Design of Adaptive Equaliser Structures in Neural Network Paradigm: Development based on both feedforward and recurrent neural topologies of reduced structural complexity - Brossura
Sinossi
Adaptive channel equalisers compensate the disruptive effects caused by band-limited channels, hence enabling higher data rate in digital communication. Designing efficient equalisers based on low structural complexity is an area of interest amongst communication system designers. This research has significantly contributed to the development of novel equaliser structures in the neural network paradigm on the framework of both the feedforward neural network and the recurrent neural network of low structural complexity. Various innovative techniques like hierarchical knowledge reinforcement, genetic evolutionary concept, transform domain approach, tuning of sigmoid slope of neuron using fuzzy logic concept have been incorporated into an FNN framework to design highly efficient equaliser structures. Subsequently, an hybrid concept of using cascaded modules of RNN and FNN in various configurations has also been proposed. Significant performance improvement over the conventional equalisers in terms of BER, faster adaptation rate and ease of implementation are the major advantages of the proposed neural network based equalisers.
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Design of Adaptive Equaliser Structures in Neural Network Paradigm
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LAP LAMBERT Academic Publishing Okt 2009, 2009
ISBN 10: 3838321049
ISBN 13: 9783838321042
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Adaptive channel equalisers compensate the disruptive effects caused by band-limited channels, hence enabling higher data rate in digital communication. Designing efficient equalisers based on low structural complexity is an area of interest amongst communication system designers. This research has significantly contributed to the development of novel equaliser structures in the neural network paradigm on the framework of both the feedforward neural network and the recurrent neural network of low structural complexity. Various innovative techniques like hierarchical knowledge reinforcement, genetic evolutionary concept, transform domain approach, tuning of sigmoid slope of neuron using fuzzy logic concept have been incorporated into an FNN framework to design highly efficient equaliser structures. Subsequently, an hybrid concept of using cascaded modules of RNN and FNN in various configurations has also been proposed. Significant performance improvement over the conventional equalisers in terms of BER, faster adaptation rate and ease of implementation are the major advantages of the proposed neural network based equalisers. 216 pp. Englisch. Codice articolo 9783838321042
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Design of Adaptive Equaliser Structures in Neural Network Paradigm
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ISBN 13: 9783838321042
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Adaptive channel equalisers compensate the disruptive effects caused by band-limited channels, hence enabling higher data rate in digital communication. Designing efficient equalisers based on low structural complexity is an area of interest amongst communi. Codice articolo 5412769
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Design of Adaptive Equaliser Structures in Neural Network Paradigm | Development based on both feedforward and recurrent neural topologies of reduced structural complexity
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LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838321049
ISBN 13: 9783838321042
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Taschenbuch. Condizione: Neu. Design of Adaptive Equaliser Structures in Neural Network Paradigm | Development based on both feedforward and recurrent neural topologies of reduced structural complexity | Susmita Das | Taschenbuch | 216 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838321042 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Codice articolo 101292720
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Design of Adaptive Equaliser Structures in Neural Network Paradigm
Editore:
LAP LAMBERT Academic Publishing Okt 2009, 2009
ISBN 10: 3838321049
ISBN 13: 9783838321042
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Adaptive channel equalisers compensate the disruptive effects caused by band-limited channels, hence enabling higher data rate in digital communication. Designing efficient equalisers based on low structural complexity is an area of interest amongst communication system designers. This research has significantly contributed to the development of novel equaliser structures in the neural network paradigm on the framework of both the feedforward neural network and the recurrent neural network of low structural complexity. Various innovative techniques like hierarchical knowledge reinforcement, genetic evolutionary concept, transform domain approach, tuning of sigmoid slope of neuron using fuzzy logic concept have been incorporated into an FNN framework to design highly efficient equaliser structures. Subsequently, an hybrid concept of using cascaded modules of RNN and FNN in various configurations has also been proposed. Significant performance improvement over the conventional equalisers in terms of BER, faster adaptation rate and ease of implementation are the major advantages of the proposed neural network based equalisers.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 216 pp. Englisch. Codice articolo 9783838321042
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Design of Adaptive Equaliser Structures in Neural Network Paradigm : Development based on both feedforward and recurrent neural topologies of reduced structural complexity
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LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838321049
ISBN 13: 9783838321042
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Adaptive channel equalisers compensate the disruptive effects caused by band-limited channels, hence enabling higher data rate in digital communication. Designing efficient equalisers based on low structural complexity is an area of interest amongst communication system designers. This research has significantly contributed to the development of novel equaliser structures in the neural network paradigm on the framework of both the feedforward neural network and the recurrent neural network of low structural complexity. Various innovative techniques like hierarchical knowledge reinforcement, genetic evolutionary concept, transform domain approach, tuning of sigmoid slope of neuron using fuzzy logic concept have been incorporated into an FNN framework to design highly efficient equaliser structures. Subsequently, an hybrid concept of using cascaded modules of RNN and FNN in various configurations has also been proposed. Significant performance improvement over the conventional equalisers in terms of BER, faster adaptation rate and ease of implementation are the major advantages of the proposed neural network based equalisers. Codice articolo 9783838321042
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Design of Adaptive Equaliser Structures in Neural Network Paradigm: Development based on both feedforward and recurrent neural topologies of reduced structural complexity
Editore:
LAP Lambert Academic Publishing, 2010
ISBN 10: 3838321049
ISBN 13: 9783838321042
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