BPSKerr_rate

A hybrid PSO algorithm

勘探地震学 研一课程 二维速度结构的时域有限差分模拟 采用雷克子波(Exploration seismology Kenichi course of the two-dimensional velocity structure using finite difference time domain simulation Ricker wave)

基于负熵最大的独立分量分析，最大似然（ML）准则和最大后验概率（MAP）准则，小波包分析提取振动信号中的特征频率。( Based on negative entropy largest independent component analysis, Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, Wavelet packet analysis to extract vibration signal characteristic frequency.)

该工具箱包括了二种分类,二种回归,以及一种一类支持向量机算法(The toolkit includes two kinds of classification, two kinds of return, and a one-class support vector machine algorithm)

说明：  使用gui编写的计算器功能，与windows上计算器类似(A calculator written in GUI)

matlab 初学者书籍，对初学者有很大的帮助(matlab beginner books, there is a great help for beginners)

语音是人类交换信息的有效渠道之一，也是我们日常生活交流的主要形式。 语音与当今科学技术的快速发展息息相关，特别是计算机中的语音交互技术，通 过对语音信号进行采集和处理，实现人与人之间有效信息的传输、获取以及存储。 基于 MATALAB 的语音信号去噪设计，对噪声信号进行有效地滤除，将降噪后的语音信号与原始 信号在时域和频域进行对比分析，计算出信噪比，并在 MATLAB 中设计 GUI 仿 真界面进行展示.(Speech is one of the effective ways for human to exchange information, and it is also the main form of our daily life communication. Speech is closely related to the rapid development of modern science and technology, especially the voice interaction technology in the computer. Through the acquisition and processing of voice signals, the transmission, acquisition and storage of effective information between people and people is realized. Based on the noise signal de-noising design of MATALAB, the noise signal is effectively filtered, the speech signal and the original signal after the noise reduction are compared and analyzed in the time domain and frequency domain, and the signal to noise ratio is calculated, and the GUI simulation interface is designed in the MATLAB.)

很好的基于支持向量机的MATLAB程序，里面包含有算例及改进算法，以及已经处理好的基于支持向量机的基因数据！(good based on support vector machines MATLAB program, which contains examples and improved algorithm and have a good handle on support vector machines genetic data!)

code for cooperative sensing

说明：  Solving SVM through SMO