基于CNN的FPAA混沌发生器实现

2017 25th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2017-05-15 DOI:10.1109/SIU.2017.7960281

Enis Günay, Kenan Altun

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引用次数: 1

摘要

近年来，现场可编程模拟阵列(FPAAs)以其灵活的结构和模拟输出能力在可编程和可重构硬件中备受关注。为此，在FPAA平台上实现了一种基于细胞神经网络(CNN)的混沌发生器，该混沌发生器采用离散电路元件实现。将实验结果与数值结果和离散结果进行了比较。

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FPAA implementation of CNN based chaos generator

Recent times Field Programmable Analog Arrays (FPAAs) attracts attention among the reprogrammable and reconfigurable hardwares because of their flexible structure and analog outputs. Thus, a Celluar Neural Network (CNN) based chaos generator, which was realized by using discrete circuit elements, is reactualized in FPAA platform. Experimental results are compared with numerical results and the discrete ones.

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2017 25th Signal Processing and Communications Applications Conference (SIU)

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