Технічна інженерія (Jun 2024)
Method for optimization of FIR filter characteristics using the whale optimization algorithm
Abstract
The article discusses the analysis of the whale optimization algorithm with the aim of applying it to optimize the coefficients of digital filters with linear phase. Digital filters play an important role in signal processing, which are used in many tasks: control and measurement systems, audio and video processing systems, noise reduction tasks, etc. FIR filters are more preferable for some tasks than others because they have the following advantages: the group delay of the filter is constant; FIR filters are always stable. Nowadays, algorithms based on swarm intelligence are widely used. In the theory of artificial intelligence, these algorithms are considered as optimization methods. The existing methods for solving the problem are analyzed. The whale optimization algorithm has appeared recently. This algorithm has advantages over other algorithms: it does not require information about the gradient; it can bypass local optima; it can be used in a wide range of problems. On the basis of this algorithm, a method for optimizing the characteristics of FIR filters has been developed. The root mean square deviation between the amplitude-frequency response of the prototype and the amplitude-frequency response of the FIR filter to be designed is used as a fitness function. The modeling was carried out on the example of a 24th-order FIR filter of the first type using the Python programming language. The simulation results showed the effectiveness of this algorithm for the synthesis of FIR filters. This method can be successfully used in the design of FIR filters with a linear phase in the creation of various technical means. However, it should be noted that the efficiency of the whale optimization algorithm is lower than the genetic algorithm by almost an order of magnitude in time. Also, the disadvantages include the need to set the boundaries of the search space.
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