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Noise removal is an underlying issue of image processing. This paper proposes a generic approach to design an optimal filter which combines linear and morphological filtering techniques, so that both Gaussian and non-Gaussian noise can be rejected. The optimisation process is performed by a bacterial swarming algorithm (BSA), which is derived from the bacterial foraging algorithm (BFA) and involves...
This paper presents a dynamic bacterial swarming algorithm (DBSA) for harmonic estimation in dynamic environment. DBSA is designed from a dynamic searching framework that combines the underlying mechanisms of bacterial chemotaxis, quorum sensing and environment adaptation. The harmonic estimation process utilizes DBSA to estimate the phases of the harmonics, alongside a least square (LS) method to...
This paper presents a new algorithm for harmonic estimation. It utilizes the particle swarm optimizer with passive congregation (PSOPC) to estimate the phases of the harmonics, alongside a least-square (LS) method that is used to estimate the amplitudes. The PSOPC and LS method are executed alternately to minimize the error between the original signal and the signal reconstructed from the estimated...
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