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

作者：Sarangi Shubhendu Kumar; Panda Rutuparna^*; Dash Manoranjan

来源：Engineering Applications of Artificial Intelligence, 2014, 34: 109-121.

DOI：10.1016/j.engappai.2014.05.010

• Multidimensional systems
• Recursive filters
• Constrained optimization
• Cuckoo search algorithm
• Genetic algorithm
• Bacteria foraging optimization

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.

• 出版日期2014-9