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文中研究了6种常用数字调制信号识别的特征参数集，并采用决策树判别方法进行分类识别。仿真结果表明，在SNR≥5dB时，识别正确率在99 以上，且当SNR≥20dB时，识别正确率达到100 。其特点是，算法简单，识别正确率高，达到了自动分类识别的目的，并有利于实现识别的实时化。(In this paper, we study the set of characteristic parameters of the six kinds of commonly used digital modulation signal recognition, and decision tree method for classification. The simulation results show that SNR 鈮� 5dB, the correct rate more than 99 , and when SNR 鈮� 20dB, the correct rate of 100 . Which is characterized by simple algorithm to identify the correct rate, to achieve the purpose of automatic classification and recognition, and help to identify real-time.)

simple voice recognition program

ARMA模型建立程序，给出自相关序列，指定ARMA模型的P阶，Q阶参数，得出相应的参数值 function [bq ,ap]=armahat(rx,p,q)(ARMA model for the establishment of procedures, to come from related sequences, designated the P-order ARMA model, Q-order parameters, the corresponding parameter values derived function [bq, ap] = armahat (rx, p, q))

蓝牙全双工语音和数据传输 蓝牙调制和跳频 蓝牙语音传输的相关程序(Bluetooth full duplex voice and data transfer Bluetooth modulation and frequency hopping Bluetooth voice transmission procedures)

P.863标准（POLQA）,语音质量的客观评测标准，是对P.862标准（PESQ）的升级，适应范围更广，评价结果更接近主观的MOS。(P.863 Standards (POLQA), objective voice quality uation standard is the standard P.862 (PESQ) upgrade, adapt a wider range of uation results closer to the subjective MOS.)

hMM的前向算法 ,详细的的介绍了算法的过程，并又程序的编程说明(hmm the method of hmm )

基于ICA和PCA相结合实现的语音信号的采集、随机混合，再通过盲分离将混合后的语音信号分离(Speech signal acquisition and random mixing based on ICA and PCA, and then the mixed speech signal is separated by blind separation.)

I:CSDN技术中心 进程管理器---一个SDK的例子(I : CSDN Technology Center process management-- for example an SDK)

传统语音增强算法，谱减法和MCRC算法，matlab源代码。(Traditional speech enhancement algorithm, spectral subtraction and MCRC algorithm, matlab source code.)

用三种经典的方法对语音信号进行增强，效果还不错并且三种方法的比较(With three classical methods of speech signal enhancement, the results were good and Comparison of Three Methods)