Over the past two decades, complex network theory provided the ideal framework for
investigating the intimate relationships between the topological properties characterizing the …

The investigation of discrete memristive chaotic systems with complex dynamics has been
an interesting and meaningful research work. This paper is devoted to constructing a …

Both electric and chemical synapses play an important role in receiving and propagating
signals, and thus an isolated neuron and neurons in networks can be activated to trigger …

In this paper, a unified framework is proposed to address the synchronization problem of
memristor chaotic systems (MCSs) via the sliding-mode control method. By employing the …

The memristor is a fundamental two-terminal electrical component unique in that it
possesses the properties of non-linearity and memory, which are pervasive across natural …

When taking a memristor as a coupler to connect two memristive systems, the intricate initial
condition-dependent coexisting and synchronous behaviors could be achieved, which have …

The synchronization control problem is investigated for a class of discrete-time dynamical
networks with packet dropouts via a coding-decoding-based approach. The data is …

The nervous system is made up of various functional neurons, eg some neurons can percept
external optical signal while other neurons can detect the fluctuation of temperature, and …

A feasible neuron model can be effective to estimate the mode transition in neural activities
in a complex electromagnetic environment. When neurons are exposed to electromagnetic …

Memristor coupled neuronal networks can simulate the complex interactions between
neurons in biological neuronal networks. These capture the current and synaptic …