45 citations · 77 across the 7 of their papers we have counts for
7 papers
A 0.5V, 6.2W, 0.059mm Sinusoidal Current Generator IC with 0.088% THD for Bio-Impedance Sensing
Kwantae Kim, Changhyeon Kim, Sungpill Choi +1
This paper presents the first sub-10W, sub-0.1% total harmonic distortion (THD) sinusoidal current generator (CG) integrated circuit (IC) that is capable of 20kHz output for the…
A 23 W Keyword Spotting IC with Ring-Oscillator-Based Time-Domain Feature Extraction
Kwantae Kim, Chang Gao, Rui Graça +4
This article presents the first keyword spotting (KWS) IC which uses a ring-oscillator-based time-domain processing technique for its analog feature extractor (FEx). Its extensive…
Energy-efficient Dense DNN Acceleration with Signed Bit-slice Architecture
Dongseok Im, Gwangtae Park, Zhiyong Li +2
As the number of deep neural networks (DNNs) to be executed on a mobile system-on-chip (SoC) increases, the mobile SoC suffers from the real-time DNN acceleration within its limite…
Two-Step Spike Encoding Scheme and Architecture for Highly Sparse Spiking-Neural-Network
Sangyeob Kim, Sangjin Kim, Soyeon Um +2
This paper proposes a two-step spike encoding scheme, which consists of the source encoding and the process encoding for a high energy-efficient spiking-neural-network (SNN) accele…
GST: Group-Sparse Training for Accelerating Deep Reinforcement Learning
Juhyoung Lee, Sangyeob Kim, Sangjin Kim +2
Deep reinforcement learning (DRL) has shown remarkable success in sequential decision-making problems but suffers from a long training time to obtain such good performance. Many pa…
Extension of Direct Feedback Alignment to Convolutional and Recurrent Neural Network for Bio-plausible Deep Learning
Donghyeon Han, Gwangtae Park, Junha Ryu +1
Throughout this paper, we focus on the improvement of the direct feedback alignment (DFA) algorithm and extend the usage of the DFA to convolutional and recurrent neural networks (…
Efficient Convolutional Neural Network Training with Direct Feedback Alignment
Donghyeon Han, Hoi-jun Yoo
There were many algorithms to substitute the back-propagation (BP) in the deep neural network (DNN) training. However, they could not become popular because their training accuracy…