ArticleAdvanced materials (Deerfield Beach, Fla.)2026
Noise-Tunable Memristor Enabling Programmable Probabilistic Neurons for Frequency-Selective Time-Series Signal Encoding.
Article in Advanced materials (Deerfield Beach, Fla.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Memristors exhibit tunable resistance, which has been widely exploited in non-volatile memory, in-memory computing, and neuromorphic computing. They can also serve as an entropy source due to their inherent instability, making them attractive for security devices and probabilistic computing. When these two characteristics are coupled, memristors can act as tunable entropy sources; however, this direction remains largely unexplored. Here, we propose a spiking-rate-programmable probabilistic neuron that leverages the tunable noise characteristics of a Ru/TaO
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