Abstract
The particle velocity and position updating plays
very important role for achieving good optimization
performance for Particle Swarm Optimization (PSO). This
paper analyzed the performance of asynchronously updating
PSO and synchronously updating PSO by simulation and
found that the asynchronously updating way can achieve
better optimization performance than the synchronously
updating way. Moreover, the convergence of asynchronously
PSO is faster than the synchronously PSO, which means there
is spare time to achieve better optimization performance based
on some techniques. Here we proposed stochastic dimension
updating technique which means only some dimensions of
position will be updated. Several benchmark functions have
been used to validate the proposed method and the proposed
method is also applied to the parameter estimation for
frequency modulated Sound Waves.