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时间序列分析，AR模型，用于流数据预测与滤波 输入参数：y为原始数据矩阵，p为AR模型的阶数，la为自回归模型的遗忘系数 输出参数：预测值，置信区间，离群点等(Time series analysis, AR model for prediction and filtering data stream input parameters: y original data matrix, p is the order of the AR model, la self-forgetting coefficient regression model output parameters: predictive value, confidence intervals, outlier points)

IMF法用作轴承故障检测程序，含所需方程m文件及图像文件(Copyright (c) 2012, Santhana Raj All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS AS IS AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIM)

基于C MEX S-函数永磁同步电机控制系统仿真建模研究(C MEX S-function based on permanent magnet synchronous motor control system simulation modeling)

数字聚类识别,基于图像模式识别-VC++技术实现书的基础上完成的(Number of cluster identification, image-based pattern recognition technology-VC++ based on the completion of the book)

dynamics analysis of SC robot

说明：  通过matlab程序实现最小费用最大流算法，获取最多的经济效益(By matlab program for minimum cost maximum flow algorithm, get the most cost-effective)

simulation of machine synchrone

读取matlab 文件夹中所有的文件路径 包括子文件夹的文件路径(Read all matlab folder including subfolders file path file path)

％ FSK-FM方案的可解调问题。 ％ 高斯噪声 SNR = 2OdB 并假设镜像信号非常小。仿真设置5％( FSK-FM program can demodulation problem. Gaussian noise SNR = 2OdB and assuming the image signal is very small. Simulation set up 5)

45666031LBG-Vector-Quantization in speaker recognition