Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy

We describe in this book, new methods for intelligent pattern recognition using soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including fuzzy logic, neural networks, and genetic algorithms, which can be used to produce powerful hybrid intelligent systems for pattern recognition. Hybrid intelligent systems that combine several SC techniques are needed due to the complexity and high dimensionality of pattern recognition problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of pattern recognition systems, for this reason it is very important to optimize architecture design.

The architectures can combine, in different ways, neural networks, fuzzy logic and genetic algorithms, 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.

As a prelude, we provide a brief overview of the existing methodologies in Soft Computing. We then describe our own approach in dealing with the problems in pattern recognition. Our particular point of view is that to really achieve intelligent pattern recognition in real-world applications we need to use SC techniques. As consequence, we will describe several real-world applications, in which the reader will be able to appreciate that the use of these techniques really helps in achieving the goals of intelligent pattern recognition. In these applications, we will always compare with the traditional approaches to make clear the advantages of using SC techniques.

This book is intended to be a major reference for scientists and engineers interested in applying new computational and mathematical tools to achieve intelligent pattern recognition. This book can also be used as a textbook or major 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 research, or to continue the lines of research proposed by the authors of the book.