abdullah University of Science and Technol-ogy.Some of the simulations were enabled by the Supercomputing Laboratory and the Extreme Comput-ing Research Center at King Abdullah University of Science and Technology.Gregor Gassner acknowl-edges funding through the Klaus-Tschira Stiftung via the project“HiFiLab”.Gregor Gassner and Michael Schlottke-Lakemper acknowledge funding from the Deutsche Forschungsgemeinschaft through the research unit“SNuBIC”(DFG-FOR5409).
文摘We study a temporal step size control of explicit Runge-Kutta(RK)methods for com-pressible computational fuid dynamics(CFD),including the Navier-Stokes equations and hyperbolic systems of conservation laws such as the Euler equations.We demonstrate that error-based approaches are convenient in a wide range of applications and compare them to more classical step size control based on a Courant-Friedrichs-Lewy(CFL)number.Our numerical examples show that the error-based step size control is easy to use,robust,and efcient,e.g.,for(initial)transient periods,complex geometries,nonlinear shock captur-ing approaches,and schemes that use nonlinear entropy projections.We demonstrate these properties for problems ranging from well-understood academic test cases to industrially relevant large-scale computations with two disjoint code bases,the open source Julia pack-ages Trixi.jl with OrdinaryDiffEq.jl and the C/Fortran code SSDC based on PETSc.
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the support from the National Natural Science Foundation of China(Nos.12171384,12201492,61976176)the National Science Foundation of Shaanxi(No.2021JM-323).
文摘In this paper,we develop an active set identification technique.By means of the active set technique,we present an active set adaptive monotone projected Barzilai-Borwein method(ASAMPBB)for solving nonnegative matrix factorization(NMF)based on the alternating nonnegative least squares framework,in which the Barzilai-Borwein(BB)step sizes can be adaptively picked to get meaningful convergence rate improvements.To get optimal step size,we take into account of the curvature information.In addition,the larger step size technique is exploited to accelerate convergence of the proposed method.The global convergence of the proposed method is analysed under mild assumption.Finally,the results of the numerical experiments on both synthetic and real-world datasets show that the proposed method is effective.
基金This research was supported by National Natural Science Foundation of China Grant 11771078Natural Science Foundation of Jiangsu Province Grant BK20181258+1 种基金Project of 333 of Jiangsu Province Grant BRA2018351Postgraduate Research&Practice Innovation Program of Jiangsu Province Grant KYCX18_0200.
文摘Symmetric alternating directionmethod of multipliers(ADMM)is an efficient method for solving a class of separable convex optimization problems.This method updates the Lagrange multiplier twice with appropriate step sizes at each iteration.However,such step sizes were conservatively shrunk to guarantee the convergence in recent studies.In this paper,we are devoted to seeking larger step sizes whenever possible.The logarithmic-quadratic proximal(LQP)terms are applied to regularize the symmetric ADMM subproblems,allowing the constrained subproblems to then be converted to easier unconstrained ones.Theoretically,we prove the global convergence of such LQP-based symmetric ADMM by specifying a larger step size domain.Moreover,the numerical results on a traffic equilibrium problem are reported to demonstrate the advantage of the method with larger step sizes.
文摘We present a new least-mean-square algorithm of adaptive filtering to improve the signal to noise ratio for magneto-cardiography data collected with high-temperature SQUID-based magnetometers. By frequently adjusting the adaptive parameter a go systematic optimum values in the course of the programmed procedure, the convergence is accelerated with a highest speed and the minimum steady-state error is obtained simultaneously. This algorithm may be applied to eliminate other non-steady relevant noises as well.
文摘In this paper a model of transversal filter is presented to study the adaptive match of the time variant channel. The least mean square error filtering method is used to obtain the weighting coefficients of the filter. With the purpose of speeding up the convergence of the iteration equation of adaptive filtering, an adaptive factor of the iteration step size μa is derived in this paper. The result of computer simulation shows that in the case of using adaptive μa, the convergence speed of the iteration equation is increased 2 times approximately in comparison with constant μ1. The study suggests that the adaptive filter with adaptive μa have the performance to follow the change of time-variant characteristics of the channel.
