Leastsquare

matlab仿真实现临界比例度算法功能实现(matlab simulation algorithm to achieve the critical function of the proportion of degree achievement)

在MATLAB中用M文件编写来实现四种不同的单神经元控制器(realize single-neurons PID Controller in MATLAB)

Volterra_混沌序列的相空间重构程序，利用matlab编程，可以将一维时间序列重构到高维空间，挖掘出隐含的信息，提高预测精度，以Volterra混沌序列为例，展示混沌的美妙(Phase space reconstruction program, Volterra_ chaotic sequence using matlab programming, refactoring can be one-dimensional time series into a high dimensional space, dig out the hidden information, improve forecast accuracy, Volterra chaotic sequence, for example, showing the chaotic wonderful)

matlab实现了五类灰色关联度模型的计算,包含CV、CA、Single、当前、恒转弯速率、转弯模型，包括邓氏关联度、绝对关联度、斜率关联度、改进绝对关联度。( matlab implements five gray correlation degree computing model, It contains CV, CA, Single, current, constant turn rate, turning model, Including Deng s correlation, absolute correlation, correlation of slope, improved absolute correlation.)

to understand the Algorithm go to matlab help in page dct2 and idct2 to get the mathematical expression for M = N = 8, we can calculate the most of hard values and save it as LUTs to speed up the execution now compare our special 8X8 functions with the internal general functions use this code: A = int32(100*rand(8,8)) tic for i = 1 : 1000 IDCT_8X8(DCT_8X8(A)) end toc tic for i = 1 : 1000 idct2(dct2(A)) end toc i had built the general functions too, but with low speed (to understand the Algorithm go to matlab help in page dct2 and idct2 to get the mathematical expressionfor M = N = 8, we can calculate the most of hard values and save it as LUTs to speed up the executionnow compare our special 8X8 functions with the internal general functionsuse this code: A = int32 (100* rand (8,8)) tic for i = 1: 1000 IDCT_8X8 (DCT_8X8 (A)) end toc tic for i = 1: 1000 idct2 (dct2 (A)) end toc i had built the general functions too, but with low speed)

it is descipe use of speech recogination using matlab

基于线性判别的人脸识别，本设计对主成分分析和线性判别两种子空间方法进行了深入研究，包括LDA及其在人脸识别应用的若干问题(Face recognition based on linear discriminant, the design of the principal component analysis and linear discriminant subspace methods are two in-depth study, including the LDA and its Application in Face Recognition Issues)

点云三维重建，用matlab写成的，效果很好，而且速度也比较快(Point cloud reconstruction, written with matlab, works well, but speed is faster)

limziv algortithm for source coding

Is a good way to use geodesic active contours give you more comfortable you will be able to apply this code around the world