Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/24495
Title: | Artificial neural networks |
Authors: | Cortis, Andrew |
Keywords: | Neural networks (Computer science) Proof theory Mathematics -- Periodicals |
Issue Date: | 2003 |
Publisher: | University of Malta. Department of Mathematics |
Citation: | Cortis, A. (2003). Artificial neural networks. The Collection, 7, 28-33. |
Abstract: | It is a Parallel Computational Network made up of interconnected neurons. They are biologically inspired, i.e. they are composed of elements that work analogously to the most elementary functions of the biological neuron. Despite the similarities, the actual "intelligence" exhibited by the most sophisticated artificial neural networks, is still very limited. Each Neuron performs a function on its input. Each neuron passes its output on to another neuron to allow it to perform its work. Artificial Neural Networks can modify their behavior in response to their environment: given a set of inputs (perhaps along with the desired outputs), they can self-adjust to produce consistent responses. |
URI: | https://www.um.edu.mt/library/oar//handle/123456789/24495 |
Appears in Collections: | Collection, No.7 Collection, No.7 |
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Artificial neural networks.pdf | 208.45 kB | Adobe PDF | View/Open |
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