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- Title
Biologically Plausible Boltzmann Machine.
- Authors
Berrones-Santos, Arturo; Bagnoli, Franco
- Abstract
The dichotomy in power consumption between digital and biological information processing systems is an intriguing open question related at its core with the necessity for a more thorough understanding of the thermodynamics of the logic of computing. To contribute in this regard, we put forward a model that implements the Boltzmann machine (BM) approach to computation through an electric substrate under thermal fluctuations and dissipation. The resulting network has precisely defined statistical properties, which are consistent with the data that are accessible to the BM. It is shown that by the proposed model, it is possible to design neural-inspired logic gates capable of universal Turing computation under similar thermal conditions to those found in biological neural networks and with information processing and storage electric potentials at comparable scales.
- Subjects
BOLTZMANN machine; INFORMATION storage &; retrieval systems; BIOLOGICAL neural networks; BIOLOGICALLY inspired computing; NAND gates; LOGIC design; LOGIC circuits
- Publication
Informatics, 2023, Vol 10, Issue 3, p62
- ISSN
2227-9709
- Publication type
Article
- DOI
10.3390/informatics10030062