Email this article 
Open Access
Subscription or Fee Access
Simulated Annealing for Optimal IIR Digital Filters
Abstract
In this paper, Simulated Annealing (SA) in the context
of designing infinite-impulse response (IIR) digital filters is presented. IIR filter is essentially a digital filter with Recursive responses. Since the error surface of digital IIR filters is generally nonlinear and multimodal, global optimization techniques are required in order to avoid local minima. This Paper presents heuristic way for the designing IIR filters. SA is a powerful global optimization algorithm introduced in combinatorial optimization problems. The paper finds
the optimum Coefficients of IIR digital filter through SA. It is found that the calculated values are more optimal than fda tool availble for the design of filter in MATLAB. Design of Lowpass and High pass IIR digital filter is proposed to provide estimate of transition band. The simulation results of the employed examples shows an improvement
on transition band. Better mean-square-error equal to 0.3284 is achieved using SA. The position of the Pole-Zero is also presented to describe the stability of designed filters.
Keywords
References
J. G. Proakis and D. G. Manolakis, “Digital Signal Processing: Principles,
Algorithms, and Applications”, 4th Edition, Pearson Education, Inc, New
Delhi, 2007.
Joelle Skaf and P. Boyd Stephen, “Filter Design with Low Complexity
Coefficients,” IEEE Transactions on Signal processing, vol. 56, no. 7, pp.
-3170, July 2008.
Richard J. Vaccaro and Brian F. Harrison, “Optimal Matrix-Filter
Design,” IEEE Transactions on Signal processing, vol. 44, no. 3, pp.
-710, March 1996.
Xi Zhang and Hiroshi Iwakura, “Design of IIR Digital Filters based on
Eigen value Problem,” IEEE Transactions on Signal processing, vol. 44,
no. 6, pp. 1325-1319, June 1996.
Fabrizio Argenti and Enrico Del Re, “Design of IIR Eigen filters in the
Frequency domain,” IEEE Transactions on Signal processing, vol. 46, no.
, pp. 1694-1700, June 1998.
Xin Yao, Yong Liu, and Guangming Lin, "Evolutionary Programming
Made Faster," IEEE Transaction on Evolutionary Computation, vol. 3,
no. 2, pp. 83-102, July 1999.
R.S.Chauhan and A.Kamboj, “MATLAB based Design of Digital FIR
filter using window technique,” in IEEE Conf. on Art. Int. Systems (AIS),
Sonipat, India, 2007, pp. 208-210.
R.V. Kacelenga, P.V. Graumann, and L.E. Turner, “Design of filters
using simulated annealing,” in IEEE Proc. Int. Symp. on Circuits and
Systems , New Orleans, LA, 1990, pp. 642-645.
N. Benvenuto and M.Marchesi, “Applications of simulated annealing for
the design of digital filters,” IEEE Transaction Signal Processing, vol. 40,
no.2, pp 323-331,1992.
K.D.Abdesselam, “Design of Stable, causal, perfect reconstruction, IIR
Uniform DFT Filters,” IEEE Transactions on Signal processing, vol. 48,
no. 4, pp. 1110-1117, 2000.
C.C. Tseng and S.C. Pei, “Stable IIR Notch Filter design with optimal
pole placement,” IEEE Transactions on Signal processing, vol. 49, no. 11,
pp. 2673-2681, 2001.
J.E. Cousseau, Stefan Werner, and P.D. Donate, “Factorized All-Pass
Based IIR Adaptive Notch Filters” IEEE Transaction on Signal
Processing, vol.55, no. 11, pp. 5225-5236, 2007.
H.A.Oliveira, Antonio Petraglia, and M.R.Petraglia, “Frequency Domain
FIR Filter Design Using Fuzzy Adaptive Simulated Annealing,” in IEEE
International Symposium on Signal Processing and Information
Technology, pp. 884-888.
B.W.Jung, H.J.Yang, and J.Chun, “Finite Word length Digital Filter
Design Using Simulated Annealing,” IEEE Transaction Signal
Processing, pp.546-550, 2008.
R.S.Chauhan and Sandeep K. Arya, “Design of IIR digital filter using
analog to digital mapping”, Journal of Neural Computing Systems, vol. 3,
no. 1, pp. 51-55, 2010.
Chaohua Dai, Weirong Chen, and Yunfang Zhu, “Seeker Optimization
Algorithm for Digital IIR Filter Design,” IEEE Transaction on
Evolutionary Computation, vol. 57, no. 5, pp. 1710-1718, 2010.
Qi. Ji. Yang, “Application of Improved Simulated Annealing Algorithm
in Facility Layout Design,” in Proceedings of the 29th Chinese Control
Conference, Beijing, China, 2010, pp. 5224-5229.
Kevin I. Smith, Richard M. Everson, Jonathan E. Fieldsend, Murphy
Chris, and Rashmi Misra, “Dominance-Based Multiobjective Simulated
Annealing” IEEE Transaction on Evolutionary Computation, vol. 12, no.
, pp.323-343, June 2008.
Soyeon Ahn, Lee Heedeok, and Jung Byungwook, “Medium PRF set
selection for pulsed Doppler radars using simulated annealing” IEEE, pp.
-95, 2011.
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.