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A method for minimax design of linear phase finite impulse response (FIR) digital filters using cuckoo search algorithm (CSA) is presented. Lowpass and bandpass digital filters are used as filter examples. Equiripple linear phase FIR digital filter design results indicate that the peak errors in passband and stopband(s) obtained using the cuckoo search algorithm are similar to those obtained by the...
Artificial bee colony (ABC) algorithm is a swarm based meta-heuristic algorithm inspired by the foraging behavior of honey bees. Due to its simplicity, the ABC algorithm is used for minimax design of linear phase FIR fullband digital differentiators in this paper. Results in term of peak error obtained from designed digital differentiator examples indicate that the approach can reach smaller peak...
In this paper, teaching-learning-based optimization (TLBO) is used for minimax design of linear phase finite impulse response (FIR) digital Hilbert transformers. TLBO is a population-based and heuristic search algorithm which is parameter-free and exhibits a strong convergence ability. The results obtained from using TLBO to design Type 4 linear phase FIR highpass digital Hilbert transformers indicate...
In this paper a new heuristic algorithm called Gravitational Search Algorithm (GSA), is employed for the optimization of the filter coefficients of infinite impulse response (IIR) integrator design problem. GSA is a population based algorithm formulated on the principles of Newtonian gravity and law of motion. GSA employs the interaction of masses in an isolated system directed by law of Newtonian...
This paper presents an optimal design of linear phase digital finite impulse response (FIR) low pass (LP) filter using Adaptive Particle Swarm Optimization (APSO). APSO is an improved version of conventional PSO in which estimation of evolution state determines one of the four phases such as exploration, exploitation, convergence and jump-out for the entire optimization process. These modifications...
Independent component analysis (ICA) is a statistical signal processing technique for separation of mixed voices, images and signal. The basic idea of ICA is to find the underlying independent components in the mixture by searching for a linear or nonlinear transformation and minimizing the statistical dependence between components. Due to the computational complexity of ICA and commonly used data...
As in other complex signal processing tasks, ECG beat delineation algorithms are usually constituted of a set of processing modules, each one characterized by a certain number of parameters (filter cutoff frequencies, threshold levels, time windows, etc.). It is well recognized that the adjustment of these parameters is a complex task that is traditionally performed empirically and manually, based...
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