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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/716

Title: Design of Adaptive Channel Equaliser on Neural Framework Using Fuzzy Logic Based Multilevel Sigmoid Slope Adaptation
Authors: Das, S
Keywords: adaptive equalisers
error statistics
fuzzy control
fuzzy logic
recurrent neural nets
telecommunication control
Issue Date: 2008
Publisher: IEEE
Citation: Proceedings of the International Conference on Signal Processing, Communications and Networking, 2008. ICSCN '08, 4-6 Jan. 2008, Anna Unviersity, Chennai
Abstract: Adaptive equalisation in digital communication systems is a process of compensating the disruptive effects caused mainly by inter symbol interference in a band-limited channel and plays a vital role for enabling higher data rate in modern digital communication system. Designing efficient equalisers having low structural complexity and faster learning algorithms is also an area of much research interest in the present scenario. This research work proposes adaptive channel equalisation techniques on Recurrent Neural Network framework. Exhaustive simulation studies carried out prove that by replacing the conventional sigmoid activation functions in each of the processing nodes of recurrent neural network with multilevel sigmoid activation functions, the bit error rate performance have significantly improved. Further slopes of different levels of the multi-level sigmoid have been adapted using fuzzy logic control concept Simulation results cosidering standard channel models show faster lea...
Description: Copyright for the published version belongs to IEEE
URI: http://dx.doi.org/10.1109/ICSCN.2008.4447203
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