Memristive LSTM architectures

Kazybek Adam, Kamilya Smagulova, Alex James Pappachen

Research output: Chapter in Book/Report/Conference proceedingChapter


Mainstream standard LSTM architecture that is currently used in Tensorflow library does not use the original architecture. In fact, there are many different architectures of LSTM. One of the more widely used architectures of LSTM is Coupled Input and Forget Gate (CIFG). It is known more as Gated Recurrent Units (GRU). This chapter will introduce the existing architectures of LSTM. Further it will present memristive LSTM architecture implementation in analog hardware. The implementation realizes the standard version of LSTM architecture. Other architecture variations can be easily constructed by rearranging, adding, and deleting the existing analog circuit parts; and adding extra crossbar rows.

Original languageEnglish
Title of host publicationModeling and Optimization in Science and Technologies
PublisherSpringer Verlag
Number of pages13
Publication statusPublished - Jan 1 2020

Publication series

NameModeling and Optimization in Science and Technologies
ISSN (Print)2196-7326
ISSN (Electronic)2196-7334


ASJC Scopus subject areas

  • Modelling and Simulation
  • Medical Assisting and Transcription
  • Applied Mathematics

Cite this

Adam, K., Smagulova, K., & James Pappachen, A. (2020). Memristive LSTM architectures. In Modeling and Optimization in Science and Technologies (pp. 155-167). (Modeling and Optimization in Science and Technologies; Vol. 14). Springer Verlag.