A Multi-Channel Auditory Signal Encoder with Adaptive Resolution Using Volatile Memristors

TL;DR

This paper presents an innovative hybrid CMOS-memristor auditory encoder that adaptively adjusts its sensitivity to sound onsets using volatile memristors, improving temporal detail preservation and spike efficiency in neuromorphic audio processing.

Contribution

The work introduces a novel adaptive-threshold spike encoding method leveraging volatile memristors, demonstrating a practical hybrid CMOS-memristor auditory encoder with improved onset detection.

Findings

Enhanced onset detection and temporal detail preservation.

Efficient spike encoding with adaptive thresholds.

Successful experimental validation with speech signals.

Abstract

We demonstrate and experimentally validate an end-to-end hybrid CMOS-memristor auditory encoder that realises adaptive-threshold, asynchronous delta-modulation (ADM)-based spike encoding by exploiting the inherent volatility of HfTiOx devices. A spike-triggered programming pulse rapidly raises the ADM threshold Delta (desensitisation); the device's volatility then passively lowers Delta when activity subsides (resensitisation), emphasising onsets while restoring sensitivity without static control energy. Our prototype couples an 8-channel 130 nm encoder IC to off-chip HfTiOx devices via a switch interface and an off-chip controller that monitors spike activity and issues programming events. An on-chip current-mirror transimpedance amplifier (TIA) converts device current into symmetric thresholds, enabling both sensitive and conservative encoding regimes. Evaluated with gammatone-filtered speech, the adaptive loop-at matched spike budget-sharpens onsets and preserves fine temporal detail that a fixed-Delta baseline misses; multi-channel spike cochleagrams show the same trend. Together, these results establish a practical hybrid CMOS-memristor pathway to onset-salient, spike-efficient neuromorphic audio front-ends and motivate low-power single-chip integration.