A $\Delta$-Based Spike Sorting SoC with End-to-End Implementation of Event-Driven Binary Autoencoder Neural Network in Analog CIM Achieving 94.54% Accuracy and $\mathbf{3.11}\boldsymbol{\mu}\mathbf{W}/\mathbf{ch}$

The proposed $\Delta$-based spike sorting (SS) SoC is the first on-chip implementation of an analog computing-in-memory (CIM) binary autoencoder neural network (B-AENN) feature extraction with enhanced spike detection adopting $\Delta$-spikes, resulting in the highest on-chip SS classification accuracy of 94.54%. It also allows to reduce the digital data transmission rate by 48.8× compared to prior SS systems.