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信息融合方面得例题，对已知要求的目标，利用动态矩阵控制（DMC）使其达到期望值。所有程序均已通过调试。希望对大家有所帮助(Example of information integration have on the known requirements of the target, the use of Dynamic Matrix Control (DMC) to reach the expectations. All have been through the debugging process. I hope all of you to help)

简单语音识别源码是一个调用讯飞语音识别SDK的例子源码是一个最纯净的Demo比较容易看懂。实现的是点击按钮开始语音监听，手机需要联网，2/3G的均可，识别后会以Toast的方式提示出来，识别率还是比较高的。之前自己是用别人的Demo总是不成功，是因为，讯飞的SDK想使用是需要APPID的，可能过太长时间久会注销，还有，未通过审核的APPID每天只能试用500次，如果太多人试用，就是达到上限导致无法使用。(A simple speech recognition source code is a call Ifly speech recognition SDK example source code is a demo of the purest easier to understand. The realization of the click button to start the voice listening, mobile phone need to networking, 2/3G can, after the recognition will be prompted by Toast way out, the recognition rate is still relatively high. Before he is with someone else s demo is not always successful, is because the Xunfei SDK to use is appid, may be too long for a long time will be canceled, and not through the audit appid every day can only be tried out 500 times, if too many people tried is reaching the limit to use.)

主要是研究光纤通信系统中的克服PMD效应的电域均衡技术，构建电域均衡器的模型并进行仿真实验。找到补偿PMD效应的较理想的电域均衡器结构。(Is to study, fiber-optic communication systems to overcome the effects of PMD electrical domain equalization technology, building a power domain equalizer model and simulation experiments. PMD compensation effect to find a better balance of power domain structure.)

在matlab平台利用GUI界面实现录音，播放。并对语音信号进行频谱分析，特定人语音识别，混响，混频等基础功能。(On the MATLAB platform, the GUI interface is used to record and play. And the speech signal spectrum analysis, specific speech recognition, reverberation, mixing and other basic functions.)

光伏孤岛检测经典移相法，移频法，还有被动识别法的仿真(PV islanding detection classical phase shift method, the shift frequency, as well as passive identification method simulation)

语音信号的录音、读入、放音等：利用函数wavread对语音信号进行采样,记住采样频率和采样点数，给出以下语音的波形图（2.wav），wavread的用法参见mablab帮助文件。利用wavplay或soundview放音。也可以利用wavrecord自己录制一段语音，并进行以上操作(需要话筒)。 (Speech signal recording, reading, playback, etc.: the voice signal using the function wavread sampling, sampling frequency and sampling points to remember, given the following speech waveform (2.wav), wavread usage see mablab help file. Using wavplay or soundview playback. Can also record a voice using wavrecord own, and the above operation (requires microphone).)

国外著名的语音合成开发教程。英文的，原汁原味。(famous speech synthesis Development Guide. English, what is genuine.)

3、语音特征提取与分类 首先, 待识别语音转化为电信号后输入识别系统, 经过预处理后用数学方法提取语音特征信号, 提取出的语音特征信号可以看成该段语音的模式。(3, the voice feature extraction and classification First, to be recognized voice into electrical signals input recognition system, after pretreatment with a mathematical method to extract speech characteristic signal extracted speech characteristic signal can be seen as the voice segment model.)

基于MFCC的利用LPCC做的说话人识别论文(Based on the MFCC the use of LPCC do the speaker identification papers)

Chapter 2 Low Bit-Rate Speech Coding In this chapter an overview is given of speech coding techniques at several bit rates. Most of them use Linear Prediction. This overview is not meant to be complete its purpose is to make the reader somewhat familiar with Linear Predictive Coding which is necessary for a proper understanding of later chapters. Section 2.1 treats the subject of quantisation and coding. In section 2.2 a description of speech production and speech sounds is given. Coders based on linear prediction can be considered as being based on a simple speech production model. This model is explained in section 2.3. Section 2.4 describes various speech coding algorithms and techniques. Section 2.5 briefly describes some measures for the quality of coded speech.(In this chapter an overview is given of speech coding techniques at several bit rates. Most of them use Linear Prediction. This overview is not meant to be complete its purpose is to make the reader somewhat familiar with Linear Predictive Coding which is necessary for a proper understanding of later chapters. Section 2.1 treats the subject of quantisation and coding. In section 2.2 a description of speech production and speech sounds is given. Coders based on linear prediction can be considered as being based on a simple speech production model. This model is explained in section 2.3. Section 2.4 describes various speech coding algorithms and techniques. Section 2.5 briefly describes some measures for the quality of coded speech.)