hssvm_series_toolkit

这个程序是单纯行法寻优子程序（多变量寻优），是我的一个作业，希望对大家有用。(This procedure is a simple line method optimization subroutine (multi-variable optimization), is one of my operation, I hope useful for all of us.)

Matlab script that randomize rows and/or colums

这是具有功率因数校正的开关电源的MATLAB/SIMULINK仿真模型，希望对有用的人，有所帮助！(this is a simulink model of power supply with PFC, which is useful for those who study on this!)

MatLab Files for GLOBAL POSITIONING SYSTEMS, INERTIAL NAVIGATION, AND INTEGRATION

codes of ADAPTIVE FILTERS book, Wiley, 2008.

利用MATLAB做三层框架结构的弹塑性分析，分析结构在地震作用下的位移反应(Using MATLAB to do a three-tier framework structure of the elastic-plastic analysis, analysis of the displacement response of the structure under seismic action)

说明：  通信里面的gardner算法 实现定时同步功能(Gardner algorithm to achieve timing synchronization)

一份matlab的ppt教程，给初学者，比较多面地介绍了matlab的基础(The ppt of a matlab tutorial for beginners, more multi-faceted introduction to the basis for matlab)

有关matlab学习的ppt,内容很全面，希望对大家有点用处(For matlab learning ppt, the content is very comprehensive, I hope we are a bit useless)

2. 设 是窄带信号，定义 是在 区间上均匀分布的随机相位。 是寬带信号，它是一个零均值、方差为1的白噪音信号e(n)激励一个线性滤波器而产生，其差分方程为 。 1） 计算 和 各自的自相关函数，并画出其函数图形。根据此选择合适的延时，以实现谱线增强。 2） 产生一个 序列。选择合适的 值。让 通过谱线增强器。画出输出信号 和误差信号e(n)的波形，并分别与 和 比较。 (Computer Experiments: 1. Consider an AR process x(n) defined by the difference equation where v(n) is an additive white noise of zero mean and variance .The AR parameters and are both real valued: a) Calculate the noise variance such that the AR process x(n) has unit variance .Hence , generate different realization of the process x (n). b) Given the input x (n), an LMS filter of length M = 2 is used to estimate the unknown AR parameters and . The step size is assigned the value 0.05. Compute and plot the ensemble average curve of and by averaging the value of parameters and over an ensemble of 100 different realization of the filter. Calculate the time constant according to the experiment results and compare with the corresponded theoretical value. c) For one realization of the LMS filter, compute the prediction error And the two tap-weight errors and Using power spectral plots of , show that)