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In this paper CNN modeling of tsunami waves is presented. Two models are studied: two-component Camassa-Holm type equation is studied and generalized KdV equation. For these cases CNN models are constructed and traveling wave solutions are obtained theoretically and via simulations. New type of traveling wave solutions are introduced — peak type, called peakon. Discussion and example of tsunami waves...
We numerically investigated the dynamics of a new reaction-diffusion-type excitable medium where the diffusion coefficient is represented by memristive dynamics. This type of a medium consists of an array of excitable Oregonators, and each Oregonator is locally coupled with other Oregonators via memristors, which were claimed to be the fourth circuit element exhibiting a relationship between flux...
We present a deterministic continuous-time recurrent neural network similar to CNN models, which can solve Boolean satisfiability (k-SAT) problems without getting trapped in non-solution fixed points. The model can be implemented by analog circuits, in which case the algorithm would take a single operation: the template (connection weights) is set by the k-SAT instance and starting from any initial...
Time-Derivative CNNs (TDCNNs) have been recently proposed as a novel paradigm realizing spatiotemporal transfer functions for linear filtering. Their dynamics is usually simulated with SIMULINK because VLSI chips are still in the preliminary phase. In order to make TDCNNs available to a larger audience, we present here their implementation on a Xilinx Spartan-6 FPGA. The results concerning an 8×8...
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