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Bio-inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition [electronic resource] / edited by Patricia Melin, Janusz Kacprzyk, Witold Pedrycz.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Studies in Computational Intelligence ; 256 | Studies in Computational Intelligence ; 256Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009Descripción: VIII, 263 p. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9783642045165
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 519 23
Clasificación LoC:
  • TA329-348
  • TA640-643
Recursos en línea:
Contenidos:
Springer eBooksResumen: "Bio-Inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition" comprises papers on diverse aspects of bio-inspired models, soft computing and hybrid intelligent systems. The articles are divided in four main parts. The first one consists of papers that propose new fuzzy and bio-inspired models to solve general problems. The second part deals with the main theme of modular neural networks in pattern recognition, which are basically papers using bio-inspired techniques. The third part contains papers that apply hybrid intelligent systems to the problem of time series analysis and prediction, while the fourth one shows papers dealing with bio-inspired models in optimization and robotics applications. An edited book where both theoretical and application aspects are covered.
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Introductory Concepts and Models -- A Survey of Applications of the Extensions of Fuzzy Sets to Image Processing -- Interval Type-2 Fuzzy Cellular Model Applied to the Dynamics of a Uni-specific Population Induced by Environment Variations -- A Genetic Programming Approach to the Design of Interest Point Operators -- Modular Neural Networks in Pattern Recognition -- Face, Fingerprint and Voice Recognition with Modular Neural Networks and Fuzzy Integration -- Modular Neural Networks with Fuzzy Response Integration for Signature Recognition -- Intelligent Hybrid System for Person Identification Using Biometric Measures and Modular Neural Networks with Fuzzy Integration of Responses -- Optimization of Modular Neural Networks with Interval Type-2 Fuzzy Logic Integration Using an Evolutionary Method with Application to Multimodal Biometry -- Comparative Study of Fuzzy Methods for Response Integration in Ensemble Neural Networks for Pattern Recognition -- Neural Network Models and Time Series Prediction -- Ensemble Neural Networks with Fuzzy Integration for Complex Time Series Prediction -- Prediction of the MXNUSD Exchange Rate Using Hybrid IT2 FLS Forecaster -- Discovering Universal Polynomial Cellular Neural Networks through Genetic Algorithms -- EMG Hand Burst Activity Detection Study Based on Hard and Soft Thresholding -- Optimization and Robotics -- Modular Neural Networks Architecture Optimization with a New Evolutionary Method Using a Fuzzy Combination Particle Swarm Optimization and Genetic Algorithms -- A Multi-agent Architecture for Controlling Autonomous Mobile Robots Using Fuzzy Logic and Obstacle Avoidance with Computer Vision -- Particle Swarm Optimization Applied to the Design of Type-1 and Type-2 Fuzzy Controllers for an Autonomous Mobile Robot.

"Bio-Inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition" comprises papers on diverse aspects of bio-inspired models, soft computing and hybrid intelligent systems. The articles are divided in four main parts. The first one consists of papers that propose new fuzzy and bio-inspired models to solve general problems. The second part deals with the main theme of modular neural networks in pattern recognition, which are basically papers using bio-inspired techniques. The third part contains papers that apply hybrid intelligent systems to the problem of time series analysis and prediction, while the fourth one shows papers dealing with bio-inspired models in optimization and robotics applications. An edited book where both theoretical and application aspects are covered.

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