Second-order Time Delay Reservoir Computing for Nonlinear Time Series Problems

Shi，Xinming1,2; Gao，Jiashi1; Minku，Leandro L.2; Yu，James J.Q.1; Yao，Xin1,2

10.1109/SSCI50451.2021.9659913

2021

IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

978-1-7281-9049-5

2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings

1-8

5-7 Dec. 2021

Orlando, FL, USA

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

Time Delay Reservoir (TDR) can exhibit effects of high dimensionality and short-term memory based on delay differential equations (DDEs), as well as having hardware-friendly characteristics. However, the predictive performance and memory capacity of the standard TDRs are still limited, and dependent on the hyperparameter of the oscillation function. In this paper, we first analyze these limitations and their corresponding reasons. We find that the reasons for such limitations are fused by two aspects, which are the trade-off between the strength of self-feedback and neighboring-feedback caused by neuron separation, as well as the unsuitable order setting of the nonlinear function in DDE. Therefore, we propose a new form of TDR with second-order time delay to overcome such limitations, incurring a more flexible time-multiplexing. Moreover, a parameter-free nonlinear function is introduced to substitute the classic Mackey-Glass oscillator, which alleviates the problem of parameter dependency. Our experiments show that the proposed approach achieves better predictive performance and memory capacity compared with the standard TDR. Our proposed model also outperforms six other existing approaches on both time series prediction and recognition tasks.

Multiplexing Delay effects Time series analysis Neurons Predictive models Reservoirs Data models

第一

英语

CPCI-S ; EI

Computer Science ; Engineering ; Operations Research & Management Science ; Mathematics

Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science ; Mathematics, Applied

WOS:000824464300094

20221011760948

Differential equations ; Economic and social effects ; Functions ; Time delay ; Time series

Electronic Circuits:713 ; Pulse Circuits:713.4 ; Mathematics:921 ; Calculus:921.2 ; Mathematical Statistics:922.2 ; Social Sciences:971

2-s2.0-85125767160

Scopus

1.Southern University of Science and Technology,Department of Computer Science and Engineering,Shenzhen,China
2.School of Computer Science,University of Birmingham,Birmingham,United Kingdom

Shi，Xinming,Gao，Jiashi,Minku，Leandro L.,et al. Second-order Time Delay Reservoir Computing for Nonlinear Time Series Problems[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2021:1-8.