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Independent component analysis (ICA) technique separates mixed signals blindly without any information of the mixing system. Fast ICA is the most popular gradient based ICA algorithm. Bacterial foraging optimization based ICA (BFOICA) and constrained genetic algorithm based ICA (CGAICA) are two recently developed derivative free evolutionary computational ICA techniques. In BFOICA the foraging behavior...
The task of radar pulse compression is formulated as a multi-objective optimization problem and has been effectively solved using radial basis function (RBF) network and multi-objective genetic algorithm (NSGA-II). The pulse compression performance of three different codes in terms of signal to peak side-lobe ratio (SSR) under noisy environment, range resolution and Doppler shift are evaluated through...
The paper aims to develop an efficient forecasting model using differential evolution (DE) based learning rule. The structure chosen is an adaptive linear combiner whose weights are trained using DE. The prediction performance of the resulting model is evaluated by feeding features of retail sales data for different months' ahead prediction. These results are compared with those obtained by GA based...
Predicting the structure of a protein from primary sequence is one of the challenging problems in Molecular biology. In this context, protein structural class information provides a key idea of their structure and also other features related to the biological function. In this paper we present a new optimization approach based on Genetic algorithm (GA) and artificial immune system (AIS) for predicting...
Transmission and storing of high density digital information plays an important role in the present age of communication and information technology. These data are distorted while reading out of the recording medium or arriving at the receiver end due to inter symbol interference in the channel. The adaptive channel equalizer alleviates this distortion and reconstructs the transmitted data faithfully...
This paper introduces the application of particle swarm optimization (PSO) technique to identify the parameters of pole-zero plants or infinite impulse response (IIR) systems. The PSO is one of the evolutionary computing tools that performs a structured randomized search of an unknown parameter space by manipulating a population of parameter estimates to converge to a suitable solution with low computational...
In this paper we introduce the Comprehensive Learning Particle Swarm Optimization (CLEPSO) technique for identification of nonlinear systems. System identification in noisy environment has been a matter of concern for researchers in control theory for nonlinear analysis and optimization. In the recent past the Least Mean Square Algorithm (LMS), Genetic Algorithm (GA), Particle Swarm Optimization (PSO)...
Transmission and storing of high density digital information plays an important role in the present age of information technology. These binary data are distorted while reading out of the recording medium or arriving at the receiver end due to inter symbol interference in the channel. The adaptive channel equalizer alleviates this distortion and reconstructs the transmitted data faithfully. The bacterial...
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