SimAlamouti

当线性代数联立方程组的系数矩阵为三对角阵T时，可将T分解为主对角元素为1的下三角阵L和另一个右三角阵R的积。(Simultaneous linear algebraic equations when the coefficient matrix is tridiagonal matrix T, can break down the main diagonal elements of T 1 of the lower triangular matrix L and the other right-triangular matrix R of the product.)

bp网络训练工具箱适合新手学习和使用很有好处(Bp neural network training kit for beginners learn and use is very good )

取x轴Y轴某些点的坐标，用线连起来，包线图(Check point coordinates, even from the envelope )

code pid controller with matlab 2013

matlab中冒号的使用总结，希望对大家有用(Summary of the use of matlab colon, we want to)

自己编写的一个Krawtchouk不动距程序,附有图像处理应用的论文(I have written a program Krawtchouk Moments, with a paper image processing applications)

implement of kalman filter in Matlab (implement of kalman filter in Matlab)

说明：  matlab与人工神经网络2007 配套源代码(matlab and artificial neural network package source code, 2007)

3 gaussian random variable generation and plotting using matlab code

本实验语音库为免费的柏林情感语音库，其采样频率为16KHZ，16bit量化。该语音库共有500 句情感语音信号，分别由十名专业演员(5 男，5 女)在不同情感状态下（高兴、愤怒、平静、悲伤、害怕、厌烦、憎恨）朗读十句不同文本的德语组成。本实验选取其中的部分情感（高兴、愤怒、悲伤）加以识别。仿真实验环境为MATLAB7.0。 实验选取的情感特征为短时平均能量、短时平均幅度、基频和短时过零率。为了降低不同人在表达不同情感时的个人差异造成的影响，本文实验过程中将提取的情感特征进行归一化处理。归一化采取将同一个人的三种情感语音信号的情感特征放在一起归一化处理，并将归一化后的情感特征作为KNN分类器的训练样本和测试样本。 该实验使用了传统的KNN算法和改进算法两种识别方式，通过实验结果对比了各自的特点。 (This experiment YuYinKu for free Berlin YuYinKu emotion, the sampling frequency for 16 KHZ, 16 bit quantification. The YuYinKu 500 words of emotional speech signal, respectively by ten professional actors (5 male, five female) in different emotional state (happy, anger, sadness, fear, calm, bored, hate) read ten sentences in different text of the German. This experiment selection of part of the emotions (joy, anger, sadness) is recognized. The simulation experiment environment for MATLAB7.0. The selection of emotional characteristics for short-term average energy, short-term average amplitude, frequency, and the short zero rate. In order to reduce the different people in different emotional expression of the impact of individual differences, the experiment process will extract emotional characteristics is normalized. The normalized will take the same three kind of emotional speech signal emotional features normalized put together, and after the normalized the emotional characteristics)