Название: Complex-Valued Neural Networks Systems With Time Delay: Stability Analysis and Anti-Synchronization Control
Автор: Ziye Zhang, Zhen Wang, Jian Chen, Chong Lin
Издательство: Springer
Год: 2022
Страниц: 236
Язык: английский
Формат: pdf (true)
Размер: 10.19 MB
In recent years, with the emergence of new scientific and technological methods, complex signals have appeared in radar, imaging and other fields, which makes the state variables of the controlled system extended from the real number domain to the complex number one. As a result, the complex-valued neural networks (CVNNs) model has entered scholars’ vision. It is a kind of network that processes information with complex parameters and variables in a complex field. Compared with real-valued neural networks, on one hand, the neuron state, activation function and weight of complex-valued ones are complex-valued, which can directly process two-dimensional data. On the other hand, CVNNs model is more efficient, faster and has better generalization ability. In particular, it can deal with many problems that cannot be solved by real-valued neural networks. So far, CVNNs have been widely used in many biological and engineering fields, such as image processing, optoelectronics, pattern recognition, signal processing and so on. Moreover, time delay is inevitable in the actual system, which has a very significant impact on the system. It often leads to the delay in information transmission, affects the performance of the system and even causes instability in the system. Therefore, it is of great significance to make a profound study of CVNNs model with time delay.
Название: Классические ортогональные многочлены
Название: Advances in Mathematical Analysis and its Applications
