STAVES: Speedy tensor-aided Volterra-based electronic simulator

• Main Authors: Xiong, Xiaoyan Y. Z. (Author), Batselier, Kim (Author), Jiang, Lijun (Author), Wong, Ngai (Author), Liu, Haotian (Contributor), Daniel, Luca (Contributor), Wong, Ngai Chuen (Contributor)
• Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Research Laboratory of Electronics (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE), 2017-07-25T18:21:33Z.
• Subjects: Article
• Online Access: Get fulltext

Volterra series is a powerful tool for black-box macro-modeling of nonlinear devices. However, the exponential complexity growth in storing and evaluating higher order Volterra kernels has limited so far its employment on complex practical applications. On the other hand, tensors are a higher order generalization of matrices that can naturally and efficiently capture multi-dimensional data. Significant computational savings can often be achieved when the appropriate low-rank tensor decomposition is available. In this paper we exploit a strong link between tensors and frequency-domain Volterra kernels in modeling nonlinear systems. Based on such link we have developed a technique called speedy tensor-aided Volterra-based electronic simulator (STAVES) utilizing high-order Volterra transfer functions for highly accurate time-domain simulation of nonlinear systems. The main computational tools in our approach are the canonical tensor decomposition and the inverse discrete Fourier transform. Examples demonstrate the efficiency of the proposed method in simulating some practical nonlinear circuit structures.
Research Grants Council (Hong Kong, China) (Projects HKU 718213E)
Research Grants Council (Hong Kong, China) (Projects HKU 71208514)
University of Hong Kong. University Research Committee