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Journal ArticleDOI

IIR system identification using cat swarm optimization

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TLDR
The IIR system identification task is formulated as an optimization problem and a recently introduced cat swarm optimization (CSO) is used to develop a new population based learning rule for the model.
Abstract
Conventional derivative based learning rule poses stability problem when used in adaptive identification of infinite impulse response (IIR) systems. In addition the performance of these methods substantially deteriorates when reduced order adaptive models are used for such identification. In this paper the IIR system identification task is formulated as an optimization problem and a recently introduced cat swarm optimization (CSO) is used to develop a new population based learning rule for the model. Both actual and reduced order identification of few benchmarked IIR plants is carried out through simulation study. The results demonstrate superior identification performance of the new method compared to that achieved by genetic algorithm (GA) and particle swarm optimization (PSO) based identification.

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Citations
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Journal ArticleDOI

Solving multiobjective problems using cat swarm optimization

TL;DR: A new multiobjective evolutionary algorithm (MOEA) is proposed by extending the existing cat swarm optimization (CSO) and finds the nondominated solutions along the search process using the concept of Pareto dominance and uses an external archive for storing them.
Journal ArticleDOI

Cat Swarm Optimization algorithm for optimal linear phase FIR filter design.

TL;DR: The CSO based results confirm the superiority of the proposed CSO for solving FIR filter design problems and demonstrate that the CSO is the best optimizer among other relevant techniques, not only in the convergence speed but also in the optimal performances of the designed filters.
Journal ArticleDOI

Linear antenna array synthesis using cat swarm optimization

TL;DR: The flexibility and ease of implementation of the CSO algorithm is evident from this analysis, showing the algorithm's usefulness in electromagnetic optimization problems.
Journal ArticleDOI

Microarray medical data classification using kernel ridge regression and modified cat swarm optimization based gene selection system

TL;DR: Experimental results demonstrate that KRR outperforms other models irrespective of the datasets and WKRR produces better results as compared to RKRR, and when the results are compared on the basis of binary and multi-class datasets, it is found that binary class yields a little bit better result asCompared to the multiclass irrespective of models.
Journal ArticleDOI

A novel optimised self-learning method for compressive strength prediction of high performance concrete

TL;DR: The results indicate that the proposed SVM-based model exhibits better recognition ability and higher prediction accuracy than other commonly used models, and it can be considered as an effective method to predict the CS property of HPC in infrastructure practice.
References
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Book

System Identification: Theory for the User

Lennart Ljung
TL;DR: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis and praktische Anwendung der verschiedenen Verfahren zur IdentifIZierung hat.
Book

Adaptive Signal Processing

TL;DR: This chapter discusses Adaptive Arrays and Adaptive Beamforming, as well as other Adaptive Algorithms and Structures, and discusses the Z-Transform in Adaptive Signal Processing.
Journal ArticleDOI

System identification-A survey

TL;DR: The survey explains the least squares method and several of its variants which may solve the problem of correlated residuals, viz. repeated and generalized least squares, maximum likelihood method, instrumental variable method, tally principle.
Journal ArticleDOI

Adaptive IIR filtering

TL;DR: In this article, an overview of several methods, filter structures, and recursive algorithms used in adaptive infinite-impulse response (IIR) filtering is presented, and several important issues associated with adaptive IIR filtering, including stability monitoring, the SPR condition, and convergence are addressed.
Journal ArticleDOI

A new design method based on artificial bee colony algorithm for digital IIR filters

TL;DR: A new method based on ABC algorithm for designing digital IIR filters is described and its performance is compared with that of a conventional optimization algorithm (LSQ-nonlin) and particle swarm optimization (PSO) algorithm.
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