The contradiction of variable step size least mean square(LMS)algorithm between fast convergence speed and small steady-state error has always existed.So,a new algorithm based on the combination of logarithmic and sym...The contradiction of variable step size least mean square(LMS)algorithm between fast convergence speed and small steady-state error has always existed.So,a new algorithm based on the combination of logarithmic and symbolic function and step size factor is proposed.It establishes a new updating method of step factor that is related to step factor and error signal.This work makes an analysis from 3 aspects:theoretical analysis,theoretical verification and specific experiments.The experimental results show that the proposed algorithm is superior to other variable step size algorithms in convergence speed and steady-state error.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
This paper puts forward a new variable step size LMS adaptive algorithm based on variable region. The step size p(k) in the algorithm varies with the variation of the region of deviation e (k) to ensure the optimi...This paper puts forward a new variable step size LMS adaptive algorithm based on variable region. The step size p(k) in the algorithm varies with the variation of the region of deviation e (k) to ensure the optimization of the three performance objectives including initial convergent speed, trace ability of the time-varying system and steady disregulation. The paper demonstrates the convergence of the algorithm accompanied by random noise,展开更多
The problem of inter symbol interference( ISI) in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn't require a ...The problem of inter symbol interference( ISI) in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn't require a training sequence,a blind equalization channel is implemented in the receiver to increase the throughput of the system. To improve the performances of both the blind equalizer and the system,a joint receiving mechanismincluding variable step size( VSS) modified constant modulus algorithms( MC-MA) and modified decision directed modulus algorithms( MD DMA) is proposed to ameliorate the convergence speed and mean square error( MSE) performance and combat the phase error when using high order QAM modulation. The VSS scheme is based on the selection of step size according to the distance between the output of the equalizer and the desired output in the constellation plane. Analysis and simulations showthat the performance of the proposed VSS-MCMA-MD DMA mechanismis better than that of algorithms with a fixed step size. In addition,the MCMA-MDDMA with VSS can performthe phase recovery by itself.展开更多
为了解决传统最小均方(Least Mean Square,LMS)算法因固定步长无法同时满足收敛速度快和稳态误差低的矛盾,提出了一种基于反双曲正弦函数的改进变步长LMS算法。该算法利用反双曲正弦函数和误差的自相关量构造了步长因子和误差信号的非...为了解决传统最小均方(Least Mean Square,LMS)算法因固定步长无法同时满足收敛速度快和稳态误差低的矛盾,提出了一种基于反双曲正弦函数的改进变步长LMS算法。该算法利用反双曲正弦函数和误差的自相关量构造了步长因子和误差信号的非线性函数,并从理论和仿真上验证了抗干扰能力以及参数选取对算法性能的影响。仿真结果表明:在系统辨识方面,与现有变步长LMS算法相比,该算法具有更低的稳态误差、更快的收敛速度;在通道校准方面的成功应用也说明了该算法的适用性。展开更多
