  In most digital communication systems, bandwidth limited channel along with
multipath propagation causes ISI (Inter Symbol Interference) to occur. This
phenomenon causes distortion of the given transmitted symbol due to other
transmitted symbols. With the help of equalization ISI can be reduced. This
paper presents a solution to the ISI problem by performing blind equalization
using ANN (Artificial Neural Networks). The simulated network is a multilayer
feedforward Perceptron ANN, which has been trained by utilizing the error
back-propagation algorithm. The weights of the network are updated in
accordance with training of the network. This paper presents a very effective
method for blind channel equalization, being more efficient than the
pre-existing algorithms. The obtained results show a visible reduction in the
noise content.
