scholarly journals On the Effect of Topology on Learning and Generalization in Random Automata Networks

2000 ◽  
Author(s):  
Alireza Goudarzi
Keyword(s):  
Automata Networks ◽  
Random Automata

scholarly journals Computational capabilities of random automata networks for reservoir computing

2013 ◽  
Vol 87 (4) ◽  
Author(s):  
David Snyder ◽  
Alireza Goudarzi ◽  
Christof Teuscher
Keyword(s):  
Reservoir Computing ◽  
Automata Networks ◽  
Random Automata

On the Use of Spin Glass Concepts in Random Automata Networks

1988 ◽  
Vol 6 (4) ◽  
pp. 297-300 ◽  
Author(s):  
E. N Miranda ◽  
N Parga
Keyword(s):  
Spin Glass ◽  
Automata Networks ◽  
Random Automata

Learning, generalisation, and functional entropy in random automata networks

2014 ◽  
Vol 7 (3) ◽  
pp. 295
Author(s):  
Alireza Goudarzi ◽  
Christof Teuscher ◽  
Natali Gulbahce ◽  
Thimo Rohlf
Keyword(s):  
Automata Networks ◽  
Random Automata

scholarly journals RANDOMIZED CELLULAR AUTOMATA

2007 ◽  
Vol 18 (08) ◽  
pp. 1303-1312 ◽  
Author(s):  
NINO BOCCARA
Keyword(s):  
Cellular Automata ◽  
Cellular Automaton ◽  
Directed Graphs ◽  
A Priori ◽  
One Dimensional ◽  
Automata Networks ◽  
Random Automata

We define and study a few properties of a class of random automata networks. While regular finite one-dimensional cellular automata are defined on periodic lattices, these automata networks, called randomized cellular automata, are defined on random directed graphs with constant out-degrees and evolve according to cellular automaton rules. For some families of rules, a few typical a priori unexpected results are presented.

scholarly journals Multipreconditioned GMRES for simulating stochastic automata networks

2018 ◽  
Vol 16 (1) ◽  
pp. 986-998
Author(s):  
Chun Wen ◽  
Ting-Zhu Huang ◽  
Xian-Ming Gu ◽  
Zhao-Li Shen ◽  
Hong-Fan Zhang ◽  
...  
Keyword(s):  
Steady State ◽  
Probability Distribution ◽  
Linear Systems ◽  
Iterative Methods ◽  
Communication Systems ◽  
Queueing Systems ◽  
Steady State Probability ◽  
Stochastic Automata ◽  
Automata Networks ◽  
Generator Matrices

AbstractStochastic Automata Networks (SANs) have a large amount of applications in modelling queueing systems and communication systems. To find the steady state probability distribution of the SANs, it often needs to solve linear systems which involve their generator matrices. However, some classical iterative methods such as the Jacobi and the Gauss-Seidel are inefficient due to the huge size of the generator matrices. In this paper, the multipreconditioned GMRES (MPGMRES) is considered by using two or more preconditioners simultaneously. Meanwhile, a selective version of the MPGMRES is presented to overcome the rapid increase of the storage requirements and make it practical. Numerical results on two models of SANs are reported to illustrate the effectiveness of these proposed methods.

scholarly journals Iterative disaggregation for a class of lumpable discrete-time stochastic automata networks

2003 ◽  
Vol 53 (1) ◽  
pp. 43-69 ◽  
Author(s):  
Oleg Gusak ◽  
Tuğrul Dayar ◽  
Jean-Michel Fourneau
Keyword(s):  
Discrete Time ◽  
Stochastic Automata ◽  
Automata Networks

Graphs and Stochastic Automata Networks

1995 ◽  
pp. 217-235 ◽  
Author(s):  
Jean-Michel Fourneau ◽  
Franck Quessette
Keyword(s):  
Stochastic Automata ◽  
Automata Networks
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