In order to improve the problem that the filtered-x least mean square(FxLMS)algorithm cannot take into account the convergence speed,steady-state error during active noise control.A piecewise variable step size FxLMS ...In order to improve the problem that the filtered-x least mean square(FxLMS)algorithm cannot take into account the convergence speed,steady-state error during active noise control.A piecewise variable step size FxLMS algorithm based on logarithmic function(PLFxLMS)is proposed,and the genetic algorithm are introduced to optimize the parameters of logarithmic variable step size FxLMS(LFxLMS),improved logarithmic variable step size Films(IFxLMS),and PLFxLMS algorithms.Bandlimited white noise is used as the input signal,FxLMS,LFxLMS,ILFxLMS,and PLFxLMS algorithms are used to conduct active noise control simulation,and the convergence speed and steady-state characteristic of four algorithms are comparatively analyzed.Compared with the other three algorithms,the PLFxLMS algorithm proposed in this paper has the fastest convergence speed,and small steady-state error.The PLFxLMS algorithm can effectively improve the convergence speed and steady-state error of the FxLMS algorithm that cannot be controlled at the same time,and achieve the optimal effect.展开更多
针对传统超声信号时延估计(Time Delay Estimation,TDE)中固定步长最小均方(Least Mean Square,LMS)算法难以兼顾收敛速度与稳态精度,以及现有变步长算法依赖瞬时误差和固定函数模型导致在非平稳回波信号下适应性差的问题,提出一种基于...针对传统超声信号时延估计(Time Delay Estimation,TDE)中固定步长最小均方(Least Mean Square,LMS)算法难以兼顾收敛速度与稳态精度,以及现有变步长算法依赖瞬时误差和固定函数模型导致在非平稳回波信号下适应性差的问题,提出一种基于模糊变步长LMS的超声测厚信号TDE方法。分析超声回波信号的时变特性,摒弃单一误差反馈机制,提取输出信号与期望信号的局部相关系数误差及其变化量作为模糊控制器的双输入特征;设计零阶Sugeno模糊推理系统,建立输入特征与步长因子之间的非线性映射规则,实现步长因子的自适应动态调节。利用模拟回波信号进行不同信噪比下的仿真测试,结果表明:相较定步长LMS算法、双曲正切函数变步长LMS算法以及基于瞬时误差的模糊变步长LMS算法,所提方法的综合性能更优,在保证快速收敛的同时显著降低了稳态失调误差,具有更高的测量精度和抗噪性能。搭建超声测厚平台进行标准量块测量实验,结果表明:所提方法对不同厚度量块的测量相对误差均小于其他三种LMS算法,最大相对误差为0.710%。模糊变步长LMS时延估计方法为高精度超声飞行时间(Time of Flight,TOF)计算提供了重要技术支撑,有利于促进超声无损检测技术发展,具有一定的工程应用价值。展开更多
为规避最小均方(Least Mean Square,LMS)算法不能同时提高收敛速度和降低稳态误差的固有缺陷,以及已有变步长LMS算法存在收敛速度慢和稳态误差估计精度差的问题,文中提出了一种基于变步长归一化频域块(Normalized Frequency-domain Bloc...为规避最小均方(Least Mean Square,LMS)算法不能同时提高收敛速度和降低稳态误差的固有缺陷,以及已有变步长LMS算法存在收敛速度慢和稳态误差估计精度差的问题,文中提出了一种基于变步长归一化频域块(Normalized Frequency-domain Block,NFB)LMS算法的汽车车内噪声主动控制方法。为了比较,应用传统的LMS算法、基于反正切函数的变步长LMS算法和变步长NFB-LMS算法分别进行实测汽车车内噪声的主动控制。结果表明,与其他两个算法相比,变步长NFB-LMS算法的收敛速度提高了70%以上,稳态误差减小了90%以上。变步长NFB-LMS算法在处理车内噪声信号时具有很高的效率,为进行汽车车内噪声主动控制提供了一种新方法。展开更多
为改善滤波-x最小均方(filtered-x least mean square,FxLMS)算法在噪声主动控制时无法兼顾收敛速度和稳态误差的问题,提出了基于sigmoid-sinh分段函数的FxLMS(SSFxLMS)算法,并引入蚁狮算法对SFxLMS(sigmoid filtered-x least mean squa...为改善滤波-x最小均方(filtered-x least mean square,FxLMS)算法在噪声主动控制时无法兼顾收敛速度和稳态误差的问题,提出了基于sigmoid-sinh分段函数的FxLMS(SSFxLMS)算法,并引入蚁狮算法对SFxLMS(sigmoid filtered-x least mean square)、ShFxLMS(sinh filtered-x least mean square)、SSFxLMS算法的参数进行优化。分别采用高斯白噪声和实测簇绒地毯织机噪声为输入信号,采用FxLMS、SFxLMS、ShFxLMS、SSFxLMS算法进行噪声主动控制仿真,对比分析这4种算法的性能。结果表明:与其他3种算法相比,采用SSFxLMS算法对高斯白噪声和簇绒地毯织机噪声进行控制时,误差信号的平均绝对值更小,平均降噪量与收敛速度也有大幅度提升。由此可知,SSFxLMS算法有效改善了FxLMS算法无法兼顾收敛速度和稳态误差的问题,研究结果为噪声主动控制算法设计提供了一定的参考。展开更多
滤波x最小均方差(filtered-x least mean square,简称Fx-LMS)算法作为振动控制领域常用的自适应控制算法,其固定步长因子不能同时满足收敛速度和稳态误差的双重要求。为了改善Fx-LMS算法实施效果,提出一种基于反余切函数的滤波x变步长...滤波x最小均方差(filtered-x least mean square,简称Fx-LMS)算法作为振动控制领域常用的自适应控制算法,其固定步长因子不能同时满足收敛速度和稳态误差的双重要求。为了改善Fx-LMS算法实施效果,提出一种基于反余切函数的滤波x变步长最小均方差(filtered x variable step size least mean square,简称Fx-VSSLMS)算法。首先,归纳了7种常规VSSLMS算法的步长更新公式,并按照其迭代特点予以性能分析与分类对比;其次,以压电柔性悬臂梁振动主动控制为算法验证目标,采用多体动力学软件Adams和Simulink进行联合仿真,表明所提的Fx-VSSLMS算法在振动控制中的有效性;最后,通过分析对比多种Fx-VSSLMS算法在不同噪声环境下的抑振效果,验证了所提出控制算法对噪声干扰的良好鲁棒性。展开更多
基金the National Natural Science Foundation of China(No.51575328,61503232).
