fixedbeam

这 里主要对LMS算法及一些改进的LMS算法（NLMS算法、变步长LMS算法、变换域LMS算法）之间的不同点进行了比较，，在传统的LMS算法的基础上发 展了LMS算法的应用。另一方面又从RLS算法的分析析中对其与LMS算法的不同特性进行了比较。 (Here the main difference between the LMS algorithm and improved LMS algorithm (NLMS algorithm, variable step size LMS algorithm, the transform domain LMS algorithm) comparison, the traditional LMS algorithm based on the development of the application of the LMS algorithm . On the other hand and from its different characteristics of the LMS algorithm of the analytical analysis of the RLS algorithm.)

程序功能可以基本上实现基于C语言的G.729A语音算法的解码功能，添加了部分本人的注释和理解，便于读者理解(Program features can basically C language-based decoding algorithm G.729A voice, add some of my notes and understanding, easier to understand)

4基于稀疏编码的语音增强方法.pdf (4 sparse coding speech enhancement based on 4 sparse coding speech enhancement method based on.Pdf.Pdf method)

基音提取并换算成音高,matlab程序，加入了优化的功能使得结果更好(Pitch extraction and converted into pitch, matlab program, joined the optimization of the function of making the results better)

利用自适应滤波器对心音信号进行预测，包括了LMS算法，归一化LMS，变步长LMS和RLS算法，其中RLS的预测效果最好.(Heart sound signals using adaptive filter to predict, including the LMS algorithm, the normalized LMS, variable step size LMS and RLS algorithm, in which the best forecast of RLS.)

关于lms经典算法汇总，包括lms,nlms,LMS_Equalizer,Basic_LMS,LMS toolbox等等。(classical algorithm for matrix lms, including lms, nlms. LMS_Equalizer, Basic_LMS, LMS toolbox, and so on.)

LBG-vector quantization algorithm

短时自相关和短时平均幅度差计算基音周期的matlab程序，附带有原语音信号(Short-term autocorrelation and short-term average deviation of pitch period matlab program, comes with the original speech signal)

验证码识别简化源码程序,结合易语言位图操作支持库和应用接口支持库，实现验证码图像的识别简化。(Verification code identifying the source simplify procedures , combined with easy language bitmap operations support libraries and application interface support library that implements a simplified identification verification code image .)

基于VQ的说话人识别系统，在MATLAB环境下实现基于矢量量化的说话人识别系统。在实时录音的情况下，利用该说话人识别系统，对不同的人的1s～7s的语音进行辨识。实现与文本无关的自动说话人确认的实时识别。(speaker recognition system based on vector quantization)