Spiking neural network integrated circuits: A review of trends and future directions
The rapid growth of deep learning, spurred by its successes in various fields ranging from
face recognition [1] to game playing [2], has also triggered a growing interest in the design of …
face recognition [1] to game playing [2], has also triggered a growing interest in the design of …
A 23μW solar-powered keyword-spotting ASIC with ring-oscillator-based time-domain feature extraction
Voice-controlled interfaces on acoustic Internet-of-Things (IoT) sensor nodes and mobile
devices require integrated low-power always-on wake-up functions such as Voice Activity …
devices require integrated low-power always-on wake-up functions such as Voice Activity …
An 82nW 0.53 pJ/SOP clock-free spiking neural network with 40µs latency for AloT wake-up functions using ultimate-event-driven bionic architecture and computing-in …
Human brain is a natural ultimate-event-driven (UED) system with low power and real-time
response-ability, thanks to the asynchronous propagation and processing of spikes. Power …
response-ability, thanks to the asynchronous propagation and processing of spikes. Power …
Hardware acceleration for embedded keyword spotting: Tutorial and survey
In recent years, Keyword Spotting (KWS) has become a crucial human–machine interface
for mobile devices, allowing users to interact more naturally with their gadgets by leveraging …
for mobile devices, allowing users to interact more naturally with their gadgets by leveraging …
A 23-μW Keyword Spotting IC With Ring-Oscillator-Based Time-Domain Feature Extraction
This article presents the first keyword spotting (KWS) IC that uses a ring-oscillator-based
time-domain processing technique for its analog feature extractor (FEx). Its extensive usage …
time-domain processing technique for its analog feature extractor (FEx). Its extensive usage …
An ultra-low power adjustable current-mode analog integrated general purpose artificial neural network classifier
This study introduces a methodology tailored to analog hardware architecture for
implementing an artificial neural network. The fundamental components of the architecture …
implementing an artificial neural network. The fundamental components of the architecture …
Hoyer regularizer is all you need for ultra low-latency spiking neural networks
Spiking Neural networks (SNN) have emerged as an attractive spatio-temporal computing
paradigm for a wide range of low-power vision tasks. However, state-of-the-art (SOTA) SNN …
paradigm for a wide range of low-power vision tasks. However, state-of-the-art (SOTA) SNN …
IMPULSE: A 65-nm digital compute-in-memory macro with fused weights and membrane potential for spike-based sequential learning tasks
The inherent dynamics of the neuron membrane potential in spiking neural networks (SNNs)
allows the processing of sequential learning tasks, avoiding the complexity of recurrent …
allows the processing of sequential learning tasks, avoiding the complexity of recurrent …
AAD-KWS: A Sub-μ W Keyword Spotting Chip With an Acoustic Activity Detector Embedded in MFCC and a Tunable Detection Window in 28-nm CMOS
As a widely used speech-triggered interface, deep-learning-based keyword spotting (KWS)
chips require both ultra-low power and high detection accuracy. We propose a sub …
chips require both ultra-low power and high detection accuracy. We propose a sub …
An 82-nW 0.53-pJ/SOP clock-free spiking neural network with 40-μs latency for AIoT wake-up functions using a multilevel-event-driven bionic architecture and …
This article presents a clock-free spiking neural network (SNN) intelligent inference engine
(IIE) for artificial intelligence of things (AIoT) sensor nodes, which often operate in random …
(IIE) for artificial intelligence of things (AIoT) sensor nodes, which often operate in random …