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This proceeding is compiled from our previous works, where architecture of the Second-Generation Real-Time Cellular Neural Network (CNN) Processor (RTCNNP-v2) was proposed. The system is designed for applications where highresolution and high-speed is desired. The structure is fully-pipelined and the processing is real-time. Proposed structure is coded in VHDL and realized on two FPGA devices: one...
In this paper, a new Cellular Neural Network (CNN) structure for implementing two dimensional Gabor-type filters is proposed over our previous design. The structure is coded in VHDL and realized on a state of the art Altera Stratix IV 230 FPGA. The prototype supports Full-HD 1080p resolution and 60 Hz frame rate. One dedicated processor is used for each Euler iteration, where time step is taken as...
We describe the realization of a new experimental setup for the analysis and characterization of complex networks of Chua's circuits. It is characterized by full configurability of the node's parameters and the network structure (topology and link impedances), and designed for easy scalability to high number of nodes. The set-up is automated in terms of control of the network and data acquisition...
This paper presents a new approach to implement the dynamic reconfigurable logical systems based on Cellular Neural Networks (CNN), comparing with utilizing the chaos computing system, which is easier to implement in engineering applications and more stable. We provided and experimentally demonstrated the basic principle for obtaining a full-adder by using uncoupled CNN cells. The actual circuit to...
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