Recurrent Neural Networks are in the scope of the machine learning community for many years. In the current paper we discuss the Historical Consistent Recurrent Neural Network and its extension to the complex valued case. We give some insights into complex valued back propagation and its application to the complex valued recurrent neural network training. Finally we present the results for the ...

Abstract: novel multiple-valued logic clock converters using artificial neural network are proposed. Based on a set of novel neural clock base converters, an essential part of the creative solution to the multiple-valued logic dual-clock or multi-clock circuit synchronization problem is presented in this paper. The multiple-valued logic neuron clock converters are planned to be useful in the mu...

We generalize the classical universal approximation theorem for neural networks to case of complex-valued networks. Precisely, we consider feedforward with a complex activation function σ:C→C in which each neuron performs operation CN→C,z↦σ(b+wTz) weights w∈CN and bias b∈C, σ applied componentwise. completely characterize those functions associated have property, meaning that they can uniformly...

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In this paper, the synchronization problem of fractional-order complex-valued neural networks with discrete and distributed delays is investigated. Based on the adaptive control and Lyapunov function theory, some sufficient conditions are derived to ensure the states of two fractional-order complex-valued neural networks with discrete and distributed delays achieve complete synchronization rapi...

Recurrent Neural Networks were invented a long time ago, and dozens of different architectures have been published. In this paper we generalize recurrent architectures to a state space model, and we also generalize the numbers the network can process to the complex domain. We show how to train the recurrent network in the complex valued case, and we present the theorems and procedures to make t...

In this paper, the synchronization problem for a class of discrete-time complex-valued neural networks with time-varying delays is investigated. Compared with the previous work, the time delay and parameters are assumed to be time-varying. By separating the real part and imaginary part, the discrete-time model of complex-valued neural networks is derived. Moreover, by using the complex-valued L...