The Computational Capabilities of Neural Networks

0404164 - UIVT-O 20010033 RIV AT eng C - Conference Paper (international conference)
Šíma, Jiří
The Computational Capabilities of Neural Networks.
Artificial Neural Nets and Genetic Algorithms. Proceedings of the International conference. Wien: Springer, 2001 - (Kůrková, V.; Steele, N.; Neruda, R.; Kárný, M.), s. 22-26. ISBN 3-211-83651-9.
[ICANNGA'2001 /5./. Praha (CZ), 22.04.2001-25.04.2001]
R&D Projects: GA MŠMT LN00A056
Keywords : computational power * computational complexity * perceptrons * radial basis functions * spiking neurons * probabilistic computation * analog computation
Subject RIV: BA - General Mathematics
https://link.springer.com/book/10.1007/978-3-7091-6230-9#toc

We survey and summarize the existing literature on the computational aspects of neural network models, by presenting a detailed taxonomy of the various models according to their computational characteristics. The criteria of classification include e.g. the architecture of the network, time model, state type, weight constraints, network size, computation type, etc. The underlying results concerning the computational power of perceptron, RBF, winner-take-all, and spiking neural networks are briefly surveyed.
Permanent Link: http://hdl.handle.net/11104/0124431