Discrete Langevin machine: Bridging the gap between thermodynamic and neuromorphic systems.
basic_science · Level V
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- Record sourced from PubMed, PMID 32688507.
- Also identified by DOI 10.1103/PhysRevE.101.063304.
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Abstract
A formulation of Langevin dynamics for discrete systems is derived as a class of generic stochastic processes. The dynamics simplify for a two-state system and suggest a network architecture which is implemented by the Langevin machine. The Langevin machine represents a promising approach to compute successfully quantitative exact results of Boltzmann distributed systems by LIF neurons. Besides a detailed introduction of the dynamics, different simplified models of a neuromorphic hardware system are studied with respect to a control of emerging sources of errors.