Influence of smart sensors on structural health monitoring systems and future asset management practices
Recent developments in networked and smart sensors have significantly changed the way
Structural Health Monitoring (SHM) and asset management are being carried out. Since the …
Structural Health Monitoring (SHM) and asset management are being carried out. Since the …
Stereo attention cross-decoupling fusion-guided federated neural learning for hyperspectral image classification
Federated learning is a promising solution in several industries for cotraining models among
distributed clients via centralized servers without leaving private user data on the devices …
distributed clients via centralized servers without leaving private user data on the devices …
From Multipliers to Integrators: a Survey of Stochastic Computing Primitives
Stochastic Computing (SC) has the potential to dramatically improve important nanoscale
circuit metrics, including area and power dissipation, for implementing complex digital …
circuit metrics, including area and power dissipation, for implementing complex digital …
Highly optimized hardware morphological neural network through stochastic computing and tropical pruning
JL Rosselló, J Font-Rosselló, CF Frasser… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
This work aimed to enhance a previous neural network hardware implementation based on
an efficient combination of Stochastic Computing (SC) and Morphological Neural Networks …
an efficient combination of Stochastic Computing (SC) and Morphological Neural Networks …
Low power nanoscale S-FED based single ended sense amplifier applied in integrate and fire neuron circuit
SMJ Motaman, T Ghafouri, N Manavizadeh - Scientific Reports, 2024 - nature.com
Current advancements in neuromorphic computing systems are focused on decreasing
power consumption and enriching computational functions. Correspondingly, state-of-the-art …
power consumption and enriching computational functions. Correspondingly, state-of-the-art …
A stochastic computing sigma-delta adder architecture for efficient neural network design
N Temenos, PP Sotiriadis - … and Selected Topics in Circuits and …, 2023 - ieeexplore.ieee.org
A stochastic computing (SC) adder architecture, based on sigma-delta modulation is
introduced. The operation principle of the stochastic computing sigma-delta (SCSD) adder is …
introduced. The operation principle of the stochastic computing sigma-delta (SCSD) adder is …
From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks
Deep neural networks (DNNs) have been widely used in many artificial intelligence (AI)
tasks. However, deploying them brings significant challenges due to the huge cost of …
tasks. However, deploying them brings significant challenges due to the huge cost of …
SC-PLR: An Approximate Spiking Neural Network Accelerator with On-Chip Predictive Learning Rule
W Liu, S Xiao, Y Liu, Z Yu - IEEE Transactions on Biomedical …, 2024 - ieeexplore.ieee.org
The brain's ability to anticipate future events is crucial for intelligent behavior. However,
when deploying the capability to edge devices, there are huge challenges in terms of …
when deploying the capability to edge devices, there are huge challenges in terms of …
Analysis, design and evaluation of high-performance stochastic multilayer perceptron: from mini-batch training to inference
Stochastic computing (SC) is a novel computing paradigm for implementing Multilayer
Perceptrons (MLPs), which can mitigate the burden of power dissipation in advanced …
Perceptrons (MLPs), which can mitigate the burden of power dissipation in advanced …
A Digital Realization of Neuroglial Interaction Model and Its Network Structure
Astrocyte cells, the most existing abundant cells in central nervous system, play an essential
role in modulating the neuronal activities, information processing, and regulating the …
role in modulating the neuronal activities, information processing, and regulating the …