Abstract
Gated recurrent unit (GRU) is a variant of recurrent neural network (RNN), which is widely used in applications and tasks related to sequence data processing. However, traditional GRU networks based on von Neumann computing construction, have been facing challenges such as big data dimension and high real-time requirements. Meanwhile, limited internal storage resources and external storage bandwidth have jointly limited the overall performance of hardware implementation of GRU networks. Based on these, a compact scheme for the hardware circuit design of memristor-based GRU network is presented, along with the concrete circuit design of nonlinear activation and the linear matrix operation. The entire scheme is validated by the application of the Lithium ion battery state of charge (SOC) estimation. This work is expected to integrate the neuromorphic electronics and battery management systems, and further promote the development of electric vehicles in smart cities.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
