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Introduction to Neural Networks

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Sensitivity Analysis for Neural Networks

Part of the book series: Natural Computing Series ((NCS))

Abstract

The human brain consists of ten billion densely interconnected nerve cells, called neurons; each connected to about 10,000 other neurons, with 60 trillion connections, synapses, between them. By using multiple neurons simultaneously, the brain can perform its functions much faster than the fastest computers in existence today. On the other hand, a neuron can be considered as a basic information-processing unit, whereas our brain can be considered as a highly complex, nonlinear and parallel biological information-processing network, in which information is stored and processed simultaneously. Learning is a fundamental and essential characteristic of biological neural networks. The ease with which they can learn led to attempts to emulate a biological neural network in a computer.

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Correspondence to Daniel S. Yeung .

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© 2009 Springer-Verlag Berlin Heidelberg

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Yeung, D.S., Cloete, I., Shi, D., Ng, W.W. (2009). Introduction to Neural Networks. In: Sensitivity Analysis for Neural Networks. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02532-7_1

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  • DOI: https://doi.org/10.1007/978-3-642-02532-7_1

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02531-0

  • Online ISBN: 978-3-642-02532-7

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