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matlab中的关于CDMA接收和发射的部分simulink(Simulation of CDMA Transmitter And Receiver in Matlab)

通过输入单位脉冲序列从而得到相应的单位脉冲响应(Input unit pulse sequence get unit impulse response )

基本蜂群的另一种实现形式~~~~~~~~~~~~~~~~~~(basic ABC)

计算最大李雅普诺夫图，来分析微分方程的分岔情况(To calculate the largest Lyapunov Figure to bifurcation analysis of differential equations)

With PRP conjugate gradient method for solving unconstrained problem

用matlab实现GLG论文中的灰度图像的对比度增强算法(GLG paper to achieve the grayscale image contrast enhancement algorithm by matlab)

太阳能光伏阵列的matlab simulink 仿真 不带mppt功能(Matlab simulink simulation of solar photovoltaic array function without mppt)

本书是“MATLAB应用技术”系列丛书之一，以最新推出的MATLAB中的小波分析工具箱Wavelet Toolbox 3.0版本为基础。全书共分为三部分，第1部分着重介绍了小波理论基础，包括小波基础知识、连续小波变换、离散小波变换、多分辨率分析与正交小波变换、小波变换和多采样滤波器组、二维小波变换与图像处理及小波包的基本原理等；第2部分重点说明了小波分析工具箱的详细使用方法，包括图形用户接口、小波通用函数、一维小波变换的MATLAB实现、二维小波变换的MATLAB实现、小波包变换的MATLAB实现、信号和图像的降噪和压缩，以及最新的信号和图像的提升小波变换等内容；第3部分主要介绍了小波工具箱的应用基础，以及小波变换在语音和生物医学信号处理中、故障诊断中、数字水印中的应用方法。(This book is "MATLAB application technology" Series on one of the latest MATLAB Wavelet toolbox in the Wavelet Toolbox 3.0 version of the basis. The book is divided into three parts, Part 1 focuses on the theory of wavelet basis, including basic knowledge of wavelets, continuous wavelet transform, discrete wavelet transform, multiresolution analysis and orthogonal wavelet transform, wavelet transform and multirate filter banks, 2-dimensional wavelet transform and image processing and the basic principles of wavelet packets, etc. Part 2 highlights the detailed use of wavelet analysis toolbox methods, including graphical user interface, wavelet generic function, one-dimensional wavelet transform MATLAB realization of two-dimensional wavelet transform of the MATLAB implementation of the MATLAB implementation of wavelet packet transform, signal and image noise reduction and compression, and the latest signal and image enhancement of wavelet transform content Part 3 introduces the wavele)

simple implementation of DVBS technology

本文针对基于经验模态分解ＥＭＤ的时空滤波器存在的固有模态函数分量中频率混叠交叉导致有用信号与噪声一起被滤除的问题结合小波在时间尺度两域表征信号局部特征的特性提出了一种基于能量估计实现ＥＭＤ分解层数确定(In this paper, based on empirical mode decomposition EMD temporal filter mode functions inherent component of cross-frequency aliasing and noise together lead to useful signal is filtered in the time scale of the problem combined with wavelet domain characterization of two local features of the signal characteristics of proposed achieve energy estimation based on EMD decomposition level determined)