Solutions to Parallel and Distributed Computing Problems: Lessons from Biological Sciences

10.1 INTRODUCTION

Because of its practical significance, there has been a growing interest in the literature in the field of artificial-neural-network (ANN) based applications. This field has seen a tremendous growth in several industries, such as very-large-scale integration (VLSI) design, computer engineering, and very-large telecommunication systems. Neural networks are massively parallel interconnected networks of simple (usually adaptive) elements that are intended to interact with real-world objects in the same way that the biological nervous system does [16]. Perhaps, one of the most relevant properties of neural networks is the possibility of learning. ANN estimates a function without requiring a mathematical description of how the output functionally depends on the input: they learn from examples. By learning, a neural network can discover some regular patterns and the relation across them, and organize itself for making these associations. As a consequence, they are widely used for solving regression and classification problems.

This chapter is motivated by the needs in the rapidly changing telecommunications industry, and present some applications of neural networks to wireless and mobile systems. The fusion of computer and telecommunication technologies has heralded the age of the information superhighway over wire-line and wireless networks. Mobile cellular communication systems and wireless networking technologies are growing at an ever-faster rate, and this is likely ...