Simulated-annealing-based optimization of coefficient and data word-lengths in digital filters

1988 ◽  
Vol 16 (4) ◽  
pp. 371-390 ◽  
Author(s):  
Francky Catthoor ◽  
Hugo de Man ◽  
Joos Vandewalle
1992 ◽  
Vol 40 (2) ◽  
pp. 323-332 ◽  
Author(s):  
N. Benvenuto ◽  
M. Marchesi ◽  
A. Uncini

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Supriya Dhabal ◽  
Palaniandavar Venkateswaran

We present a novel hybrid algorithm based on particle swarm optimization (PSO) and simulated annealing (SA) for the design of two-dimensional recursive digital filters. The proposed method, known as SA-PSO, integrates the global search ability of PSO with the local search ability of SA and offsets the weakness of each other. The acceptance criterion of Metropolis is included in the basic algorithm of PSO to increase the swarm’s diversity by accepting sometimes weaker solutions also. The experimental results reveal that the performance of the optimal filter designed by the proposed SA-PSO method is improved. Further, the convergence behavior as well as optimization accuracy of proposed method has been improved significantly and computational time is also reduced. In addition, the proposed SA-PSO method also produces the best optimal solution with lower mean and variance which indicates that the algorithm can be used more efficiently in realizing two-dimensional digital filters.


Author(s):  
R.V. Kacelenga ◽  
P.J. Graumann ◽  
L.E. Turner

1989 ◽  
Vol 36 (3) ◽  
pp. 459-460 ◽  
Author(s):  
N. Benvenuto ◽  
M. Marchesi

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