Welch

Function Toolbox hope u like it

我初次接触到压缩方法实验的JPEG压缩算法源代码，用matlab编写的，欢迎探讨(I first exposure to the experimental compression JPEG compression algorithm source code, prepared by the use of Matlab, welcome to explore)

matlab code for Hilbert-Huang Transform

这是nmflab的操作指导书，可以当成一个工具箱添加到matlab中，其中包含nmf几种经典的算法，很有指导意义！(This is the operating instructions nmflab can be added as a toolbox to matlab, which contains nmf several classic algorithms, is very instructive!)

keep useful variables in the matlab workspace

在复杂网络中，求经典的无标度网络最短路径算法的matlab源程序非常的实用。(In complex networks, and the classical scale-free network shortest path algorithm matlab source code is very practical.)

文件名：C-C法计算时间延迟和嵌入维数 C-C法计算出相空间重构的时间延迟和嵌入维数 文件名：dingyi_lyapunov 采用定义法计算lyapunov指数 文件名：fencha 求lorenz系统分岔图（采用区域最大值法） 文件名：m_test 求解嵌入维数m 文件名：pinghengdian 求lorenz系统在某一系数下的平衡点，并求出特征值 文件名：poincare 求lorenz系统的poincare截面 文件名：PSD 求lorenz系统的功率谱 文件名：tau_test 相空间重构时间延迟求解 文件名：time_test lorenz系统时域分析，相平面图 文件名：wolf_lyapunov wolf法求解lyapunov指数（需要配合求解m和嵌入时间延迟t使用） 文件名：xiao_shuju 小数据量法求解lyapunov指数 文件名：zheng_jiao 正交法求lyapunov指数谱(choastic time series analysis)

语音识别技术的最终目标是要让计算机能与人自由交谈。目前，连续语音识别技术正趋于成熟，语音识别也延伸出了诸多实用化的研究方向。今后，语音识别的重点将集中在自然话语识别与理解、实时语音识别和语音识别鲁棒性等方面。作为一门交叉学科，语音识别所涉及到的技术有信号处理、模式识别、概率论和信息论、发声机理、听觉机理和人工智能等。(The ultimate goal of speech recognition technology is to make computers and allowing others to speak freely. At present, continuous speech recognition technology is maturing, voice recognition is also extended out a lot of practical research directions. In the future, speech recognition will focus on Spontaneous Speech Recognition and Understanding, real-time speech recognition and speech recognition robustness and so on. As an interdisciplinary subject, speech recognition technology involved in a signal processing, pattern recognition, probability theory and information theory, vocal mechanism, hearing mechanism and artificial intelligence.)

M/M/1单服务台或M/M/S(n)排队系统仿真 （用事件调度法实现离散事件系统仿真） (M/M/1 single desk or M/M/S (n) Queuing System Simulation (Event Scheduling Method using Discrete Event System Simulation))

This folder or any similar folder such as this created to hold your speech files, should be copied into the root folder C: , created on the local hard drive. Then the path will read thus C:SpeechDataTope... etc. An alternative is to modify the file setTemplates.m to change the directory as appropriate. Try to use the same microphone for training as well as for recognition to obtain improved accuracy. You might also need to tweak your sound card s mic input level. The recognition time is dependent on systems s processing power and has been observed at between 1 and 5 seconds on various x86 platforms. To speed up recognition, you can implement unconstrained DTW (this is the code portion taking most time).