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Algorithm Collectionsfor Digital Signal Processing Applications Using Matlab

英文书Beginning Mac OS X Snow Leopard Programming的源码。(Source code of book "Beginning Mac OS X Snow Leopard Programming")

基于RLS的RLS、SMI、SINR、LMS、MMSE算法的matlab环境下的自适应波束成型(Adaptive beamforming based RLS RLS, SMI, SINR, LMS, MMSE algorithm matlab environment)

说明：  matlab代码 交通流元胞自动机仿真 双车道 如果需要改变车流密度在脚本文件中修改fp.(Matlab code traffic flow cellular automata simulation of two lanes If you need to change the traffic density, modify the FP in the script file.)

mse算法的matlab仿真程序，包含LS_MSE_calc.m，MMSE_MSE_calc.m，SER_compare.m 文件(mse algorithm matlab simulation program, including LS_MSE_calc.m, MMSE_MSE_calc.m, SER_compare.m file)

说明：  三项交流同步电机的仿真 已经调试过了 可以使用(3 AC synchronous motor simulation has been debugging can use)

关于遗传算法（GA）的相关内容介绍（英文资料）以及算法工具箱(on genetic algorithm (GA) introduced the relevant content (English) and the algorithm toolbox)

这是一个SA求解tsp旅行商的matlab源代码，由m文件构成，可方便大家学习模拟退火算法。(This is a traveling salesman tsp SA for the Matlab source code, document constitute m, can facilitate learning simulated annealing.)

压缩感知，又称压缩采样，压缩传感。它作为一个新的采样理论，它通过开发信号的稀疏特性，在远小于Nyquist 采样率的条件下，用随机采样获取信号的离散样本，然后通过非线性重建算法完美的重建信号。(Compressed sensing, also known as compressed sampling, compressed sensing. It as a new sampling theory, it is through the development signal sparse characteristics under conditions of far less than the Nyquist sampling rate, with a random sampling obtain discrete samples of the signal, and then through a perfect reconstruction of the signal of the non-linear reconstruction algorithm.)

说明：  粒子群算法求解约束多目标优化万能matlab代码。本代码是基于有约束条件的寻优问题，采用APSO可以加快寻优的速度，修改参数比较简单，目标函数和上下限根据自身的需要进行改动，，可以实现目标函数的寻优(Particle swarm algorithm for solving constrained multi-objective optimization universal matlab code. This code is based on the optimization problem with constraints. Using APSO can speed up the optimization process. It is relatively simple to modify the parameters. The objective function and the upper and lower limits are changed according to their own needs. The optimization of the objective function can be achieved.)