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Many Approaches for Obtaining Least Noisy Signal using Kaiser Window and Genetic Algorithm
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 11 - Number 9 |
| Year of Publication: 2017 |
| Authors: Ali Alomari |
10.5120/ijais2017451644
|
Ali Alomari . Many Approaches for Obtaining Least Noisy Signal using Kaiser Window and Genetic Algorithm. International Journal of Applied Information Systems. 11, 9 ( Jan 2017), 22-26. DOI=10.5120/ijais2017451644
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.
References
- Mahesh S.Chavan, R.A.Aggarwala, M.D.Uplane, ‘Interference reduction in ECG using digital FIR filters based on Rectangular window,' WSEAS Transactions on Signal Processing, Issue 5, Volume 4, May 2008, pp.340-49.
- L.R.Rabiner and B.Gold, Theory and Application of Digital Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1975.
- Alyson K. Fletcher, Vivek K Goyal and Kannan Ramchandran, 2003. "Iterative Projective Wavelet Methods for Denoising," Proc.Wavelets X, part of the 2003 SPIE Int. Symp. On Optical Science & Technology, Vol. 5207, pp: 9-15, San Diego, CA August.
- C. K. Chui, “An Introduction to Wavelets,” Wavelet Analysis and Its Application, Vol I, Academic Press, Inc., 1992
- Major Joseph 0. Chapa, “Constructing Wavelets from Desired Signal Functions” Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623, USA.
- https://en.wikipedia.org/wiki/Digital_filter.
- J. Barros, ?On the Use of the Hanning window for harmonic analysis in the standard framework?, IEEE Transactions on Power Delivery, 2006.
- http://www.cs.utexas.edu/~mooney/cs343/slide-handouts/heuristic-search.4.pdf Sharma, S. 2009. Book on Digital Signal Processing (with Matlab Programs)
- Ye, W.B., Yu, Y.J., H. Zhao.et.al. 2013. Sparse FIR Filter Design Based on Genetic Algorithm, In Proceedings of International Symposium on Circuits and Systems.
- Claudia Schremmer, Thomas Haenselmann and Florian Bomers, 2001. "A Wavelet Based Audio Denoiser," In Proc.
- Awad, A.M. 2010. Adaptive Window Method for FIR Filter Design, In Proceedings of IEEE Conference on Open Systems (ICOS).
- Table 1 and Figure 1 modified by the author and adapted by Poulami Das, Subhas Chandra Panja, Sudip Kumar Naskar and Sankar Narayan Patra.
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