Counting with Analog Neurons
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F19%3A00502583" target="_blank" >RIV/67985807:_____/19:00502583 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-30487-4_31" target="_blank" >http://dx.doi.org/10.1007/978-3-030-30487-4_31</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-30487-4_31" target="_blank" >10.1007/978-3-030-30487-4_31</a>
Alternative languages
Result language
angličtina
Original language name
Counting with Analog Neurons
Original language description
We refine the analysis of binary-state neural networks with alpha extra analog neurons (alpha-ANNs). For rational weights, it has been known that online 1ANNs accept context-sensitive languages including examples of non-context-free languages, while offline 3ANNs are Turing complete. We now prove that the deterministic (context-free) language containing the words of n zeros followed by n ones, cannot be recognized offline by any 1ANN with real weights. Hence, the offline 1ANNs are not Turing complete. On the other hand, we show that any deterministic language can be accepted by a 2ANN with rational weights. Thus, two extra analog units can count to any number which is not the case of one analog neuron.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA19-05704S" target="_blank" >GA19-05704S: FoNeCo: Analytical Foundations of Neurocomputing</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation. Proceedings, Part I
ISBN
978-3-030-30486-7
ISSN
0302-9743
e-ISSN
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Number of pages
12
Pages from-to
389-400
Publisher name
Springer
Place of publication
Cham
Event location
Munich
Event date
Sep 17, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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