Hybrid Time-Domain Behavior Model Based on Neural Differential Equations and RNNs

• URL: http://arxiv.org/abs/2503.22313v1
• Date: Fri, 28 Mar 2025 10:42:52 GMT
• Title: Hybrid Time-Domain Behavior Model Based on Neural Differential Equations and RNNs
• Authors: Zenghui Chang, Yang Zhang, Hu Tan, Hong Cai Chen,
• Abstract summary: This paper presents a novel continuous-time domain hybrid modeling paradigm.<n>It integrates neural network differential models with recurrent neural networks (RNNs), creating NODE-RNN and NCDE-RNN models.<n>Theoretical analysis shows that this hybrid model has mathematical advantages in event-driven dynamic mutation response and propagation stability.
• Score: 3.416692407056595
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Nonlinear dynamics system identification is crucial for circuit emulation. Traditional continuous-time domain modeling approaches have limitations in fitting capability and computational efficiency when used for modeling circuit IPs and device behaviors.This paper presents a novel continuous-time domain hybrid modeling paradigm. It integrates neural network differential models with recurrent neural networks (RNNs), creating NODE-RNN and NCDE-RNN models based on neural ordinary differential equations (NODE) and neural controlled differential equations (NCDE), respectively.Theoretical analysis shows that this hybrid model has mathematical advantages in event-driven dynamic mutation response and gradient propagation stability. Validation using real data from PIN diodes in high-power microwave environments shows NCDE-RNN improves fitting accuracy by 33\% over traditional NCDE, and NODE-RNN by 24\% over CTRNN, especially in capturing nonlinear memory effects.The model has been successfully deployed in Verilog-A and validated through circuit emulation, confirming its compatibility with existing platforms and practical value.This hybrid dynamics paradigm, by restructuring the neural differential equation solution path, offers new ideas for high-precision circuit time-domain modeling and is significant for complex nonlinear circuit system modeling.

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