Neural Networks

Essay by Anonymous UserCollege, UndergraduateA+, November 1996

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        A neural network also known as an artificial neural network provides a unique computing architecture whose potential has only begun to be tapped. They are used to address problems that are intractable or cumbersome with traditional methods. These new computing architectures are radically different from the computers that are widely used today. ANN's are massively parallel systems that rely on dense arrangements of interconnections and surprisingly simple processors (Cr95, Ga93).

        Artificial neural networks take their name from the networks of nerve cells in the brain. Although a great deal of biological detail is eliminated in these computing models, the ANN's retain enough of the structure observed in the brain to provide insight into how biological neural processing may work (He90).

        Neural networks provide an effective approach for a broad spectrum of applications. Neural networks excel at problems involving patterns, which include pattern mapping, pattern completion, and pattern classification (He95). Neural networks may be applied to translate images into keywords or even translate financial data into financial predictions (Wo96).

        Neural networks utilize a parallel processing structure that has large numbers of processors and many interconnections between them. These processors are much simpler than typical central processing units (He90). In a neural network, each processor is linked to many of its neighbors so that there are many more interconnections than processors. The power of the neural network lies in the tremendous number of interconnections (Za93).

        ANN's are generating much interest among engineers and scientists. Artificial neural network models contribute to our understanding of biological models. They also provide a novel type of parallel processing that has powerful capabilities and potential for creative hardware implementations, meets the demand for fast computing hardware, and provides the potential for solving application problems (Wo96).

        Neural networks excite our imagination and relentless desire to understand the self,