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Institute of Electrical and Electronics Engineers, IEEE Transactions on Neural Networks and Learning Systems, 6(29), p. 2645-2650, 2018

DOI: 10.1109/tnnls.2017.2697386

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Memcomputing Numerical Inversion with Self-Organizing Logic Gates

Journal article published in 2016 by Haik Manukian ORCID, Fabio L. Traversa, Massimiliano Di Ventra ORCID
This paper is available in a repository.
This paper is available in a repository.

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Abstract

We propose to use Digital Memcomputing Machines (DMMs), implemented with self-organizing logic gates (SOLGs), to solve the problem of numerical inversion. Starting from fixed-point scalar inversion we describe the generalization to solving linear systems and matrix inversion. This method, when realized in hardware, will output the result in only one computational step. As an example, we perform simulations of the scalar case using a 5-bit logic circuit made of SOLGs, and show that the circuit successfully performs the inversion. Since this type of numerical inversion can be implemented by DMM units in hardware, it is scalable, and thus of great benefit to any real-time computing application.