Turing Computation with Neural Networks Composed of Synfire Rings

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F22%3A00562577" target="_blank" >RIV/67985807:_____/22:00562577 - isvavai.cz</a>

Result on the web

<a href="https://dx.doi.org/10.1109/IJCNN55064.2022.9892332" target="_blank" >https://dx.doi.org/10.1109/IJCNN55064.2022.9892332</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IJCNN55064.2022.9892332" target="_blank" >10.1109/IJCNN55064.2022.9892332</a>

Result language

angličtina

Original language name

Turing Computation with Neural Networks Composed of Synfire Rings

Original language description

Synfire rings are fundamental neural circuits capable of conveying self-sustained activities in a robust and temporally precise manner. We propose a Turing-complete paradigm for neural computation based on synfire rings. More specifically, we provide an algorithmic procedure which, for any fixed-space Turing machine, builds a corresponding Boolean neural network composed of synfire rings capable of simulating it. As a consequence, any fixed-space Turing machine with tapes of length N can be simulated in linear time by some Boolean neural network composed of O(N) rings and cells. The construction can naturally be extended to general Turing machines. Therefore, any Turing machine can be simulated in linear time by some Boolean neural network composed of infinitely many synfire rings. The linear time simulation relies on the possibility to mimic the behavior of the machines. In the long term, these results might contribute to the realization of biological neural computers.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA22-02067S" target="_blank" >GA22-02067S: AppNeCo: Approximate Neurocomputing</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

2022 International Joint Conference on Neural Networks (IJCNN) Proceedings

ISBN

978-1-7281-8671-9

ISSN

—

e-ISSN

—

Number of pages

8

Pages from-to

—

Publisher name

IEEE

Place of publication

Piscataway

Event location

Padua

Event date

Jul 18, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000867070903092