Frequency Modulation Sound Parameter Identification using Shuffled Particle Swarm Optimization

Abstract

The frequency modulation sound parameter identification is a complex multimodal optimization problem. This problem is modeled in the form of a cost function that is the sum-squared error between the samples of estimated wave and the samples of real wave. In this research, the authors propose a shuffled particle swarm optimization algorithm to solve this problem. In the shuffled particle swam optimization proposed here, population such as shuffled frog leaping algorithm is divided to several memeplexes and each memeplex is improved by the particle swam optimization algorithm. A comparison among the obtained results of the authors' proposed algorithm with the results reported in the literature confirms a better performance of the authors' proposed algorithm.

Quasi-Opposition-Based Learning in a Shuffled Particle Swarm Optimization for Solving Frequency Modulation Sounds Parameter Identification Problem

“…( 2) to approximate the real sound wave given in Eq. ( 3), so as to minimize the sum of squared-error between the samples of measured and the estimated data [10].…”

“…To provide parallel search ability for the PSO, a shuffled PSO (SPSO) was proposed by [10]. The main idea behind of such algorithms is to participate each member in previous experience of all other members.…”

“…( 11) has a better performance than its original version proposed in Eq. (10). Also for second kind of operators, Eq.…”

“…To improve performance of the original PSO, various concepts have been proposed in the literature. On of these concepts is shuffled PSO (SPSO) [10] which provides a parallel search ability for the pure PSO algorithm. The SPSO partitions the population into several parallel subsets and then these subsets perform a local search independently using a PSO algorithm.…”

Optimisation of electric distribution systems: A review

“…In [114], a modified version of shuffled frog leaping algorithm (SFLA) [115] has been used for optimising total cost of distribution systems in the presence of DG units. Status of sectionalising and tie switches, location and size of DG units are found in a way that the considered objective is minimised.…”