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Soft Computing in Communications

  • Book
  • © 2004

Overview

Authors:
  1. Lipo Wang

    1. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

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  • Presents novel applications of soft computing to telecommunications

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 136)

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Table of contents (18 chapters)

  1. Front Matter

    Pages I-VIII
    Download chapter PDF

  2. Neural Networks

    1. Neural Approximation of Resource Allocation Functions in Multiservice Access Multiplexers

      • Franco Davoli, Piergiulio Maryni
      Pages 1-30

    2. Performance of the Multilayer Perceptron-based Decision Feedback Equalizer with Lattice Structure in Non-Linear Channels

      • Azzedine Zerguine, Ahmar Shafi
      Pages 31-53

    3. Nonlinear Channel Identification Using Natural Gradient Descent: Application to Modeling and Tracking

      • Mohamed Ibnkahla
      Pages 55-70

    4. Maximizing Topology Connectivity Using a Hopfield Neural Network

      • Hosam M. F. AboElFotoh
      Pages 71-86

    5. Binary Neural Network Approaches to Combinatorial Optimization Problems in Communication Networks

      • Nobuo Funabikil
      Pages 87-104

    6. Robust Multiuser Detection Using Artificial Neural Networks

      • B. S. Sharif, T. C. Chuah, O. R. Hinton
      Pages 105-129

    7. Minimizing Interference in Cellular Mobile Communications by Optimal Channel Assignment Using Chaotic Simulated Annealing

      • Lipo Wang, Sa Li, Chunru Wan, Boon Hee Soong
      Pages 131-145

  3. Evolutionary Computation

    1. Orthogonal Genetic Algorithms with Application to Multimedia Multicast Routing

      • Yiu-Wing Leung
      Pages 147-174

    2. Solving the QoS Multicast Routing Problems Using Genetic Algorithms

      • Qijun Gu, Chao-Hsien Chu
      Pages 175-200

    3. Base Station Location Optimization in Cellular Wireless Networks using Heuristic Search Algorithms

      • Bhaskar Krishnamachari, Stephen Wicker
      Pages 201-219

    4. The Synthesis and Design of Communication Antennas Using Genetic Algorithms

      • Douglas H. Werner, Matthew G. Bray, Rene J. Allard, Pingjuan L. Werner
      Pages 221-244

  4. Fuzzy Logic and Neurofuzzy Systems

    1. QoS Adaptation Based on Fuzzy Theory

      • Cristian Koliver, Jean-Marie Farines, Klara Nahrstedt
      Pages 245-267

    2. Fuzzy Chaotic Synchronization and Communication — Signal Masking and Encryption

      • Kuang-Yow Lian, Peter Liu, Chian-Song Chiu
      Pages 269-291

    3. Intelligent Channel Assignment Schemes for Hierarchical Cellular Systems

      • Kuen-Rong Lo, Chung-Ju Chang, Yih-Shen Chen
      Pages 293-321

    4. A New Mobility Prediction System using Neuro-Fuzzy Model and Its Application to Restoration of Mobility Databases

      • Joon-Min Gil, Chan Yeol Park
      Pages 323-343

    5. Voice Over Wireless LAN Using Intelligent Control

      • Maria C. Yuang, Po-Lung Tien
      Pages 345-364

  5. Kernel Methods

    1. Least Squares Kernel Methods and Applications

      • Anthony Kuh
      Pages 365-387

    2. Least Bit Error Rate Adaptive Multiuser Detection

      • Sheng Chen
      Pages 389-408
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Keywords

About this book

Soft computing, as opposed to conventional "hard" computing, tolerates imprecision and uncertainty, in a way very much similar to the human mind. Soft computing techniques include neural networks, evolutionary computation, fuzzy logic, and chaos. The recent years have witnessed tremendous success of these powerful methods in virtually all areas of science and technology, as evidenced by the large numbers of research results published in a variety of journals, conferences, as weil as many excellent books in this book series on Studies in Fuzziness and Soft Computing. This volume is dedicated to recent novel applications of soft computing in communications. The book is organized in four Parts, i.e., (1) neural networks, (2) evolutionary computation, (3) fuzzy logic and neurofuzzy systems, and (4) kernel methods. Artificial neural networks consist of simple processing elements called neurons, which are connected by weights that may be adjusted during learning. Part 1 of the book has seven chapters, demonstrating some of the capabilities of two major types of neural networks, i.e., multiplayer perceptron (MLP) neural networks and Hopfield-type neural networks.

Authors and Affiliations

  • School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

    Lipo Wang

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