Adaptive control

Algorithm

Control (management)

Engineering

Algebraic number

Quantization (signal processing)

Coupling (piping)

Stability (learning theory)

Computer science

Mechanical engineering

Mathematics

Synchronization (alternating current)

Mathematical analysis

Artificial intelligence

Combinatorics

Logarithm

Topology (electrical circuits)

Control theory (sociology)

Artificial neural network

Lyapunov stability

Machine learning

IEEE Transactions on Neural Networks and Learning Systems

This article focuses on the adaptive synchronization for a class of fractional-order coupled neural networks (FCNNs) with output coupling. The model is new for output coupling item in the FCNNs that treat FCNNs with state coupling as its particular case. Novel adaptive output controllers with logarithm quantization are designed to cope with the stability of the fractional-order error systems for the first attempt, which is also an effective way to synchronize fractional-order complex networks. Based on fractional-order Lyapunov functionals and linear matrix inequalities (LMIs) method, sufficient conditions rather than algebraic conditions are built to realize the synchronization of FCNNs with output coupling. A numerical simulation is put forward to substantiate the applicability of our results.

Adaptive Synchronization of Fractional-Order Output-Coupling Neural Networks via Quantized Output Control