Related Experiment Video
Updated: Jul 8, 2026

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
Published on: November 12, 2019
The antisynchronization of a class of chaotic delayed neural networks
1College of Communication and Control Engineering, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, People's Republic of China.
Abstract:
In this paper, the antisynchronization problems of a class of chaotic delayed neural networks are investigated. Some criteria of the antisynchronization of the chaotic delayed neural networks are established by using the linear matrix inequality and Lyapunov stability theory. These criteria not only improve and generalize some known results, but are also some less conservative conditions. Finally, two numerical examples and the corresponding numerical simulations are used to illustrate the effectiveness of the obtained results.
Related Concept Videos
Neural Circuits
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Linear time-invariant Systems
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be calculated...
Propagation of Action Potentials
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...
Antiarrhythmic Drugs: Class I Agents as Sodium Channel Blockers
Class 1A Antiarrhythmic Drugs: These drugs work by moderately blocking sodium channels,...
Classification of Systems-I
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
