On the Effect of Analog Noise in Discrete-Time Analog Computations
Abstract
We introduce a model for analog computation with discrete time in the
presence of analog noise that is flexible enough to cover the most important
concrete cases, such as noisy analog neural nets and networks
of spiking neurons. This model subsumes the classical model for digital
computation in the presence of noise. We show that the presence of
arbitrarily small amounts of analog noise reduces the power of analog
computational models to that of finite automata, and we also prove a new
type of upper bound for the VC-dimension of computational models with
analog noise.
Main Authors
Format
Articles
Research article
Published
1998
Series
Subjects
Publication in research information system
Publisher
MIT Press
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201807173590Use this for linking
Review status
Peer reviewed
ISSN
0899-7667
DOI
https://doi.org/10.1162/089976698300017359
NB.
Published also in Advances in Neural Information Processing Systems 9 edited by M.C. Mozer and M.I. Jordan and T. Petsche, from the conference, "Neural Information Processing Systems 1996 (NIPS 1996), MIT Press. ISSN 1049-5258; ISBN 0-262-10065-7
Please see also
http://papers.nips.cc/paper/1213-on-the-effect-of-analog-noise-in-discrete-time-analog-computations
Language
English
Published in
Neural Computation
Citation
- Maass, W., & Orponen, P. (1998). On the Effect of Analog Noise in Discrete-Time Analog Computations. Neural Computation, 10(5), 1071-1095. https://doi.org/10.1162/089976698300017359
License
Copyright© 1998 Massachusetts Institute of Technology