Sentence examples for based recurrent neural networks from inspiring English sources
By considering the nonlinear and dynamic dependency relationships between articulatory movements and acoustic signals, this study adopts bidirectional long short-term memory (BLSTM) based recurrent neural networks (RNN) for the articulatory-to-acoustic conversion.
This paper deals with the problem of global exponential synchronization of a class of memristor-based recurrent neural networks with time-varying delays based on the fuzzy theory and Lyapunov method.
By using an impulsive delayed differential inequality and Lyapunov function, several exponential and uniform stability criteria of the impulsive delayed memristor-based recurrent neural networks are obtained.
In this paper, finite-time synchronization (FTS) of memristor-based recurrent neural networks (MNNs) with time-varying delays is investigated by designing a new switching controller.
This paper is concerned with the problem of μ-stability analysis of memristor-based recurrent neural networks with the effects of bounded and unbounded leakage time-varying delays.
The paper presents theoretical results on the global exponential periodicity and stability of a class of memristor-based recurrent neural networks with multiple delays.
Based on the drive-response concept, the stochastic differential inclusions theory and the Lyapunov functional method with the impulsive delay differential inequality technique was established to guarantee the impulsive synchronization of memristor-based recurrent neural networks with stochastic effects.
