自适应加权FIR-Myriad混合滤波算法

针对FIR滤波器滤除脉冲噪声以及加权Myriad滤波器滤除高斯噪声的不足,提出基于FIR滤波器和加权WMy滤波器有效组合的一类新的非线性滤波器FIR-WMyH滤波器.利用神经网络中的反向传播算法,在均方误差准则下,推导了一个基于统计梯度的自适应算法.基于稳定α分布脉冲噪声模型下的仿真结果说明了该算法的良好的性能.     

用于杂波抑制滤波器优化设计的混合遗传算法 及其收敛性分析

参差时变动目标显示(MTI)滤波器是在强运动杂波背景下检测弱目标和缓解盲速问题的一种有效方法.选择适当参差码使参差时变MTI滤波器的第一零点尽可能浅,可在有效抑制杂波的同时避免陷入其中的弱目标丢失.本文采用了结合梯度的混合遗传算法(HGA)选择最优参差码,与标准遗传算法(SGA)相比,该算法只需要很小的种群规模.采用马尔可夫链方法证明了HGA是以概率1收敛的全局随机搜索算法.将该算法应用于米波雷达中,性能分析和仿真实验表明,基于混合遗传算法的杂波抑制滤波器设计是可行和有效的.     

低延迟码激励语音编码算法的最佳增益滤波器

该文采用加权L-S算法、有限记忆算法以及BP神经网络算法分别与G.728标准使用的Levinson_Durbin(L-D)方法进行5样点激励增益滤波方案比较测试,发现编码效果均好于G.728。其中加权L-S方法语音编码效果最好,其平均分段SNR高出G.728算法0.76dB。用该方法评价了16样点激励矢量增益滤波器和20样点激励矢量增益滤波器,加权L-S方法同样效果最佳。     

稳态噪声背景下加权Myriad滤波的遗传算法实现

该文利用遗传算法具有全局最优搜索的特点,同时,考虑到运算复杂度问题,提出了用十进制代替传统的二进制进行算子操作的遗传算法,来获得加权Myriad滤波器输出。另外,针对在原自适应权值训练算法中权值处于稳定区后波动仍较大的问题,分析了波动存在的原因并对其进行了改进.仿真结果表明,该方法在较多极值点的情况下,所有染色体均可快速收敛至全局极值点,并且改进后权值估计可使滤波效果有明显改善。     

基于加权最小二乘正则化方法的混合滤波器组最优化设计

模拟分析滤波器的实现误差以及数字综合滤波器有效阶数实现的设计误差造成的病态问题都将影响混合滤波器组(HFB)的重构效果.提出一种新的满足近似完美重构的基于加权最小二乘(WLS)正则化算法的IIR形式综合滤波器设计方法.该算法根据误差量二阶统计特性采用WLS算法抑制滤波器实现误差以及随机噪声等扰动因素影响,使得到的综合滤波器组频域响应解的加权误差平方和最小化,并通过Tikhonov正则化方法优化解的稳定性.提出一种IIR类型综合滤波器设计算法,并利用正则化方法优化滤波器系数,减小设计误差.该方法可应用于过采样HFB的设计.仿真结果表明该算法的有效提高系统鲁棒性和改善重构性能.     

Alpha稳定分布下基于RHMy滤波的MQAM信号码元速率估计方法

针对Alpha稳定分布噪声环境下,传统的MQAM信号码元速率估计方法性能恶化甚至完全失效的问题,本文结合了改进的Myriad类滤波与小波变换法的优点,提出一种基于递归混合Myriad滤波(Recursive Hybrid Myriad filter, RHMy)的高阶消失矩二次小波变换法对MQAM信号进行码元速率估计。首先采用RHMy滤波充分抑制噪声中的脉冲成分,再采用高阶消失矩小波估计码元速率。仿真结果表明,在Alpha稳定分布噪声环境中,相比于多尺度Haar小波变换法、分数低阶循环谱法与基于加权Myriad滤波(Weighted Myriad filter, WMy)的小波变换法,该方法有效的提高了低广义信噪比下的估计精度,同时在不同的脉冲噪声条件下具有较好的鲁棒性。      

自适应多模滤波算法的研究

文章论述的自适应多模滤波器采用了两种目标运动模型,其一为匀速运动模型,其二为匀加速运动模型,滤波值为两个滤波器的加权值,加权系数可自适应调节.文中还对核算法及α-β、α-β-γ滤波算法进行了仿真,仿真结,果表明该算法对目标的运动轨迹适应性较强.     

