Modeling Transient Time-Dependent Behavior of a Digital Phase-Locked Loop Circuit Using Gated Recurrent Neural Network

S. F. Mousavi ¹ ( Dept. of Elec. Eng., Yazd University, Yazd, Iran )
S. A. Sadrossadat ² ( Dept. of Comp. Eng., Yazd University, Yazd, Iran )
A. Moftakharzadeh ³ ( Dept. of Elec. Eng., Yazd University, Yazd, Iran )

Submited date : 2024-09-21 Accepted date : 2025-08-17

Keywords: DPLL circuit, nonlinear circuit dynamic response modeling, gradient vanishing, GRU neural network,

Abstract :

Nowadays, neural networks are a powerful tool for modeling complex and nonlinear circuits. In this paper, the transient time-dependent behavior of a digital phase-locked loop circuit is modeled using two time-dependent neural network models. Modeling with an RNN (Recurrent Neural Network) faces the challenge of gradient vanishing during the training phase and does not perform well in terms of speed and accuracy. To achieve desirable training and testing error values, the GRU (Gated Recurrent Unit) neural network is used for modeling. This network, due to the presence of update and reset gates, can overcome the gradient vanishing problem and provide acceptable modeling results. A comparison of the results of these two networks shows that the method based on the gated neural network structure has superior capability and performance in modeling the behavior of nonlinear circuits.

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