Stochastic Exponential Robust Stability of Delayed Complex-Valued Neural Networks With Markova Jumping Parameters

Mean Square Exponential Stability of Stochastic Complex‐Valued Neural Networks with Mixed Delays

“…In [18, 20-22, 33, 40], the authors investigated some interval neural networks in complex number domain. However, the stochastic disturbances were not considered in [18,[20][21][22] and the continuously distributed delays were not considered in [33,40].…”

“…In fact, most real models of neural networks are affected by many external and internal perturbations which are of great uncertainty, such as impulsive disturbances [5,[9][10][11][12][13][14][15], Markovian jumping parameters [16][17][18][19], and parameter uncertainties [20][21][22]. As Haykin [23] points out, in real nervous systems, synaptic transmission is a noisy process brought on by random fluctuations from the release of neurotransmitters and other probabilistic causes.…”

Robust Exponential Stability of Switched Complex‐Valued Neural Networks with Interval Parameter Uncertainties and Impulses

“…It is of great importance to study complex-valued neural networks because of their extensive application in many fields, such as filtering, speech synthesis, remote sensing, signal processing, and others, which cannot be analyzed comprehensively with only their real-valued counterparts [1,2]. Complex-valued neural networks are not only the simple extensions of real-valued systems due to their more complicated properties and research methods for dynamic behavior analysis, including stability, synchronization, and periodicity of system states.…”

“…This usually obligates neural networks to exhibit a special characteristic, network mode switching. Modeling this behavior by using the technique of the Markov process [2] or the switched system [18,19] is more natural and generally accepted in the practical application of neural networks. However, the stability results proposed in [17][18][19][20][21][22][23][24][25][26][27] are only suitable to neural networks defined in the real number domain.…”

Robust Exponential Stability Analysis of Switched Neural Networks with Interval Parameter Uncertainties and Time Delays

“…Furthermore, from the point of view of control, multicontroller switching is an effective way to deal with complex systems. It is well-known that time delays are inevitable in a practical control design which usually leads to unsatisfactory performances and the stability of the dynamic systems may even be destroyed with the increase of delays [30][31][32][33][34][35]. Attributing to the interaction among the discrete dynamics, continuous dynamics, and time delays, the behaviors of delayed SNNs are very complicated.…”