FPGA design of a digital circuit for estimating chaotic characteristics from approximated nonlinear functions

Abstract

In this paper, an FPGA circuit for estimating chaotic characteristics of unknown nonlinear systems is proposed. From particular solutions corresponding to chaotic signals of the unknown system, the proposed circuit approximates nonlinear functions. The approximation of these nonlinear functions are performed by using supervised learning. From the approximated functions, chaotic characteristics of the unknown system are estimated.An understanding of the behavior of unknown nonlinear system will be provided by uti lizing the estimated chaotic characteristics.The proposed circuit is implemented onto an FPGA by using Verilog-HDL. This implementation confirmed that the proposed circuit can achieve high-speed operation and low-cost development.

Suppression of time-delayed signature in chaotic signals based on optoelectronic hybrid feedbacks

“…Chaotic signals, referring to random and unpredictable signals, have been highlighted in several fields such as highresolution radar ranging [1][2][3], broadband secure communication [4][5][6], and random number generation [7][8][9]. In general, complex chaotic signals are generated by the electrical methods, such as the oscillation circuits [10][11] or the field programmable gate array [12][13]. However, suffered from the electrical bottleneck, chaotic signals generation based on the electrical methods are narrowband, which cannot meet the ever-increasing requirement of the high-resolution radar and the broadband secure communication.…”