Many Approaches for Obtaining Least Noisy Signal using Kaiser Window and Genetic Algorithm

A. Alomari
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Abstract

In a communication system in a signal is an information holding portion which is a route for the system. But this route may not be clean and plane route when data is transmitted from signal there will be some noise is added to the signal and signal turned into a noisy signal, so that is why we want to remove this noise from signal to get information from the signal. In this research, we find some approaches to remove this noise from the signal. These approaches are Wavelet filter based on Butterworth IIR filter and Kaiser Window FIR filter for the analysis of the signal. The newly designed Wavelet filter presents and idea for signal analysis and finding difficulties during any communication. The other techniques are FIR filter that mostly uses for videos. It is somehow valuable technique for filtering signal. This technique uses for complicated purposes like signal preconditioning and various communication application. Most of the FIR filters designing methods is based on Windows method, frequency sampling method and Optimal Sampling method these approaches has been proposed to obtain the clean signal from a noisy signal.
利用Kaiser窗和遗传算法获取最小噪声信号的多种方法
在通信系统中,信号是信息保存部分,它是系统的路由。但是这种路由可能不是干净的,而平面路由从信号中传输数据时,会有一些噪声被添加到信号中,使信号变成有噪声的信号,所以我们要从信号中去除这些噪声,从信号中获取信息。在本研究中,我们找到了一些从信号中去除这种噪声的方法。这些方法是基于小波滤波器的Butterworth IIR滤波器和Kaiser窗FIR滤波器对信号进行分析。新设计的小波滤波器为信号分析和发现通信中的困难提供了一种思路。其他技术是FIR滤波器,主要用于视频。它是一种有价值的信号滤波技术。该技术用于信号预处理和各种通信应用等复杂用途。大多数FIR滤波器的设计方法是基于Windows法、频率采样法和最优采样法,这些方法都是为了从噪声信号中获得干净的信号而提出的。
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