US6298463

说明：  在matlab中四阶Runge-Kutta法求解常微分方程(Runge-Kutta)

Support Vector Machine ToolBOX for MatLAB

this is the mse of th camera men with differner wavelet families

To calculate PBG for triangle lattice

calculate group delay

此文件是基于MATLAB环境下的关于FIR滤波器设计程序 其中包括了MATLAB的源程序和采用循环缓冲区实现的汇编源程序和连接程序。(This document is based on the MATLAB environment on FIR filter design process including the use of MATLAB and the cycle of the source buffer to achieve the compilation of source code and connection procedures.)

自己编程的matlab成绩查询系统，能实现对.txt以及.xls等多种文件格式的读取，并通过mcc命令转化为可执行文件。压缩包内含所有源码。(Own programming matlab query system can achieve right. Reading txt and. Xls and other file formats, and through the mcc command into an executable file. Archive contains all the source code. .)

EMD algorithm..used in speech processing, breaks trhe signal upto fundamental levels

说明：  近年来，基于启发式的多目标优化技术得到了很大的发展，研究表明该技术比经典方法更实用和高效。有代表性的多目标优化算法主要有NSGA、NSGA-II、SPEA、SPEA2、PAES和PESA等。粒子群优化(PSO)算法是一种模拟社会行为的、基于群体智能的进化技术，以其独特的搜索机理、出色的收敛性能、方便的计算机实现，在工程优化领域得到了广泛的应用，多目标PSO(MOPSO)算法应用到了不同的优化领域[9~11]，但存在计算复杂度高、通用性低、收敛性不好等缺点。 多目标粒子群（MOPSO）算法是由CarlosA. Coello Coello等在2004年提出来的(In recent years, heuristic-based multi-objective optimization technology has been greatly developed, and research shows that this technology is more practical and efficient than classical methods. Representative multi-objective optimization algorithms mainly include NSGA, NSGA-II, SPEA, SPEA2, PAES and PESA. Particle Swarm Optimization (PSO) algorithm is an evolutionary technology based on swarm intelligence that simulates social behavior. With its unique search mechanism, excellent convergence performance, and convenient computer implementation, it has been widely used in the field of engineering optimization. The objective PSO (MOPSO) algorithm is applied to different optimization fields [9~11], but it has shortcomings such as high computational complexity, low versatility, and poor convergence. The multi-objective particle swarm optimization (MOPSO) algorithm was proposed by Carlos A. Coello Coello et al. in 2004)

Pisarenko 谐波分解算法源码,可用于对信号进行频率估计。(Pisarenko harmonic decomposition algorithm source code, can be used to estimate the frequency of the signal.)