optimierung

matlab 非平稳信号分析，功能强大，但本人不太会用(matlab 脟脝 陆 脦脠脨脜 潞 脜 脰脦枚 拢 卢 鹿 | 脛脺脟 驴 )

成都国腾辉GM3101倒车雷达专用芯片显示源程序(Chengdu, China Tenghui GM3101 reversing radar dedicated chip source)

涵盖了多种卡尔曼滤波算法及MATLAB实现（书内附有一些例子的源M文件），作者将多年的工作经验融入此书，使之成为学习卡尔曼滤波的同学一本不可多得的经典参考书。(The book content is very comprehensive, covering a wide range of Kalman filter algorithm and MATLAB implementation of many years of work experience will be integrated into the book, making the students learn a Kalman filter rare classic reference book.)

PV-SIMULINK FILE FOR SOLAR SYSTEM

Program untuk ekstraksi ciri fitur suara

比较NLMS、基于分块的LMS和基于符号的LMS三种算法，并且实现信道均衡(More NLMS, based on the LMS and block LMS three algorithms based on symbols, and to achieve channel equalization)

three-phase model of induction motor

CGA - Canonical Genetic Algorithm with matlab

实验一 双极性矩形随机信号的归一化功率谱密度一 1.1 功率谱密度简介 平稳过程的任何一个非零样本函数的持续时间为无限长，显然都不满足绝对可积和总能量有限的条件。因此，它的傅里叶变换不存在即没有频谱函数。所以我们用功率谱密度来表述其频谱特性。 随机过程的任一实现是一个确定的功率型信号。而对于任意的确定功率信号f(t)，它的功率谱密度为： 式中， 是f(t)的截短函数 对应的频谱函数。f(t)是平稳随机过程 的一个实现。而随机过程某一个实现的功率谱密度不能作为过程的功率谱密度。过程的功率谱密度应该看作是任一实现的功率谱密度的统计平均，即 虽然该式给出了平稳随机过程的功率谱密度，但我们通常都不利用这个式子来计算功率谱。我们知道，确知的非周期功率信号的自相关函数与功率谱密度是一对傅里叶变换。对于平稳随机过程，也有类似的关系，即 和 对于平稳随机过程我们通常先求出其自相关函数再利用上式求出其功率谱密度。 1.2 实验要求  1.了解平稳随机信号功率谱的概念及计算方法  2.仿真不同占空比，等概、非等概双极性矩形随机信号的归一化功率谱密度  3.分析不同信号所包含的频谱分量，有无直流分量和定时分量信息 (A pair of rectangular random experiment polarity signal sample return a nonzero function of any duration power spectral density of a 1.1 power spectral density of a stationary process Introduction of infinite length, apparently not satisfied absolutely integrable and the total energy of the limited conditions. Therefore, it is the Fourier transform of the spectrum that does not function does not exist. Therefore, we use the power spectral density to express their spectral characteristics. Any random process is a realization of a certain type signal power. For arbitrarily determined power signal f (t), its power spectral density is: wherein, is f (t) is a function corresponding to the truncated spectrum function. f (t) is a stationary random process of realization. The random process to achieve a certain power spectral density can not serve as the power spectral density of the process. Power spectral density process should be seen as a statistical average power spectral density of any r)

The channel modeling work package WP1 of IST-WINNER project provided a Matlab implementation of the WINNER Phase II Model (referred as WIM this onward). The main purpose of the WIM channel models is to generate a radio channel realisations for a link and system level simulations. The implementation is based on the earlier implementations of WINNER II interim model [6], WINNER I (interim) model [3], 3GPP/3GPP2 Spatial Channel Model (SCM) [4] and SCM(E) Extension models. For details concerning the WIM model, please refer to [1]. This document describes the SW implementation structure of WIM, its input/output interface and its functionality. Channel model scenarios and parameters are modified to correspond to IMT.EVAL [7] channel model.