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In the context of physical reservoir computing, the key challenge is identifying scalable and technologically accessible materials with controllable dynamic properties suitable for implementing neuromorphic computing architectures. Materials with hopping mechanism of transport are assumed to be promising for these purposes. In this work, reservoir computing based on a charge carrier hopping transport model in a lattice of localized states with energy disorder is investigated. The feasibility of adapting output layer weights for forecasting complex nonlinear stochastic time series is demonstrated. Numerical modeling was conducted that confirms the architecture’s potential for forecasting tasks, while revealing limitations of its feedforward neural network-like topology with preferential charge transport direction. It has been established that to enhance the efficiency of such neuromorphic systems, future developments must incorporate off-diagonal disorder and memristive effects caused by current-dependent hopping rate modifications between nodes. The results obtained provide important practical insights for designing novel neuromorphic computing architectures based on hopping transport semiconductor systems.

Key words: hopping transport, doped silicon, neuromorphic computing, reservoir computing, memristive system
Published in: FUNDAMENTAL RESEARCHES
Bibliography link: Lekomtsev P. S., Sibatov R. T. Reservoir computing based on a semiconductor system with hopping transport. Izv.vuzov. Elektronika = Proc. Univ. Electronics. 2025;30(4):391–399. (InRuss.). https://doi.org/10.24151/1561-5405-2025-30-4-391-399.
Financial source: the work has been supported by the Ministry of Science and Higher Education of the Russian Federation (project FNRM-2025-0010).

Pavel S. Lekomtsev
National Research University of Electronic Technology (Russia, 124498, Moscow, Zelenograd, Shokin sq., 1)

Renat T. Sibatov
National Research University of Electronic Technology (Russia, 124498, Moscow, Zelenograd, Shokin sq., 1); SMC “Technological Centre” (Russia, 124498, Moscow, Zelenograd, Shokin sq., 1)

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Information about the publication

UDK: 621.38
Publication type: Scientific article
Source lang: Russian
DOI: 10.24151/1561-5405-2025-30-4-391-399
RISC id: CFWERE

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