TIME SERIES PREDICTION AND CHANNEL EQUALIZER USING ARTIFICIAL NEURAL NETWORKS WITH VLSI IMPLEMENTATION A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Technology in VLSI DESIGN and EMBEDDED SYSTEM

................................................................................................................................. vii List Of Figures ........................................................................................................................ iii List Of Tables .......................................................................................................................... iv Abbreviations Used ...................................................................................................................v CHAPTER 1.INTRODUCTION ..............................................................................................1 1.1 Motivation ....................................................................................................................2 1.2 Thesis Layout ...............................................................................................................3 CHAPTER 2.CONCEPTS OF NEURAL NETWORK ...........................................................4 2.1 Single Neuron Structure .....................................................................................................5 2.2 Activation Functions and Bias............................................................................................6 2.3 Learning Processes ............................................................................................................7 2.3.1 Supervised Learning: ...................................................................................................8 2.4 Recurrent Neural Network ................................................................................................9 2.5 The Back-Propagation Algorithm .................................................................................... 10 CHAPTER 3.MULTIFEED-BACK LAYER NEURAL NETWORK AND ITS APPLICATION....................................................................................................................... 12 3.