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首页> 外文期刊>Asian Journal of Information Technology >Performance Comparison of Adaptive Algorithms with Improved Adaptive Filter Based Algorithm for Speech Signals
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Performance Comparison of Adaptive Algorithms with Improved Adaptive Filter Based Algorithm for Speech Signals

机译：自适应算法与改进的基于自适应滤波器的语音信号性能比较

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摘要

Noise cancellation is a technique applied to offset the interference in the signals. Noise Cancellation finds a pile of applications like mobile telephones, hearing aids bluetooth receivers and more. It is difficult to find out any signal, especially speech signal in a noisy environment.An adaptive filter plays a lively role in cancelling the noise in the speech signal. Adaptive filters use several algorithms for scaling down the interferences in the signal. Thus an improved Adaptive filter based Noise cancellation for speech signals approach named Variable Step Size Normalized Differential LMS (VSSNDLMS) Algorithm that incorporates the performance and features of Variable Step Size LMS (VSSLMS) and Normalized Differential LMS (NDLMS) is offered. It is to analyze and compare the performance of the proposed VSSNDLMS Algorithm with various Least Mean Square adaptive algorithms. This algorithm aims in applying the proposed algorithm for various real time applications like auditorium, automobile, seminar hall, etc. The analysis indicates that the proposed adaptive algorithm has fast convergence rate, tracking ability, reduced Mean Square Error (MSE) and maladjustments which is the required characteristics of an adaptive filter. For performance, analysis different input speech signals and sound signal are analyzed. The simulation results show that the proposed VSSNDLMS algorithm converges fast with Minimum MSE and is useful in anticipating the performance of adaptive filters.
机译：噪声消除是一种用于抵消信号中干扰的技术。降噪技术在移动电话，助听器，蓝牙接收器等领域都有大量应用。很难找到任何信号，特别是在嘈杂的环境中的语音信号。自适应滤波器在消除语音信号中的噪声方面起着积极的作用。自适应滤波器使用多种算法来减小信号中的干扰。因此，提供了一种改进的基于自适应滤波器的语音信号噪声消除方法，称为可变步长归一化差分LMS（VSSNDLMS）算法，该算法结合了可变步长LMS（VSSLMS）和归一化差分LMS（NDLMS）的性能和特征。将分析和比较所提出的VSSNDLMS算法与各种最小均方自适应算法的性能。该算法旨在将所提出的算法应用于礼堂，汽车，研讨厅等各种实时应用。分析表明，所提出的自适应算法具有收敛速度快，跟踪能力强，均方误差（MSE）降低和失调的特点。自适应滤波器的所需特性。为了性能，分析了不同的输入语音信号和声音信号。仿真结果表明，所提出的VSSNDLMS算法与最小MSE算法快速收敛，可用于预测自适应滤波器的性能。

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