Neural Networks in Telecommunications

Nirwan Ansari

ISBN 10: 1461361796 / ISBN 13: 9781461361794

Editore: Springer US, 2012

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Druck auf Anfrage Neuware - Printed after ordering - Neural Networks in Telecommunications consists of a carefully edited collection of chapters that provides an overview of a wide range of telecommunications tasks being addressed with neural networks. These tasks range from the design and control of the underlying transport network to the filtering, interpretation and manipulation of the transported media. The chapters focus on specific applications, describe specific solutions and demonstrate the benefits that neural networks can provide. By doing this, the authors demonstrate that neural networks should be another tool in the telecommunications engineer's toolbox. Neural networks offer the computational power of nonlinear techniques, while providing a natural path to efficient massively-parallel hardware implementations. In addition, the ability of neural networks to learn allows them to be used on problems where straightforward heuristic or rule-based solutions do not exist. Together these capabilities mean that neural networks offer unique solutions to problems in telecommunications. For engineers and managers in telecommunications, Neural Networks in Telecommunications provides a single point of access to the work being done by leading researchers in this field, and furnishes an in-depth description of neural network applications.

Codice articolo 9781461361794

Dati bibliografici

• Titolo: Neural Networks in Telecommunications
• Editore: Springer US
• Data di pubblicazione: 2012
• Lingua: Inglese
• ISBN 10: 1461361796
• ISBN 13: 9781461361794
• Rilegatura: Taschenbuch
• Condizione: Neu

Descrizione articolo

Riassunto

Neural Networks in Telecommunications consists of a carefully edited collection of chapters that provides an overview of a wide range of telecommunications tasks being addressed with neural networks. These tasks range from the design and control of the underlying transport network to the filtering, interpretation and manipulation of the transported media. The chapters focus on specific applications, describe specific solutions and demonstrate the benefits that neural networks can provide. By doing this, the authors demonstrate that neural networks should be another tool in the telecommunications engineer's toolbox.
Neural networks offer the computational power of nonlinear techniques, while providing a natural path to efficient massively-parallel hardware implementations. In addition, the ability of neural networks to learn allows them to be used on problems where straightforward heuristic or rule-based solutions do not exist. Together these capabilities mean that neural networks offer unique solutions to problems in telecommunications.
For engineers and managers in telecommunications, Neural Networks in Telecommunications provides a single point of access to the work being done by leading researchers in this field, and furnishes an in-depth description of neural network applications.

Contenuti

1. Introduction; B. Yuhas, N. Ansari. 2. Neural Networks for Switching; T.X. Brown. 3. Routing in Random Multistage Interconnection Networks; M.W. Goudreau, C.L. Giles. 4. ATM Traffic Control Using Neural Networks; A. Hiramatsu. 5. Learning from Rare Events: Dynamic Cell Scheduling for ATM Networks; D.B. Schwartz. 6. A Neural Model for Adaptive Congestion Control in ATM Networks; Xiaoqiang Chen. 7. Structure and Performance of Neural Nets in Broadband System Admission Control; Phuoc Tran-Gia, O. Gropp. 8. Neural Network Channel Equalization; W.R. Kirkland, D.P. Taylor. 9. Neural Networks as Excisers for Spread Spectrum Communication Systems; R. Bijjani, P.K. Das. 10. Static and Dynamic Channel Assignment Using Simulated Annealing; M. Duque-Antón, D. Kunz, B. Rüber. 11. Cellular Mobile Communication Design Using Self-Organizing Feature Maps; T. Fritsch. 12. Automatic Language Identification Using Telephone Speech; Y.K. Muthusamy, R.A. Cole. 13. Text-Independent Talker Verification Using Cohort Normalized Scores; D.J. Burr. 14. Neural Network Applications in Character Recognition and Document Analysis; L.D. Jackel, et al. 15. Image Vector Quantization by Neural Networks; R. Lancini. 16. Managing the Infoglut: Information Filtering Using Neural Networks; T. John. 17. Empirical Comparisons of Neural Networks and Statistical Methods for Classification and Regression; D. Duffy, B. Yuhas, A. Jain, A. Buja. 18. A Neurocomputing Approach to Optimizingthe Performance of a Satellite Communication Network; N. Ansari. Index.