Learning of Phase-Amplitude-Type Complex-Valued Neural Networks with Application to Signal Coherence

2017 ◽  
pp. 91-99 ◽  
Author(s):  
Rongrong Wu ◽  
He Huang ◽  
Tingwen Huang
Keyword(s):  
Neural Networks ◽  
Type Complex ◽  
Phase Amplitude ◽  
Complex Valued

scholarly journals Global Exponential Stability of Periodic Solution for Neutral-Type Complex-Valued Neural Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Song Guo ◽  
Bo Du
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Periodic Solutions ◽  
Global Exponential Stability ◽  
Neutral Type ◽  
Sufficient Conditions ◽  
Mawhin’S Continuation Theorem ◽  
Type Complex ◽  
Existence Of Periodic Solutions ◽  
Complex Valued

This paper deals with a class of neutral-type complex-valued neural networks with delays. By means of Mawhin’s continuation theorem, some criteria on existence of periodic solutions are established for the neutral-type complex-valued neural networks. By constructing an appropriate Lyapunov-Krasovskii functional, some sufficient conditions are derived for the global exponential stability of periodic solutions to the neutral-type complex-valued neural networks. Finally, numerical examples are given to show the effectiveness and merits of the present results.

scholarly journals Sampling-Based Event-Triggered Control for Neutral-Type Complex-Valued Neural Networks with Partly Unknown Markov Jump and Time-Varying Delay

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Zhen Wang ◽  
Lianglin Xiong ◽  
Haiyang Zhang ◽  
Yingying Liu
Keyword(s):  
Neural Networks ◽  
Neutral Type ◽  
Markov Jump ◽  
Stochastic Stabilization ◽  
Time Varying Delay ◽  
Type Complex ◽  
The Stability ◽  
First Time ◽  
Complex Valued ◽  
Event Triggered

This work is devoted to studying the stochastic stabilization of a class of neutral-type complex-valued neural networks (CVNNs) with partly unknown Markov jump. Firstly, in order to reduce the conservation of our stability conditions, two integral inequalities are generalized to the complex-valued domain. Secondly, a state-feedback controller is designed to investigate the stability of the neutral-type CVNNs with H ∞ performance, making the stability problem a further extension, and then, the stabilization of the CVNNs with H ∞ performance is investigated through a sampling-based event-triggered (SBET) control for the first time that the transmission event is not triggered except when it violates the event-triggered condition. Finally, two examples are given to illustrate the validity and correctness of our obtained theorems.

scholarly journals Finite-time projective synchronization of stochastic complex-valued neural networks with probabilistic time-varying delays

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Meng Hui ◽  
Jiahuang Zhang ◽  
Jiao Zhang ◽  
Herbert Ho-Ching Iu ◽  
Rui Yao ◽  
...  
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Projective Synchronization ◽  
Time Varying ◽  
Complex Valued
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