Efficient hardware architecture of softmax layer in deep neural network
Deep neural network (DNN), as a very important machine learning technique in
classification and detection tasks for images, video, speech as wellas audio, has recently …
classification and detection tasks for images, video, speech as wellas audio, has recently …
Efficient precision-adjustable architecture for softmax function in deep learning
The softmax function has been widely used in deep neural networks (DNNs), and studies on
efficient hardware accelerators for DNN have also attracted tremendous attention. However …
efficient hardware accelerators for DNN have also attracted tremendous attention. However …
FPGA-based implementation of deep neural network using stochastic computing
M Nobari, H Jahanirad - Applied Soft Computing, 2023 - Elsevier
A serious challenge in artificial real-time applications is the hardware implementation of
deep neural networks (DNN). Among various methods, stochastic computing (SC)-based …
deep neural networks (DNN). Among various methods, stochastic computing (SC)-based …
Base-2 softmax function: Suitability for training and efficient hardware implementation
Y Zhang, Y Zhang, L Peng, L Quan… - … on Circuits and …, 2022 - ieeexplore.ieee.org
The softmax function is widely used in deep neural networks (DNNs), its hardware
performance plays an important role in the training and inference of DNN accelerators …
performance plays an important role in the training and inference of DNN accelerators …
[HTML][HTML] Design of infinite impulse response filters based on multi-objective particle Swarm optimization
TJ Su, QY Zhuang, WH Lin, YC Hung, WR Yang… - Signals, 2024 - mdpi.com
The goal of this study is to explore the effectiveness of applying multi-objective particle
swarm optimization (MOPSO) algorithms in the design of infinite impulse response (IIR) …
swarm optimization (MOPSO) algorithms in the design of infinite impulse response (IIR) …
High-accuracy stochastic computing-based fir filter design
KJ Ahmed, B Yuan, MJ Lee - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
In this paper we propose a novel Stochastic Computing (SC) Finite Impulse Response (FIR)
filter design to improve the overall accuracy. Since SC is generated probabilistically, it incurs …
filter design to improve the overall accuracy. Since SC is generated probabilistically, it incurs …
All-digital time-mode direct-form all-pole biquadratic filter realization
In this brief, the design of time-mode signal processing (TMSP) circuits having an all-digital
advantage is introduced and experimental data covering all necessary aspects of operation …
advantage is introduced and experimental data covering all necessary aspects of operation …
Low-cost approximate constant coefficient hybrid binary-unary multiplier for DSP applications
SR Faraji, P Abillama… - 2020 IEEE 28th Annual …, 2020 - ieeexplore.ieee.org
Multipliers are used in virtually all Digital Signal Processing (DSP) applications, such as
image and video processing. Multiplier efficiency has a direct impact on the overall …
image and video processing. Multiplier efficiency has a direct impact on the overall …
Hardware implementation of infinite impulse response anti‐notch filter for exon region identification in eukaryotic genes
The discrimination of exons from introns in the DNA sequence of a eukaryotic gene is
important to understand the functionality of protein formation inside a living organism …
important to understand the functionality of protein formation inside a living organism …
Optimization of softmax layer in deep neural network using integral stochastic computation
Deep neural network (DNN), as a very important machine learning technique in
classification and detection tasks for images, video, speech as well as audio, has recently …
classification and detection tasks for images, video, speech as well as audio, has recently …