A 4.3-bit/Cell RRAM Dual-Cell-Inferring TRNG for Bio-Inspired Mutation Emulation in Stochastic Computing With 1.095 pJ/bit

This paper presents a dual-cell inferring random number generator (TRNG) based on a 1-M-cell multi-resistance-state 1T1R RRAM macro fabricated in a 40-nm CMOS process. By employing a gradual-FORMing and incremental SET/RESET modulation scheme, 20 well-separated resistance states are established acro...

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Detalhes bibliográficos

Principais autores:	Po Hsiung Huang, Ting He Shen, Jun Sheng Hou, E Ray Hsieh
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2026-01-01
coleção:	IEEE Journal of the Electron Devices Society
Assuntos:	True random number generators (TRNG) random-access memory (RRAM) probabilistic-bit (p-bit) dual-cell interference
Acesso em linha:	https://ieeexplore.ieee.org/document/11611870/
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