DIGITAL COMMUNICATION (ECE-305)

DIGITAL COMMUNICATION(ECE-305)TECHNICAL PAPER-PPTSubmitted by,PONGANESH.C(9911005114)PANDIMUNEESWARAN.M(9911005110)ECE-B

Title:A Clustering Technique for Digital Communications Channel Equalization Using Radial Basis Function Networks

CHANNEL EQUALIZEREqualization is the process of adjusting the balance betweenfrequencycomponents within an electronicsignal. The circuit or equipment used to achieve equalization is called an equalizer. These devices strengthen (boost) or weaken (cut) the energy of specific frequencybands.Anadaptive equalizeris anequalizerthat automatically adapts to time-varying properties of thecommunication channelRADIAL BASIS FUNCTIONIt is an Artificial Neural NetworkThey are having two layerThe hidden nodes implement a set of radial basis function (E.g:Gaussian Function)The output nodes implement liner summation function as in MLPThe training/learning is Very FastThe network are network very good at Interpolation

SOFTWARE TOOL:Here, we use the MATLAB program

TECHNIQUESclustering algorithmGaussian algorithmleast mean square (LMS) algorithm

Equalizer: Bayesian equalizer Adaptive equalizer

ADVANTAGE OF RBFIt has been demonstrated that the training of the RBF network to realize the optimal equalizer solution can be achieved efficiently using the supervised clustering algorithm. For no stationary channels, a decision-directed version of the clustering algorithm can be employed to provide tracking ability for the RBF network during data transmission. A useful technique to improve equalization performance is to use the decision feedback.

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