摘要The contradiction of variable step size least mean square(LMS)algorithm between fast convergence speed and small steady-state error has always existed.So,a new algorithm based on the combination of logarithmic and symbolic function and step size factor is proposed.It establishes a new updating method of step factor that is related to step factor and error signal.This work makes an analysis from 3 aspects:theoretical analysis,theoretical verification and specific experiments.The experimental results show that the proposed algorithm is superior to other variable step size algorithms in convergence speed and steady-state error.
基金Natural Science Foundation of Shandong Province of China(No.ZR2012FM011)Shandong University of Science and Technology Research Fund(No.2010KYTD101)
摘要By analyzing algorithms available for variable step size least mean square(LMS)adaptive filter,a new modified LMS adaptive filtering algorithm with variable step size is proposed,along with performance analysis based on different parameters.Compared with the existing algorithms through the simulation,the proposed algorithm has faster convergence speed and smaller steady state error.
基金Supported by Natural Science Foundation of Beijing of China (No.2005AA501140)
摘要This paper puts forward a new variable step size LMS adaptive algorithm based on variable region. The step size p(k) in the algorithm varies with the variation of the region of deviation e (k) to ensure the optimization of the three performance objectives including initial convergent speed, trace ability of the time-varying system and steady disregulation. The paper demonstrates the convergence of the algorithm accompanied by random noise,
基金Supported by the National Natural Science Foundation of China(6100201461101129+1 种基金6122700161072050)
摘要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.
摘要为了解决传统最小均方(Least Mean Square,LMS)算法因固定步长无法同时满足收敛速度快和稳态误差低的矛盾,提出了一种基于反双曲正弦函数的改进变步长LMS算法。该算法利用反双曲正弦函数和误差的自相关量构造了步长因子和误差信号的非线性函数,并从理论和仿真上验证了抗干扰能力以及参数选取对算法性能的影响。仿真结果表明:在系统辨识方面,与现有变步长LMS算法相比,该算法具有更低的稳态误差、更快的收敛速度;在通道校准方面的成功应用也说明了该算法的适用性。
摘要In order to improve the problem that the filtered-x least mean square(FxLMS)algorithm cannot take into account the convergence speed,steady-state error during active noise control.A piecewise variable step size FxLMS algorithm based on logarithmic function(PLFxLMS)is proposed,and the genetic algorithm are introduced to optimize the parameters of logarithmic variable step size FxLMS(LFxLMS),improved logarithmic variable step size Films(IFxLMS),and PLFxLMS algorithms.Bandlimited white noise is used as the input signal,FxLMS,LFxLMS,ILFxLMS,and PLFxLMS algorithms are used to conduct active noise control simulation,and the convergence speed and steady-state characteristic of four algorithms are comparatively analyzed.Compared with the other three algorithms,the PLFxLMS algorithm proposed in this paper has the fastest convergence speed,and small steady-state error.The PLFxLMS algorithm can effectively improve the convergence speed and steady-state error of the FxLMS algorithm that cannot be controlled at the same time,and achieve the optimal effect.
