ABSTRACT
Artificial Neural Networks have been one of the most active areas of research in computer science over the last 50 years with periods of intense activity interrupted by episodes of hiatus [1]. The premise for the evolution of the theory of artificial Neural Networks stems from the basic neurological structure of living organisms. A cell is the most important constituent of these life forms. These cells are connected by “synapses,” that are the links that carry messages between cells. In fact, by using synapses to carry the pulses, cells can activate each other with different threshold values to form a decision or memorize an event. Inspired by this simplistic vision of how messages are transferred between cells, scientists invented a new computational approach, which became popularly known as Artificial Neural Networks (or Neural Networks for short) and used it extensively to target a wide range of problems in many application areas.
