Parameter identification of two dimensional digital filters using electro-magnetism optimization
The design of Two-Dimensional Infinite Input Response Filters (2D IIR) is an important task in the field of signal processing. These filters are widely used in several areas of engineering as an important tool to eliminate undesired frequencies in high-noised signals. However, 2D IIR filters have parameters that need to be calibrated in order to obtain the best output, and finding these optimal values is not an easy task. On the other hand, Electro-magnetism Optimization (EMO) is a population-based technique which possess interesting convergence properties, it works following the electro-magnetism principles for solving complex optimization problems. This paper introduces an algorithm for the automatic parameter identification of 2D IIR filters using EMO, a process that is regarded as a multidimensional optimization problem. Experimental results are included to validate the efficiency of the proposed technique regarding accuracy, speed, and robustness.
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