摘要针对传统超声信号时延估计(Time Delay Estimation,TDE)中固定步长最小均方(Least Mean Square,LMS)算法难以兼顾收敛速度与稳态精度,以及现有变步长算法依赖瞬时误差和固定函数模型导致在非平稳回波信号下适应性差的问题,提出一种基于模糊变步长LMS的超声测厚信号TDE方法。分析超声回波信号的时变特性,摒弃单一误差反馈机制,提取输出信号与期望信号的局部相关系数误差及其变化量作为模糊控制器的双输入特征;设计零阶Sugeno模糊推理系统,建立输入特征与步长因子之间的非线性映射规则,实现步长因子的自适应动态调节。利用模拟回波信号进行不同信噪比下的仿真测试,结果表明:相较定步长LMS算法、双曲正切函数变步长LMS算法以及基于瞬时误差的模糊变步长LMS算法,所提方法的综合性能更优,在保证快速收敛的同时显著降低了稳态失调误差,具有更高的测量精度和抗噪性能。搭建超声测厚平台进行标准量块测量实验,结果表明:所提方法对不同厚度量块的测量相对误差均小于其他三种LMS算法,最大相对误差为0.710%。模糊变步长LMS时延估计方法为高精度超声飞行时间(Time of Flight,TOF)计算提供了重要技术支撑,有利于促进超声无损检测技术发展,具有一定的工程应用价值。
摘要为规避最小均方(Least Mean Square,LMS)算法不能同时提高收敛速度和降低稳态误差的固有缺陷,以及已有变步长LMS算法存在收敛速度慢和稳态误差估计精度差的问题,文中提出了一种基于变步长归一化频域块(Normalized Frequency-domain Block,NFB)LMS算法的汽车车内噪声主动控制方法。为了比较,应用传统的LMS算法、基于反正切函数的变步长LMS算法和变步长NFB-LMS算法分别进行实测汽车车内噪声的主动控制。结果表明,与其他两个算法相比,变步长NFB-LMS算法的收敛速度提高了70%以上,稳态误差减小了90%以上。变步长NFB-LMS算法在处理车内噪声信号时具有很高的效率,为进行汽车车内噪声主动控制提供了一种新方法。
摘要为改善滤波-x最小均方(filtered-x least mean square,FxLMS)算法在噪声主动控制时无法兼顾收敛速度和稳态误差的问题,提出了基于sigmoid-sinh分段函数的FxLMS(SSFxLMS)算法,并引入蚁狮算法对SFxLMS(sigmoid filtered-x least mean square)、ShFxLMS(sinh filtered-x least mean square)、SSFxLMS算法的参数进行优化。分别采用高斯白噪声和实测簇绒地毯织机噪声为输入信号,采用FxLMS、SFxLMS、ShFxLMS、SSFxLMS算法进行噪声主动控制仿真,对比分析这4种算法的性能。结果表明:与其他3种算法相比,采用SSFxLMS算法对高斯白噪声和簇绒地毯织机噪声进行控制时,误差信号的平均绝对值更小,平均降噪量与收敛速度也有大幅度提升。由此可知,SSFxLMS算法有效改善了FxLMS算法无法兼顾收敛速度和稳态误差的问题,研究结果为噪声主动控制算法设计提供了一定的参考。
摘要滤波x最小均方差(filtered-x least mean square,简称Fx-LMS)算法作为振动控制领域常用的自适应控制算法,其固定步长因子不能同时满足收敛速度和稳态误差的双重要求。为了改善Fx-LMS算法实施效果,提出一种基于反余切函数的滤波x变步长最小均方差(filtered x variable step size least mean square,简称Fx-VSSLMS)算法。首先,归纳了7种常规VSSLMS算法的步长更新公式,并按照其迭代特点予以性能分析与分类对比;其次,以压电柔性悬臂梁振动主动控制为算法验证目标,采用多体动力学软件Adams和Simulink进行联合仿真,表明所提的Fx-VSSLMS算法在振动控制中的有效性;最后,通过分析对比多种Fx-VSSLMS算法在不同噪声环境下的抑振效果,验证了所提出控制算法对噪声干扰的良好鲁棒性。