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This work makes use of SFLA as a training algorithm to train multi-layer Artificial Neural Network (ANN). Next, The SFLA-ANNs are used for channel equalization. In this way, this book introduces a novel strategy for training of ANN and also proposes one novel approach for channel equalization problem. The proposed strategies are tested both in time-invariant and time varying channels and interestingly yields better performance than contemporary approaches as evidenced by simulation results.
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