Artificial Intelligence

ain. Neural networks are composed of simple components called
             "neurons" each having simple tasks, and simultaneously communicating with each other by
             complex interconnections. As Herb Brody states, "Neural networks do not require an explicit
             set of rules. The network - rather like a child - makes up its own rules that match the
             data it receives to the result it’s told is correct" (42). Impossible to achieve in expert
             systems, this ability to learn by example is the characteristic of neural networks that makes
             them best suited to simulate human behavior. Computer scientists have exploited this system
             characteristic to achieve breakthroughs in computer vision, speech recognition, and optical
             character recognition. Figure 1 illustrates the knowledge structures of neural networks
             as compared to expert systems and standard computer programs. Neural networks restructure
             their knowledge base at each step in the learning process.
             This paper focuses on neural network technologies which have the potential to increase security
             for financial transactions. Much of the technology is currently in the research phase and has
             yet to produce a commercially available product, such as visual recognition applications.
             Other applications are a multimillion dollar industry and the products are well known, like
             Sprint Telephone’s voice activated telephone calling system. In the Sprint system the neural
             network positively recognizes the caller’s voice, thereby authorizing activation of his
             The study of the brain was once limited to the study of living tissue. Any attempts at an
             electronic simulation were brushed aside by the neurobiologist community as abstract conceptions
             that bore little relationship to reality. This was partially due to the over-excitement in
             the 1950’s and 1960’s for networks t...

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