gross-error

模式识别常用的工具箱，包括各种距离度量等必须的算法(Commonly used pattern recognition toolbox, including a variety of distance measures such as the algorithm must)

3种伪随机数列发生器的matlab编码以及其各种特性的分析(Three kinds of pseudo-random number generator matlab bar coding and analysis of its characteristics)

this is bldc simulink file in matlab and sensorlles method for starting.

很不错的一段代码，对于ostu阈值分割的理解有很大帮助(Very good piece of code, for ostu segmentation of great help in understanding)

Robot Control with matlab

功率谱估计是利用有限长的数据估计信号的功率谱，广泛应用于各个领域。功率谱估计主要分为经典谱估计与现代谱估计。常用的经典谱估计方法有周期图法，相关法，周期图的改进法，常用的现代谱估计方法有最大熵谱估计，AR模型，MA模型，ARMA模型。经典谱估计适用于长序列的信号，其主要缺陷是描述功率谱波动的数字特征方差性能差，频率分辨率低，现代谱估计适用于短序列的信号，旨在改善谱估计的分辨率，并将其应用于实际地震资料的谱分析。 (Power spectrum estimation is the use of a finite length data to estimate the power spectrum of the signal, widely used in various fields. Power spectrum estimation is divided into classic and modern spectral estimation spectral estimation. Commonly used methods of classical periodogram spectrum estimation method, the relevant law, the cycle graph Improvement Act, commonly used in modern spectral estimation methods have maximum entropy spectral estimation, AR model, MA model, ARMA model. Classical spectral estimation applied to signal a long sequence, its main drawback is the fluctuation power spectrum describing digital signature variance performance is poor, the frequency resolution is low, modern spectral estimation applied to signal short sequences designed to improve spectral estimation resolution, and The analysis applied to real seismic data spectrum.)

对井下放炮，地面接收地震资料进行偏移。长测线同样适用。(Underground blasting, ground receiving seismic data offset. Long lines are equally applicable.)

说明：  模式识别及MATLAB实现学习与实验指导 源代码 杨杰 郭志强编(the source code of PATTERN RECOGNITION)

MATLAB遗传算法目前在优化方面已经得到广泛的应用，特别是在比较复杂的优化方面，此文件提供了一个实例供读者参考。(MATLAB genetic algorithm optimization has been now widely used, especially in the more complex optimization, this document provides an example for readers reference.)

求mel频率倒谱系数的matlab程序(for mel frequency cepstrum coefficients of Matlab procedures)