DocumentCode :
1814768
Title :
Monotonicity of semiflows generated by cooperative delayed full-range CNNs
Author :
Marco, Mauro Di ; Forti, Mauro ; Grazzini, Massimo ; Pancioni, Luca
Author_Institution :
Dept. of Inf. Eng., Univ. of Siena, Siena, Italy
fYear :
2012
fDate :
29-31 Aug. 2012
Firstpage :
1
Lastpage :
6
Abstract :
The paper considers the full-range (FR) model of cellular neural networks (CNNs) with ideal hard-limiter non-linearities that limit the allowable range of the neuron state variables. It is also supposed that there is a concentrated delay (D) in the neuron interconnections. Due to the presence of multivalued nonlinearities the D-FRCNN model is mathematically described by a retarded differential inclusion. The main result is a rigorous proof that, in the case of nonsymmetric cooperative (nonnegative) interconnections, and delayed interconnections, the semiflow generated by D-FRCNNs is monotone, and that monotonicity implies some basic restrictions on the long-term behavior of the solutions. The result is compared with recent results in the literature on semiflows generated by cooperative standard CNNs, with and without delays.
Keywords :
cellular neural nets; delays; differential equations; set theory; D-FRCNN model; cellular neural network; concentrated delay; convex set; cooperative delayed full-range CNN; delayed interconnection; full-range model; ideal hard-limiter nonlinearity; multivalued nonlinearity; neuron interconnection; neuron state variable; nonnegative interconnection; nonsymmetric cooperative interconnection; retarded differential inclusion; semiflow monotonicity; Convergence; Delay; Differential equations; Hypercubes; Mathematical model; Neurons; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cellular Nanoscale Networks and Their Applications (CNNA), 2012 13th International Workshop on
Conference_Location :
Turin
ISSN :
2165-0160
Print_ISBN :
978-1-4673-0287-6
Type :
conf
DOI :
10.1109/CNNA.2012.6331406
Filename :
6331406
Link To Document :
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