Mathematical foundations of neurocomputing

Journal Article · Sat Sep 01 00:00:00 EDT 1990 · Proceedings of the IEEE (Institute of Electrical and Electronics Engineers); (USA)

DOI:https://doi.org/10.1109/5.58324· OSTI ID:6357408

Amari, S ^[1]

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1. Tokyo Univ. (Japan). Faculty of Engineering

Neurocomputing makes use of parallel dynamical interactions of modifiable neuron-like elements. It is important to show, by mathematical treatments, the capabilities and limitations of information processing by various architectures of neural networks. This paper, gives mathematical foundations to neurocomputing. It considers the capabilities of transformations by layered networks, statistical neurodynamics, the dynamical characteristics of associative memory, a general theory of neural learning, and self-organization of neural networks.

• OSTI ID: 6357408
• Journal Information: Proceedings of the IEEE (Institute of Electrical and Electronics Engineers); (USA), Vol. 78:9; ISSN 0018-9219
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
PARALLEL PROCESSING
COMPUTER ARCHITECTURE
LEARNING
MATHEMATICAL MODELS
NEURAL NETWORKS
PROGRAMMING
990200* - Mathematics & Computers