Design of Adaptive Equaliser Structures in Neural Network Paradigm
SUSMITA DAS
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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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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, ge...