The week's pick
Reseach Article
Interpolated Finite Impulse Response (IFIR) Filter Approach: A Case Study
| National Conference on Advanced Computing and Communications 2012 |
| Foundation of Computer Science USA |
| NCACC - Number 1 |
| August 2012 |
| Authors: B N Jagadale |
| f6baa3f6-832c-4307-89da-9c3b37df9f5d |
B N Jagadale . Interpolated Finite Impulse Response (IFIR) Filter Approach: A Case Study. National Conference on Advanced Computing and Communications 2012. NCACC, 1 (August 2012), 43-45.
Abstract
The finite impulse response filters are inherently stable and have linear phase response property. The main drawback of these filters is lies in requirement of higher orders for similar magnitude response compared to Infinite Impulse response filters. Also the amount of computational complexity needed for the implementation of the filter, especially for the filters with narrow transition band is much higher. In order reduce the computational complexity of narrowband FIR filters, the interpolated FIR (IFIR) filter technique is used.
References
- Oppenheim A. V. , and Schafer, R. W, 1989. Discrete-Time Signal Processing. Prentice-Hall, Englewood Cliffs, NJ
- Proakis, J. G, Rader, C. M, Ling, F. and Nikias. C. L, 1992. Advanced Signal Processing. Macmillan, New York.
- Tan, L. 2000. Digital signal processing, Academic press, UK.
- Mitra, S. K, 2001. Digital Signal Processing, Tata-McGraw Hill, New Delhi.
- Rabiner, L. R. and Gold, B 1975. . Theory and Applications of Digital Processing. Prentice- Hall, Englewood Cliffs, NJ.
- Neuvo, Y. , Dong C. Y, and Mitra, S. K. 1984. Interpolated Finite impulse response filters. IEEE Trans. Acoust. , Speech, Signal Processing, vol. ASSP-32,pp. 563-570.
- Lyons, R. 2003. Interpolated narrow and lowpass FIR filters. IEEE Signal Process. Mag. , pp. 50-57. .
- Haykin. S, 1991 Adaptive Filter Theory. Prentice - Hall, Englewood Cliffs, NJ.
- Vaidyanathan, P. P . 1993. Multirate Systems and Filter Banks Prentice - Hall Signal Processing Series
- Mitra,S. K. 2006. Digital Signal Processing: A Computer-Based Approach, New York, NY: McGraw Hill pp. 427- 578.
- McClellan, J. H. , Parks, T. W. and Rabiner, L. R. 1973. A Computer program for designing optimum FIR linear phase digital filters. IEEE Trans. Audio Electroacoust. , Vol. AU 21, pp. 506-52.
- Bartolo, A. Clymer, B. D. Burges, R. C. and Turnbull, J. P. 1998 An efficient method for FIR filtering based on impulse Response rounding. IEEE Trans. On Signal Processing Vol. 46 No. 8, pp. 2243-2248.
- Kaiser, J. Hamming, R. 1977. Sharpening the response of a Symmetric nonrecursive filter by multiple use of the same filter IEEE Trans. Acoust. , Speech, Signal Process. , vol. ASSP-25 no. 5, pp. 415-422,
- Mann , D. A. 2008. Interpolated FIR (IFIR) Filters: A case Study. IEEE Transactions.
- Saramaki, T. Neuvo, Y. and Mitra, S. K. 1988 "Design of Computationally efficient interpolated FIR filters," IEEE Trans. Circuits Syst. , vol. CAS-35, pp. 70-88.
- Webb, J. L. , Munson. D. 1996. "A new approach to designing Computationally efficient interpolated FIR filters" IEEE Trans. Signal Processing, vol. 44, pp. 1923-1931.
- Mehrnia, A. Willson, J. A. 2004. On optimal IFIR filter design IEEE Proceedings of the 2004 International Symposium on Circuits and Systems, vol. 3, pp. 133-13.
- Jovanovic-Dolecek, G. Mitra, S. K 2005. Multiplier-free FIR filter design based on IFIR structure and rounding," IEEE 48th Midwest Symposium on Circuits and Systems. , vol. 1, pp. 559-562.
Index Terms
Keywords