Design of 1-D and 2-D recursive filters using crossover bacterial foraging and Cuckoo search techniques

• The evolutionary filter design technique is proposed for 2-D recursive filters.
• COBFO and CS algorithms are used to optimize filter parameters.
• Constraint handling and repair is incorporated to ensure stability.
• Optimal values for filter parameters are obtained.
• The proposed method provides stability and outperforms other methods.

Recently, there has been an increasing interest on the application of the evolutionary algorithms in order to solve the drawbacks of traditional filter design methods. Unlike classical methods, they offer the advantage of not requiring a good initial estimate of filter parameters to proceed. This paper presents design of one-dimensional (1-D) and two-dimensional (2-D) recursive filters using crossover bacterial foraging (COBFO) and Cuckoo Search (CS) techniques. Design of 1-D and 2-D recursive filters is considered here as a constrained optimization problem to ensure stability. The solution is obtained through convergence of a biased random search using crossover bacterial foraging optimization technique to ensure quality. A faster solution is also obtained through the convergence of a meta heuristic search technique called the Cuckoo search technique. Inbuilt constraint handling capability makes our proposal attractive in the design of recursive filters. Results are compared with genetic algorithm (GA) and bacteria foraging optimization (BFO) techniques.