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

Ali Alomari

International Journal of Applied Information Systems
Year of Publication: 2017
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors:Ali Alomari
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  1. Ali Alomari. Many Approaches for Obtaining Least Noisy Signal using Kaiser Window and Genetic Algorithm. International Journal of Applied Information Systems 11(9):22-26, January 2017. URL, DOI BibTeX

    	author = "Ali Alomari",
    	title = "Many Approaches for Obtaining Least Noisy Signal using Kaiser Window and Genetic Algorithm",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "January 2017",
    	volume = 11,
    	number = 9,
    	month = "Jan",
    	year = 2017,
    	issn = "2249-0868",
    	pages = "22-26",
    	numpages = 5,
    	url = "",
    	doi = "10.5120/ijais2017451644",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"


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.


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  12. Table 1 and Figure 1 modified by the author and adapted by Poulami Das, Subhas Chandra Panja, Sudip Kumar Naskar and Sankar Narayan Patra.


DSP, OMRA, FIR digital Filter