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Memristive self-learning logic circuit with application to encoder and decoder

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Abstract

Different logic circuits based on memristors have been extensively investigated. However, most of these circuits require accurate initialization. A self-learning logic circuit based on mermristors that can achieve various logic gates without initialization is proposed in this paper. Three functional blocks, including a sum block, a learning block, and a compare block, are elaborately designed in the proposed logic circuit. Programmable switches in the sum and compare blocks enable the circuit to perform various logic gates, such as Boolean, IMPLY, and random logical combinations. In these various logical operations, the learning block can automatically obtain different memristance states. The aforementioned logic operations can easily be extended to multi-fan-in logic and logical cascade operations. Circuit designs of an encoder and decoder are considered as application examples. Finally, PSpice simulation results of the logic circuits and extended applications are provided. Simulation results indicate that the proposed circuit can effectively perform different logic operations and exhibits excellent robustness to circuit device variations.

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Acknowledgements

The work was supported by the Fundamental Research Funds for the Central Universities (No. 531118010418) and the Open Fund Project of Key Laboratory in Hunan Universities (No. 19K022) and the National Nature Science Foundation of China (No. 61674054) and the Natural Science Foundation of Hunan Province of China (No. 2017JJ2049).

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  1. College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, China

    Qinghui Hong, Zirui Shi, Jingru Sun & Sichun Du

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  1. Qinghui Hong
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  2. Zirui Shi
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Correspondence to Jingru Sun.

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Hong, Q., Shi, Z., Sun, J. et al. Memristive self-learning logic circuit with application to encoder and decoder. Neural Comput & Applic 33, 4901–4913 (2021). https://doi.org/10.1007/s00521-020-05281-z

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