一种迭代正弦频率估计硬件实现研究

 本文提出了一种基于迭代算法的八通道滤波器组单频正弦信号频率估计方法,该算法的基本思想是利用频域重叠的多通道滤波器来实现大的频率估计范围,同时提高单通道内的信噪比;还对滤波抽取后的数据进行迭代,这样即使采用运算量最小的不加权线性预测算法也能实现高精度测频,并采用FPGA实现了该算法,最后数值仿真结果证实所提算法的优异性能.     

直方图加权均值滤波器

本文提出了一种适合于消除图像盐椒噪声的滤波器——直方图加权均值(HWM)滤波器.该算法以加权均值滤波器为基础,利用被污染图像的直方图函数作为权值进行加权运算.实验表明,对于噪声率在5％到90％的的噪声图像,HWM滤波器具有良好而稳健的去噪效果,当噪声率超过70％时,其优越性更加突出.     

基于加权总体最小二乘正则化方法的混合滤波器组最优化设计

模拟分析滤波器组的实现欠理想、系统噪声以及数字综合滤波器有效阶数实现所带来的系统误差均有可能造成混合滤波器组的设计出现解不稳定、无唯一解等病态问题,影响混合滤波器组的准确重构效果。本文首先给出了满足准确重构条件下,以综合滤波器组频域响应为求解变量的混合滤波器组线性求解模型。针对线性方程中系数矩阵以及目标向量受扰动误差影响特点,提出一种新的基于加权总体最小二乘正则化算法的IIR形式综合滤波器设计方法。算法以系统扰动误差最小化为目标函数,根据随机误差变量的二阶统计特性,采用加权总体最小二乘算法抑制滤波器实现误差以及随机噪声等扰动因素影响,使得到的综合滤波器组频域响应解的加权误差平方和最小化,并通过Tikhonov正则化方法优化病态情况下方程组解的稳定性。提出一种IIR类型的综合滤波器系数的求解算法,并利用正则化方法优化滤波器系数,提高系统稳定性。该方法可应用于过采样混合滤波器组的设计。仿真结果表明该算法的有效提高系统鲁棒性和改善重构性能。      

基于指数遗忘分布的瞬时频率估计算法

本文提出了基于指数遗忘分布的信号瞬时频率估计算法.与其他的时频分布算法相比,通过采用单边指数分析窗口,指数遗忘分布可以在时频分析中引入迭代算法从而大大提高计算效率,本文对这一算法的性能进行了理论分析,同时其有效性在相应的仿真试验中得到了证明.     

A hybrid genetic algorithm for analog active filter component selection

Analog filters are circuits that process electrical signals on a frequency-dependent basis. Analog filter circuits can be implemented using resistors, capacitors and inductors and they can also be implemented with only resistors and capacitors with the use of active circuit equipments. The selection of optimum component values is difficult because of the number of possible filter combinations. This paper presents an effective algorithm that hybridizes the Genetic Algorithm (GA) to form a Hybrid Genetic Algorithm (HGA) and proposes the use of Tabu Search (TS) for the analog active filter component selection. The GA has a powerful global searching ability and so is used to perform exploitation and because TS also has good local searching ability, it too is applied to perform exploitation. Thus, the proposed HGA will have very good searching ability. In this study, a band-pass Sallen-Key filter circuit was used, and the filter component values were found using HGA with LabVIEW. The results are compared to other reported state-of-the-art algorithms, such as the artificial bee colony (ABC) and differential evaluation (DE) to demonstrate the effectiveness and efficiency of the developed method. It can be said that the developed LabVIEW based HGA gives satisfactory results with regard to amplitude response, the minimum fitness values and the computational time.     

一种非线性回归模型参数估计的混合基因算法

提出了一种新的结合可变多面体法和基因算法的混合基因算法(HGA),它通过对问题的解空间交替进行全局和局部搜索,达到快速收敛至全局最优解,较好地解决了基因算法在达到全局最优解前收敛慢的问题。非线性回归模型参数估计的实验表明该算法具有较好的通用性和有效性。     

Hybrid Genetic Algorithm for the Design of Modified Frequency-Response Masking Filters in a Discrete Space

This paper presents the design of high-speed, arbitrary bandwidth sharp finite impulse response filters with signed powers-of-two coefficients based on a modified frequency-response masking (FRM) structure. A novel hybrid genetic algorithm (HGA) is proposed to jointly optimize all subfilters in a discrete space. The proposed HGA introduces the simulated annealing technique into the genetic algorithm (GA) optimization process and effectively prevents the GA from prematurely converging. It is shown, by means of examples, that FRM filters designed by the HGA achieve a significant reduction in the number of bits.     

