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quality. To improve the audio quality, several authors have developed acoustic echo cancellers based
on particle swarm optimization algorithms (PSO). However, its performance is reduced significantly
since the PSO algorithm suffers from premature convergence. To [...] Read more.
quality. To improve the audio quality, several authors have developed acoustic echo cancellers based
on particle swarm optimization algorithms (PSO). However, its performance is reduced significantly
since the PSO algorithm suffers from premature convergence. To overcome this issue, we propose a
new variant of the PSO algorithm based on the Markovian switching technique. Furthermore, the
proposed algorithm has a mechanism to dynamically adjust the population size over the filtering
process. In this way, the proposed algorithm exhibits great performance by reducing its computational
cost significantly. To adequately implement the proposed algorithm in a Stratix IV GX EP4SGX530
FPGA, we present for the first time, the development of a parallel metaheuristic processor, in which
each processing core simulates the different number of particles by using the time-multiplexing
technique. In this way, the variation of the size of the population can be effective. Therefore,
the properties of the proposed algorithm along with the proposed parallel hardware architecture
potentially allow the development of high-performance acoustic echo canceller (AEC) systems Full article
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