Bio-Inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition

ISBN-13: 9783642045158 / Angielski / Twarda / 2009 / 263 str.

Patricia Melin; Janusz Kacprzyk; Witold Pedrycz

Opis

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 into 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 in which both theoretical and application aspects are covered.

Spis treści

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.

Blurb

"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.