FPGA Realization and Lyapunov–Krasovskii Analysis for a Master-Slave Synchronization Scheme Involving Chaotic Systems and Time-Delay Neural Networks

Table 3

Some synchronization schemes proposed in the literature.

Reference	Approach	Synchronization scheme	Implementation
[40]	Extended Kalman filter	Drive-response between Genesio–Tesi multiscroll and recurrent neural network	Digital: Arduino uno microcontroller
[41]	Inverse optimality	Drive-response between chaotic time-delay recurrent neural networks	None
[19]	V-stability and Lyapunov theory	Drive-response between a delayed recurrent neural network and a complex dynamical network	None
[42]	Quantized sliding-mode control	Drive-response between delayed memristive neural networks	None
[43]	Adaptive intermittent control	Drive-response between chaotic systems with time-varying delay	None
Proposed	Lyapunov–Krasovskii and Lur’e theory	Drive-response between Liu-delayed recurrent neural network and Genesio–Tesi and delayed recurrent neural networks	Digital: FPGA Xilinx Zynq-7000 XC7Z020