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Efficient Spectral Analysis Through Effective Reduction of Adjacent Channel Interference in Multirate Processing
Ganekanti Hemanja, K. Satya Prasad, P. Venkata Subbaiah
Pages - 1 - 21     |    Revised - 15-01-2012     |    Published - 21-02-2012
Volume - 6   Issue - 1    |    Publication Date - February 2012  Table of Contents
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KEYWORDS
Multirate Processing, Bandpass filtering, Decimation, Modified Kaiser window, Net input samples, Spectral output
ABSTRACT
Spectral analysis is considered to be important area of consideration in which the volume reconstruction and visualization takes place, besides amounting to increase in computational efficiency. The reception of selected frequency and amplitude level takes an important role for further processing at the succeeding stages of Digital Signal Processing. The number of developments are undertaken through research work for effective reception of signals. In this paper, the proposed method is based on Multirate technique, specified by authors[1][2], in Finite Impulse Response digital filter bank through Modified Kaiser window, subsequently followed by Fast fourier transform. A remarkable spectral output is achieved by way of increase in magnitude, linear phase response, constant width and sharp rise of response, less adjacent channel interference and better stopband attenuation as compared to authors of [3][4][5][6] besides significant improvement of specific parameters listed among by respective methods are elited. In addition, a better reduction in computational complexity is achieved. This method of spectral analysis is suitable in most of applications, especially in digital hearing aid applications as it is compatible with low frequency, low delay and low power requirements. The simulation results are added on account of satisfactory performance and comparison is drawn to enlighten the advantages in the proposed method.
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1 R.E. Crochiere, I.R. Rabiner. “Multirate Digital Signal Processing”. Prentice-Hall Inc., 1983.
2 Douglas F. Elliot. “A Hand book of Digital Signal Processing”. Academic press, 1987.
3 Robert W Bauml, Wolfgang sorgel. “Uniform polyphase filter banks for use in hearing aids: Design and Constraints”. 16th European Signal Processing Conference (EUSIPCO-2008).
4 Aditya Goel. “Design of multichannel filter banks for subband coding of audio signals for multirate signal processing techniques”. SPIE publications, 2007.
5 Jovanovic-Dolecek G. “Multirate Systems: Design and Application”. Idea Group Publishers, 2002.
6 Robert Brennum, Todd Schneider. “A flexible filter bank structure for Extensive signal manipulations in Digital hearing aids”. O-7803-4455-3/98/5 10:00(c),IEEE, 1998.
7 Ricky Setiawan, Victor Putra Lesmana, Bah-Hwee-Gwee. “Design and Implementation of a low power FIR filter bank”. Journal of The institution of Engineers, Singapore, Vol. 45, Issue 5, 2005.
8 David J. Defatta, Joseph C. Lucas, William S. Hodgkiss. “Digital Signal Processing : A System Design Approach”. John Wiley and Sons, 1988.
9 T. Schmeider, R.L. Brennan. “A Multichannel Compression Strategy for a Digital hearing Aid”. proc, IC ASSP-97, Munich Germany, pp. 411-415.
10 D.Y. Pan. “A Tutorial on MPEG Audio Compression”. IEEE Multimedia Magazine Summer, pp. 60-74, 1995.
11 Behrouz Farhang – Boroujeny, Chung Him (George) Yuen.”Cosine Modulated and Offset QAM Filter bank Multicarrier techniques: A Continuous – Time Prospect”. EURASIP Journal on Advances in Signal Processing Volume 2010, Article ID 165654, 2010.
Mr. Ganekanti Hemanja
S.V. Government Polytechnic - India
ganekantihemanj@yahoo.com
Dr. K. Satya Prasad
J.N.T. University - India
Dr. P. Venkata Subbaiah
Amrita Sai institute of Science and Technology - India