In this research project, the features of biological and artificial neural networks were studied by reviewing the existing works of authorities in print and electronics on biological and artificial neural networks.
The features were then assessed and evaluated and comparative analysis of the two networks was carried out. The metrics such as structures, layers, size and functional capabilities of neurons, learning capabilities, style of computation, processing elements, processing speed, connections, strength, information storage, information transmission, communication media selection, signal transduction and fault tolerance were used as basis for comparison.
A major finding in the research showed that artificial neural networks served as the platform for neuro-computing technology and as such a major driver of the development of neuron-like computing system. It was also discovered that Information processing of the future computer systems will greatly be influenced by the adoption of artificial neural network model.
Source: Scholars Research Library
Authors: O.S. Eluyode | Dipo Theophilus Akomolafe
Adaptive Synchronization and its Use in Biological Neural Network Modeling
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