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基于LMS(最小均方误差算法)的自适应滤波 基于LMS(最小均方误差算法)的自适应滤波-based on the LMS (MMSE) algorithm based on the LMS adaptive filtering (minimum mean square error algorithm) the adaptive filtering based on the LMS (minimum mean square error algorithm) Adaptive Filter
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基于LMS算法的滤波型算法的源代码，包含有对学习曲线的刻画。迭代后的输出曲线。-LMS algorithm based on the filtering algorithm source code contains the learning curve is given. Iterative the output curve.
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加深对卡尔曼滤波算法的理解，了解卡尔曼滤波器算法的基本特点，掌握卡尔曼滤波算法应用研究的基本步骤和方法-deepen the Kalman filter algorithm understanding, knowledge Kalman Filter algorithm for the basic features, master Kalman filtering algorithm applied research on the basic steps and methods
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加深对卡尔曼滤波算法的理解，了解卡尔曼滤波器算法的基本特点，掌握卡尔曼滤波算法应用研究的基本步骤和方法-deepen the Kalman filter algorithm understanding, knowledge Kalman Filter algorithm for the basic features, master Kalman filtering algorithm applied research on the basic steps and methods
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维娜滤波算法，降噪语音残留音乐噪声很小，可惜失真还是有点大-Wei-na filtering algorithm, noise reduction Voice small residual noise music, but it is somewhat large distortion
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构造一组被噪声污染的方波或三角波数据，试选取适当的FIR滤波器结构和参数，分别应用LMS,DFT/LMS和DCT/LMS算法来实现自适应滤波器，对改组数据进行滤波，并分析仿真结果。-Construction Group was one of the Noise Pollution square or triangular wave data, Examination choose appropriate FIR filter structure and parameters, applicat
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本文将现实中采集到的一段语音加上了高斯白噪声，利用了LMS算法，将噪声滤除，仿真效果良好-This article will be collected in reality a section of voice coupled with a Gaussian white noise, using the LMS algorithm, the noise filtering, simulation results
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本 文 首先 介绍了语音识别的研究和发展状况，然后循着语音识别系统的
处理过程，介绍了语音识别的各个步骤，并对每个步骤可用的几种方法在实
验基础上进行了分析对比。研究了语音信号的预处理和特征参数提取，包括
语音信号的数字化、分帧加窗、预加重滤波、端点检测及时域特征向量和变
换域特征向量.其中端点检测采用双门限法.通过实验比对特征参数的选取，
采用12阶线性预测倒谱系数作为识别参数。详细分析了特定人孤立词识别算
法，选定动态时间弯折为识别算法，并重点介绍其设计实现。
在
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对自适应滤波的工作原理进行了详细的介绍并综述了其算法的应用，对刚刚学习自适应滤波的人有很大帮助。-Work on the principle of adaptive filtering for a detailed introduction and overview of the application of the algorithm, adaptive filter just those who study are very helpful.
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Improved Realization of Speech Enhancement Algorithm Based on Wiener Filtering
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语音增强是影响语音识别系统性能的重要成分。为了比较语音增强算法的性能，采用Matlab软件进行了数值仿真，对不同噪声环境下的语音用3种不同的方法进行降噪，采用信噪比、端点检测等方法来降噪效果，并对几种增强算法的性能进行了比较分析。结果表明，在变噪声环境下短时谱MMSE法最佳，谱减法和维纳滤波法各有优点。-Speech enhancement of voice recognition is an important component of system performance. In order
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运用自适应滤波算法实现的语音增强Matlab程序，附带带噪语音，在M文件中自己修改文件名即可使用-The use of adaptive filtering algorithm for speech enhancement Matlab program, with noisy speech, changes in the M file, the file name to use their own
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卡尔曼滤波程序实现语音增强算法，在Matlab上程序实现了该算法-Program for Kalman filtering speech enhancement algorithm in Matlab program implements the algorithm on
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There are four major types of adaptive filtering configurations adaptive system identification, adaptive noise cancellation, adaptive linear prediction, and adaptive inverse system. All of the above systems are similar in the implementation of the al
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基于麦克风阵列的自适应后滤波算法，适合初学者-After the microphone array-based adaptive filtering algorithm, suitable for beginners
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语音增强算法综述，还可以，基本的谱减法，维纳滤波法都有-Overview of speech enhancement algorithm, can also basic spectral subtraction, Wiener filtering method has
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实现FIR系统中的最小均方误差自适应滤波算法（LMS）,并通过误差曲面研究其性能。-FIR system in the minimum mean square error adaptive filtering algorithm (LMS), and study its performance through the error surface.
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自己编写的维纳滤波的算法，有清楚的注释，基于提取初始寂静噪声的滤波算法。-Wiener filtering algorithm, I have written a clear comment the initial silence noise filtering algorithm based on the extraction.
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matlab实现的传统语音降噪声使用的谱减增强算法，含有维纳滤波算法，请大家参考学习。(Matlab implementation of the traditional voice reduced noise spectrum enhancement algorithm, contains Wiener filtering algorithm, please refer to the study.)
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