matlab

matlab code for Particle filter tutorial

爱尔兰B、爱尔兰C、D算法、F算法 仿真程序(ElangB、ElangC、D、F algorithm Simulation)

Pavel Ripka, Alois Tipek. Modern Sensors Handbook 2007

用粒子群算法求解车间调度问题，包含甘特图的制作程序(Particle swarm optimization algorithm for job shop scheduling problem, including Gantt chart)

模式识别工具箱，很好用，matlab原程序(pattern recognizition toolbox)

moving average filter matlab implementation

说明：  matlab的中文帮助，，对初学matlab的很有用，，我就是看这个入门的。(matlab in Chinese help, very useful for beginners matlab,, I just see this entry in the.)

对轴承振动信号进行滤波和包络频谱分析，可通过包络谱发现轴承故障，也可用于其他故障诊断的研究，程序已调试通过(Bearing vibration signal filtering and envelope spectrum analysis, bearing failure can be found through the envelope spectrum can also be used to study other troubleshooting procedures have been debugging through)

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)

应用条件随机场知识对图像进行分割，场景理解。(Application CRFs knowledge of image segmentation, scene understanding.)