fortran

介绍了随机信号处理，并重点阐述了卡尔曼滤波在随机信号处理中的应用，并有matlab仿真的实例。(Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercise)

标准粒子群算法的实现思想基本按照粒子群算法(2) 标准的粒子群算法的讲述实现。主要分为3个函数。第一个函数为粒子群初始化函数 InitSwarm(SwarmSize......AdaptFunc)其主要作用是初始化粒子群的粒子，并设定粒子的速度、位置在一定的范围内。本函数所采用的数据结构如下所示： 表ParSwarm记录的是粒子的位置、速度与当前的适应度值，我们用W来表示位置，用V来代表速度，用F来代表当前的适应度值。在这里我们假设粒子个数为N，每个粒子的维数为D。(His thought of the implementation of the standard particle swarm algorithm according to the particle swarm algorithm (2)- the standard particle swarm algorithm about implementation. Mainly divided into three functions. The first function of particle swarm initialization function InitSwarm (SwarmSize... AdaptFunc), its main function is to initialize particle swarm particle, and set the particle s velocity, position in a certain range. The function of data structure is as follows: ParSwarm record table is the particle s position, speed and the current fitness value, we use W to represent the position, represented speed with a V, to represent the current fitness value with F. Here we assume that the number of particles N, each particle dimension for D.)

PID控制 PI控制 PD控制 matlab程序 初级入门(PID control PI control PD control matlab program entry-)

这是东南大学信息科学与工程学院《数字信号处理 第二版》第四章的实验，关于IIR 滤波器的( This is the School of Information Science and Engineering, " Digital Signal Processing Second Edition" Southeast University experiment of Chapter IV, on IIR filters)

Program to add a top x-axis in matlab

OFDM中的关于扰码器的个人设计的MATLAB的算法，比较经典的 ！(OFDM on the scrambler design of the personal MATLAB algorithm, more classic!)

贝叶斯学习算法，用在压缩感知和稀疏恢复重建之中。(The MSBL algorithm for Compressed Sensing and sparse recovery.)

说明：  《模糊ART和模糊ARTMAP 神经网络》这些文件包允许你创建、训练、测试模糊ART和模糊ARTMAP神经网络。 作者: Aaron Garre("vague and ambiguous ARTMAP ART neural network" These packages allow you to create, training, testing and Fuzzy Fuzzy ART ARTMAP neural networks. Author : Aaron Garre)

5第五章 数值计算.本章教授你如何使用MATLAB的数值计算功能。(chapter 5 would tell you how to use compute in the matlab。)

加权最小二乘双支持向量机算法应用实例，作为学习双支持向量机的例子应用(Weighted least squares double support vector machine)