Neural Network and Fuzzy Logic Applications in C/C++ by Stephen T. WelsteadBy Anatoly D. Khomonenko, Sergey E. Adadurov, Alexandr V. Krasnovidow and Pavel A. Indoor mobile navigation systems are becoming more prevalent in many areas transport, public institutions, logistics, etc. The interior navigation based on the access points, arranged according to the radio fingerprints, is becoming increasingly popular. The model of artificial neural networks ANN is often used as a mechanism for storing and processing radio fingerprints.
Neural Networks and Fuzzy Logic 101 (with subtitles)
Understanding Neural Networks and Fuzzy Logic : Basic Concepts and Applications
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PHI Learning Pvt. This book provides comprehensive introduction to a consortium of technologies underlying soft computing, an evolving branch of computational intelligence. The constituent technologies discussed comprise neural networks, fuzzy logic, genetic algorithms, and a number of hybrid systems which include classes such as neuro-fuzzy, fuzzy-genetic, and neuro-genetic systems. The book also gives an exhaustive discussion of FL-GA hybridization. Every architecture has been discussed in detail through illustrative examples and applications. The algorithms have been presented in pseudo-code with a step-by-step illustration of the same in problems.
Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book! Not only does this book stand apart from others in its focus but also in its application-based presentation style. Prepared in a way that can be easily understood by those who are experienced and inexperienced in this field. Readers can benefit from the computer source codes for both identification and control purposes which are given at the end of the book. A clear and an in-depth examination has been made of all the necessary mathematical foundations, type-1 and type-2 fuzzy neural network structures and their learning algorithms as well as their stability analysis. You will find that each chapter is devoted to a different learning algorithm for the tuning of type-1 and type-2 fuzzy neural networks; some of which are:.
Understanding Neural Networks and Fuzzy Logic: Basic Concepts and and the most used paradigms with this carefully organized state-of-the-art textbook.
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