SDCode

This Matlab s code source contain a Spectrum Analyser

Find local minimum in matlab

浙大某老师matlab基础课程教材 例子挺多的，复习基础知识有帮助(Zhejiang University course materials based on a teacher matlab example Tingzhi, review the basics of help)

对于pso有详尽的程序，包含数个测试函数并对于PSO有详细的介绍(For the pso have detailed procedures, including several test function and a detailed introduction to pso )

This is a easy to understand and sample code for shape context, Written by: Soheil Mehralian at Isfahan University of Isfahan (IUT) Contact: S.Mehralian@ec.iut.ac.ir

matlab code for Viola Jones Object Detection

An important aspect of an ANN model is whether it needs guidance in learning or not. Based on the way they learn, all artificial neural networks can be divided into two learning categories - supervised and unsupervised. • In supervised learning, a desired output result for each input vector is required when the network is trained. An ANN of the supervised learning type, such as the multi-layer perceptron, uses the target result to guide the formation of the neural parameters. It is thus possible to make the neural network learn the behavior of the process under study. • In unsupervised learning, the training of the network is entirely data-driven and no target results for the input data vectors are provided. An ANN of the unsupervised learning type, such as the self-organizing map, can be used for clustering the input data and find features inherent to the problem.

说明：  该code读出naca4412.txt中基本balde坐标，在读取data1.txt中设计要求，生成FinalCoordinates.txt文件，包含所有生成balde airfoil所需coordinates。(this matlab code read the blade coordinates in naca4412.txt, and then read the design requirements in data1.txt. Finally, it will generate the FinlCoordinates.txt which include all the coordinates of blade airfoil.)

说明：  BP神经网络的一种回归算法研究，MATLAB实现并已通过系统仿真测试(A return of BP neural network algorithm, MATLAB simulation to achieve and have passed the test)

汽车制动防抱死系统的MATLAB/SIMULINK仿真模型，通过门限值作用(MATLAB/SIMULINK simulation model of automobile anti-lock braking system, through the threshold effect)