分集接收混合遗传算法多用户检测器在异步CDMA移动通信中的应用研究

本文研究了将混合遗传法应用于码分多址扩频通信的多用户检测中，从而消除多址接入干扰的方法。本文先给出了在异步瑞利衰落信道下解调扩频信号的分集接收混合遗传算法多用户检测器的原理框图，然后分析了用混合遗传算法进行多用户检测的理论依据和实际性能。仿真结果表明无论是抗多址干扰还是抑制远近效应，分集接收混合遗传算法多用户检测器都明显优于传统接收机，其性能接近分集接收最佳多用户检测器。     

基于混合遗传算法的m序列波形优化设计

现代雷达体制多采用大时宽带宽积的m-序列二相编码脉冲压缩波形,解决信号波形优化问题即使信号波形的脉压比在尽量少损失SNR和主瓣宽度的基础上达到极值.对于m-序列,初始寄存器的选取是关键.对于较长的码,传统的优化方法由于运算量过大造成组合爆炸或陷入局部极值而无法找到最优,传统遗传算法也由于初始种群数的规模运算量比较大,将梯度搜索和遗传算法相结合的混合遗传算法很好的解决了这个问题,通过优化m-序列二相码波形的仿真和性能分析验证了该算法的可行性和有效性.     

基于改进野草算法的推荐对象建模技术研究

为了提高个性化推荐系统中模型描述的准确性，提出了一种改进的入侵野草优化算法。该算法将野草算法和混合遗传算法有机地结合，旨在克服传统野草算法过旱收敛、易于陷入局部优化的不足。最后，计算机仿真结果表明了所提出的算法明显优于其他常见的建模算法。     

Multilevel Redundancy Allocation Optimization Using Hierarchical Genetic Algorithm

This paper proposes a generalized formulation for multilevel redundancy allocation problems that can handle redundancies for each unit in a hierarchical reliability system, with structures containing multiple layers of subsystems and components. Multilevel redundancy allocation is an especially powerful approach for improving the system reliability of such hierarchical configurations, and system optimization problems that take advantage of this approach are termed multilevel redundancy allocation optimization problems (MRAOP). Despite the growing interest in MRAOP, a survey of the literature indicates that most redundancy allocation schemes are mainly confined to a single level, and few problem-specific MRAOP have been proposed or solved. The design variables in MRAOP are hierarchically structured. This paper proposes a new variable coding method in which these hierarchical design variables are represented by two types of hierarchical genotype, termed ordinal node, and terminal node. These genotypes preserve the logical linkage among the hierarchical variables, and allow every possible combination of redundancy during the optimization process. Furthermore, this paper developed a hierarchical genetic algorithm (HGA) that uses special genetic operators to handle the hierarchical genotype representation of hierarchical design variables. For comparison, the customized HGA, and a conventional genetic algorithm (GA) in which design variables are coded in vector forms, are applied to solve MRAOP for series systems having two different configurations. The solutions obtained when using HGA are shown to be superior to the conventional GA solutions, indicating that the HGA here is especially suitable for solving MRAOP for series systems.      

Wireless communication network design in IC factory

A wireless local area network (WLAN) is designed for an IC factory in Hong Kong using the hierarchical genetic algorithm (HGA). The HGA is capable of handling multiobjective functions and discrete constraints. Because of this uniqueness, together with the adoption of a Pareto ranking scheme, a solution can be reached even when skewed multiobjective functions and constraints confinements are being imposed. It has been found from this study that a precise number of base stations can be identified for the WLAN network, while it can satisfy a number of objectives and constraints. This added feature provides a further design tradeoff between cost and performance at no extra effort     

应用激光多普勒技术测量HGA共振的研究

对硬盘磁头HGA组件进行了模态分析和计算,介绍了激光多普勒技术用于硬盘磁头HGA组件的共振测量的原理,并据此设计了激光多普勒测量系统用于测量HGA共振特性.使用该测量装置,成功的测量了三组HGA的共振数据.试验表明,该测量系统能有效的实现HGA共振测量,并可获得较高的精度.