1,721,127 research outputs found
A New Synthesis Procedure for Associative Memories using Discrete-Time Cellular Neural Networks
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A Method for the Synchronization of hyperchaotic Circuits,
No full textIn this paper the Carroll-Pecora concept of chaotic system synchronization is extended to the synchronization of hyperchaotic circuits. A circuit exhibiting a hyperchaotic behavior is duplicated to generate two cascaded response subsystems, properly driven by synchronizing signals. Conditions for achieving synchronization are illustrated in detail. The proposed method is applied to two identical uniclirectionally coupled hyperchaotic Chua's circuits
Associative Memory Design using Discrete-time Second-Order Neural Networks with Local Interconnections
No full textIn this brief a design method for associative memories using a new model of discrete-time high-order neural networks which includes local interconnections among neurons is illustrated. The synthesis approach, which exploits the properties of pseudoinverse matrices, reveals flexible as it enables to choose the complexity of the associative memory to be designed that is, it can generate networks for associative memories with first-order and/or higher order interactions among neurons. The suggested technique preserves local interconnections among neurons, making feasible an implementation of such networks. Simulation results and comparisons among different neural architectures are reported to show the applicability of the proposed method
Complete practical synchronization of hyperchaotic circuits via a scalar signal
No full textIn this paper an approach to achieve a complete practical synchronization of hyperchaotic circuits with parameter mismatch via an impulsive scalar signal is presented. The chosen scalar signal is constituted by a sequence 'of samples of selected state variables alternatively transmitted for identical time frames. The approach is effectively applied to hyperchaotic circuits with parameter mismatch constituted by two bidirectionally coupled Chua's oscillators
Heteroassociative Memories via Cellular Neural Networks
No full textIn this paper a synthesis procedure for heteroassociative memories using Cellular Neural Networks (CNNs) is presented. The suggested method, by assuring the condition of symmetry of the interconnection matrix, guarantees the complete stability of the designed network, besides providing that all the stored patterns correspond to asymptotically stable equilibrium points. Numerical examples are carried out to show the behaviour of the designed memory with respect to input perturbations. Moreover, the storage capacity and the presence of spurious equilibria have been investigate
State space representation of interconnected power systems for dynamic interaction studies
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