Spatial-channel-model-for-MIMO-3GPP

Simulated annealing m-file for Rosenbrock function optimization

广义旁瓣相消器，阻塞矩阵B2，一个期望信号，一个干扰，高斯白噪声(the simulation of GSC(B2))

基于极限学习机的预测模型，数据为混沌数据(extreme learning machine)

本书专为大学自动控制、机械电子、机械制造与自动化、电力电气、通信工程等专业大 学本科生、研究生、教师、科技工作者编写。本书力图将信号分析与处理、信号与系统、数字 信号处理、工程测试等有关教学内容和MATLAB语言紧密、有机地结合起来，使学生在 学习基础理论知识的同时学会应用MATLAB，在学习应用MATLAB的同时，加深对基 础知识的理解，增强学生的计算机应用能力，提高教学效果。本书编入大量MATI‘AB应 用程序，每章也有一定的数量习题，供读者能尽快掌握MATLAB的编程技巧。(This book is designed for the University of automatic control, mechanical, electronic, mechanical manufacturing and automation, electrical power, communications, engineering and other professional undergraduates, graduate students, teachers, scientists and write. This book seeks to signal analysis and processing, signals and systems, digital signal processing, engineering, testing and other relevant teaching content and MATLAB language closely, organically combine to make the students learn basic theoretical knowledge at the same time learn to use MATLAB, MATLAB in learning applications at the same time, deepen their understanding of the basics, enhance their computer skills to improve teaching effectiveness. Incorporated into the book a lot MATI' AB applications, each chapter there is a certain number of exercises for the reader can quickly grasp the MATLAB programming skills.)

matlab monte-carlo simulation for American option pricing and other path dependent derivative(matlab monte-carlo simulation for American option pricing and other path dependent derivative)

说明：  小波作业源码，对小波系统wavelet变换进行处理，是一种通用的小波处理算法(Wavelet job source, wavelet processing systems wavelet transform is a common wavelet processing algorithms)

画贝塞尔（besselj）函数和第二类变型贝塞尔（besselk）函数图像(the images of besselj and besselk function )

此文件是Weifeng Liu等编著《Kernel Adaptive Filtering A Comprehensive Introduction》一书的源代码。对应书上每一章节。是学习Kernel adaptive filter的不二选择。(This document is the source code of Liu Weifeng, a compiled book book that corresponds to each chapter. Learning kernel adaptive filter of choice.)

line point and edge detection

CMA WITH N EQUAL TO 8,4,20