Thin-film transistor for temporal self-adaptive reservoir computing with closed-loop architecture

Authors:
raw_author_name: Haozhang Yang
raw_affiliation_string: Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China.; School of Integrated Circuits, Peking University, Beijing 100871, China.
raw_author_name: Ruiyi Li
raw_affiliation_string: Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China.; School of Integrated Circuits, Peking University, Beijing 100871, China.
raw_author_name: Guihai Yu
raw_affiliation_string: Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China.; School of Integrated Circuits, Peking University, Beijing 100871, China.
raw_author_name: Yizhou Zhang
raw_affiliation_string: Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China.; School of Integrated Circuits, Peking University, Beijing 100871, China.
raw_author_name: Junchen Dong
raw_affiliation_string: Beijing Information Science and Technology University, Beijing 100192, China.
raw_author_name: Dedong Han
raw_affiliation_string: Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China.; School of Integrated Circuits, Peking University, Beijing 100871, China.
raw_author_name: Zheng Zhou
raw_affiliation_string: Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China.; School of Integrated Circuits, Peking University, Beijing 100871, China.
raw_author_name: Peng Huang
raw_affiliation_string: Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China.; School of Integrated Circuits, Peking University, Beijing 100871, China.
raw_author_name: Lifeng Liu
raw_affiliation_string: Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China.; School of Integrated Circuits, Peking University, Beijing 100871, China.
raw_author_name: Jinfeng Kang
raw_affiliation_string: Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, China.; School of Integrated Circuits, Peking University, Beijing 100871, China.

Abstract: Reservoir computing is a powerful neural network-based computing paradigm for spatiotemporal signal processing. Recently, physical reservoirs have been explored based on various electronic devices with outstanding efficiency. However, the inflexible temporal dynamics of these reservoirs have posed fundamental restrictions in processing spatiotemporal signals with various timescales. Here, we fabricated thin-film transistors with controllable temporal dynamics, which can be easily tuned with electrical operation signals and showed excellent cycle-to-cycle uniformity. Based on this, we constructed a temporal adaptive reservoir capable of extracting temporal information of multiple timescales, thereby achieving improved accuracy in the human-activity-recognition task. Moreover, by leveraging the former computing output to modify the hyperparameters, we constructed a closed-loop architecture that equips the reservoir computing system with temporal self-adaptability according to the current input. The adaptability is demonstrated by accurate real-time recognition of objects moving at diverse speed levels. This work provides an approach for reservoir computing systems to achieve real-time processing of spatiotemporal signals with compound temporal characteristics.