This highly interdisciplinary book covers for the first time the applications of neurofuzzy and fuzzyneural scientific tools in a very wide area within the communications field. It deals with the important and modern areas of telecommunications amenable to such a treatment. Therefore, it is of interest to researchers and graduate students as well as practising engineers. Integration of Neural and Fuzzy Neuro-Fuzzy Applications in Speech Coding and Recognition Image/Video Compression Using Neuro-Fuzzy Techniques A Neuro-Fuzzy System for Source Location and Tracking in Wireless Communications Fuzzy Neural Applications in Handoff An Application of Neuro Fuzzy Systems for Access Control in Asynchronous Transfer Mode Networks.
|Statement||edited by Peter Stavroulakis|
|Series||Signals and Communication Technology, Signals and communication technology|
|The Physical Object|
|Format||[electronic resource] /|
|Pagination||1 online resource (xviii, 339 p.)|
|Number of Pages||339|
|ISBN 10||364262281X, 3642187625|
|ISBN 10||9783642622816, 9783642187629|
Get this from a library! Neuro-Fuzzy and Fuzzy-Neural Applications in Telecommunications. [Peter Stavroulakis] -- This highly interdisciplinary book covers for the first time the applications of neurofuzzy and fuzzyneural scientific tools in a very wide area within the communications field. It deals with the. Get this from a library! Neuro-fuzzy and fuzzy-neural applications in telecommunications. [Peter Stavroulakis;] -- "This book covers for the first time the applications of neurofuzzy and fuzzyneural scientific tools in a very wide area within the communications field. It deals with the important and modern areas. Note: If you're looking for a free download links of Neuro-Fuzzy and Fuzzy-Neural Applications in Telecommunications (Signals and Communication Technology) Pdf, epub, docx and torrent then this site is not for you. only do ebook promotions online and we does not distribute any free download of ebook on this site. Beritelli F., Russo M., Serrano S. () Neuro-Fuzzy Applications in Speech Coding and Recognition. In: Stavroulakis P. (eds) Neuro-Fuzzy and Fuzzy-Neural Applications in Telecommunications. Signals and Communication : Francesco Beritelli, Marco Russo, Salvatore Serrano.
Overview. Neuro-fuzzy hybridization results in a hybrid intelligent system that synergizes these two techniques by combining the human-like reasoning style of fuzzy systems with the learning and connectionist structure of neural networks. Neuro-fuzzy hybridization is widely termed as fuzzy neural network (FNN) or neuro-fuzzy system (NFS) in the literature. Neuro-Fuzzy Comp. Ch. 1 We can say that in general Neural networks and fuzzy logic systems are parameterised computational nonlinear algorithms for numerical processing of data (signals, images, stimuli). These algorithms can be either implemented of a general-purpose computer or built into a dedicated Size: KB. The paper introduces a new type of evolving fuzzy neural networks (EFuNNs), denoted as mEFuNNs, for on-line learning and their applications for dynamic time series analysis and prediction. mEFuNNs. Fast adaptive neuro fuzzy systems can be applied to various applications as it takes lesser time for convergence. In economics system there is a huge scope of future development using ANFIS. The ANFIS is a class of adaptive networks, which are functionally equivalent to the fuzzy inference system and a popular computing framework based on the Cited by:
This text provides the first comprehensive treatment of the methodologies underlying neuro-fuzzy and soft computing, an evolving branch within the scope of computational intelligence. The book places equal emphasis on theoretical aspects of covered methodologies, empirical observations and verifications of various applications in bility: Available. This chapter discusses fuzzy neural networks and their applications. Such networks have highly heterogeneous neural architectures, combining the learning abilities residing within neural networks while enjoying an explicit format of knowledge representation that is an inherent functional component originating from the theory of fuzzy sets. What are Neuro-Fuzzy Systems? A neuro-fuzzy system is a fuzzy system that uses a learning algorithm derived from or inspired by neural network theory to determine its parameters (fuzzy sets and fuzzy rules) by processing data samples. This is the abstract of our view on neuro-fuzzy systems which we explain in more detail below. This book presents specific projects where fusion techniques have been applied. The chapters start with the design of a new fuzzy-neural controller. Remaining chapters discuss the application of expert systems, neural networks, fuzzy control, and evolutionary computing techniques in modern engineering systems.