Modular Neural Networks And Type 2 Fuzzy Systems For Pattern Recognition
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Modular Neural Networks and Type 2 Fuzzy Systems for Pattern Recognition
Author | : Patricia Melin |
Publsiher | : Springer Science & Business Media |
Total Pages | : 216 |
Release | : 2011-10-18 |
Genre | : Computers |
ISBN | : 9783642241383 |
Download Modular Neural Networks and Type 2 Fuzzy Systems for Pattern Recognition Book in PDF, Epub and Kindle
This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural networks with the aim of designing intelligent systems for complex pattern recognition problems, including iris, ear, face and voice recognition. The third part contains chapters with the theme of evolutionary optimization of type-2 fuzzy systems and modular neural networks in the area of intelligent pattern recognition, which includes the application of genetic algorithms for obtaining optimal type-2 fuzzy integration systems and ideal neural network architectures for solving problems in this area.
Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing
Author | : Patricia Melin,Oscar Castillo |
Publsiher | : Springer Science & Business Media |
Total Pages | : 296 |
Release | : 2005-03-08 |
Genre | : Computers |
ISBN | : 3540241213 |
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This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms. Hybrid intelligent systems that combine several soft computing techniques are needed due to the complexity of pattern recognition problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of pattern recognition systems, to achieve the ultimate goal of pattern recognition. This book also shows results of the application of hybrid intelligent systems to real-world problems of face, fingerprint, and voice recognition. This monograph is intended to be a major reference for scientists and engineers applying new computational and mathematical tools to intelligent pattern recognition and can be also used as a textbook for graduate courses in soft computing, intelligent pattern recognition, computer vision, or applied artificial intelligence.
Modular Neural Networks and Type 2 Fuzzy Systems for Pattern Recognition
Author | : Patricia Melin |
Publsiher | : Springer |
Total Pages | : 214 |
Release | : 2011-10-25 |
Genre | : Technology & Engineering |
ISBN | : 9783642241390 |
Download Modular Neural Networks and Type 2 Fuzzy Systems for Pattern Recognition Book in PDF, Epub and Kindle
This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural networks with the aim of designing intelligent systems for complex pattern recognition problems, including iris, ear, face and voice recognition. The third part contains chapters with the theme of evolutionary optimization of type-2 fuzzy systems and modular neural networks in the area of intelligent pattern recognition, which includes the application of genetic algorithms for obtaining optimal type-2 fuzzy integration systems and ideal neural network architectures for solving problems in this area.
Recent Advances in Interval Type 2 Fuzzy Systems
Author | : Oscar Castillo,Patricia Melin |
Publsiher | : Springer Science & Business Media |
Total Pages | : 93 |
Release | : 2012-04-23 |
Genre | : Technology & Engineering |
ISBN | : 9783642289569 |
Download Recent Advances in Interval Type 2 Fuzzy Systems Book in PDF, Epub and Kindle
This book reviews current state of the art methods for building intelligent systems using type-2 fuzzy logic and bio-inspired optimization techniques. Combining type-2 fuzzy logic with optimization algorithms, powerful hybrid intelligent systems have been built using the advantages that each technique offers. This book is intended to be a reference for scientists and engineers interested in applying type-2 fuzzy logic for solving problems in pattern recognition, intelligent control, intelligent manufacturing, robotics and automation. This book can also be used as a reference for graduate courses like the following: soft computing, intelligent pattern recognition, computer vision, applied artificial intelligence, and similar ones. We consider that this book can also be used to get novel ideas for new lines of re-search, or to continue the lines of research proposed by the authors.
Bio Inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition
Author | : Patricia Melin,Witold Pedrycz |
Publsiher | : Springer Science & Business Media |
Total Pages | : 258 |
Release | : 2009-09-30 |
Genre | : Computers |
ISBN | : 9783642045158 |
Download Bio Inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition Book in PDF, Epub and Kindle
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.
Type 2 Fuzzy Logic Theory and Applications
Author | : Oscar Castillo,Patricia Melin |
Publsiher | : Springer Science & Business Media |
Total Pages | : 252 |
Release | : 2008-02-20 |
Genre | : Mathematics |
ISBN | : 9783540762836 |
Download Type 2 Fuzzy Logic Theory and Applications Book in PDF, Epub and Kindle
This book describes new methods for building intelligent systems using type-2 fuzzy logic and soft computing (SC) techniques. The authors extend the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each technique offers. This book is intended to be a major reference tool and can be used as a textbook.
Recent Advances on Hybrid Intelligent Systems
Author | : Oscar Castillo,Patricia Melin,Janusz Kacprzyk |
Publsiher | : Springer |
Total Pages | : 558 |
Release | : 2012-09-14 |
Genre | : Technology & Engineering |
ISBN | : 9783642330216 |
Download Recent Advances on Hybrid Intelligent Systems Book in PDF, Epub and Kindle
This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for achieving efficient pattern recognition or time series prediction. The third part contains papers with the theme of bio-inspired and genetic optimization methods, which basically consider the proposal of new methods and applications of bio-inspired optimization to solve complex optimization of real problems. The fourth part contains papers that deal with the application of intelligent optimization techniques in real world problems in scheduling, planning and manufacturing. The fifth part contains papers with the theme of evolutionary methods and intelligent computing, which are papers considering soft computing methods for applications related to diverse areas, such as natural language processing, recommending systems and optimization.
Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation
Author | : Daniela Sanchez,Patricia Melin |
Publsiher | : Springer |
Total Pages | : 101 |
Release | : 2016-02-23 |
Genre | : Technology & Engineering |
ISBN | : 9783319288628 |
Download Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation Book in PDF, Epub and Kindle
In this book, a new method for hybrid intelligent systems is proposed. The proposed method is based on a granular computing approach applied in two levels. The techniques used and combined in the proposed method are modular neural networks (MNNs) with a Granular Computing (GrC) approach, thus resulting in a new concept of MNNs; modular granular neural networks (MGNNs). In addition fuzzy logic (FL) and hierarchical genetic algorithms (HGAs) are techniques used in this research work to improve results. These techniques are chosen because in other works have demonstrated to be a good option, and in the case of MNNs and HGAs, these techniques allow to improve the results obtained than with their conventional versions; respectively artificial neural networks and genetic algorithms.