Chaotic attractors in delayed neural networks
By Hongtao Lu. 2002
364 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Cognitive Neuroscience, Computer Networks and Communications
View Paper: https://www.semanticscholar.org/paper/3b9f544c8545b96e791f202c8e4f542a1cfbba03
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In Computer Networks and Communications
Citations in the corpus
- Synchronization of Complex Dynamical Networks With Time-Varying Delays Via Impulsive Distributed Control (2010, background): “It is well known that the system (30) with above parameters is chaotic [41] (see Fig.”
- Global Synchronization of Linearly Hybrid Coupled Networks with Time-Varying Delay (2008, background): “Over the last few years, complex networks have received increasing attention from all fields of sciences and humanities [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40].”
- Global Synchronization of Coupled Delayed Neural Networks and Applications to Chaotic CNN Models (2004, background): “…the introduction of delays into neural networks makes their dynamical behaviors much more complicated, for example, there are strange attractors even in first-order continuous-time autonomous delayed Hopfied neural networks [Lu, 2002; Lu & He, 1996; Ruan et al., 2002; Zou & Nossek, 1993].”
- Global Synchronization in an Array of Delayed Neural Networks With Hybrid Coupling (2008, background): “For example, the chaotic behavior generated by one kind of recurrent NN has been found and investigated in [12]–[15].”
- Synchronization of delayed chaotic systems with parameter mismatches by using intermittent linear state feedback (2009, methodology): “Consider the neural oscillator described by the following delayed differential equation [35] ẋ(t) = −C1x(t) + A1f (x(t)) + B1f (x(t − 1)), (24) where”