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crossbar-array

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bshepp / memristive-crossbar

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Differential memristive crossbar with a hardware-friendly in-situ (Manhattan/sign-rule) learning rule, tested on parity-3 — the calibrated in-memory-compute baseline of the physical-learning-substrates portfolio. Verdict #1: PASS, learns parity-3 at SNR ~24.5 (half co-located: physics activations, off-array error sign, physical-pulse increment).

python simulation numpy parity scipy memristor neuromorphic-computing analog-computing in-memory-computing physical-learning crossbar-array in-situ-learning manhattan-rule deadman-publish
  • Updated Jun 21, 2026
  • Python

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