Robust automatic modulation classification in low signal to noise ratio
In a non-cooperative communication environment, automatic modulation classification
(AMC) is an essential technology for analyzing signals and classifying different kinds of …
(AMC) is an essential technology for analyzing signals and classifying different kinds of …
Analytic deep neural network-based robot control
HT Nguyen, CC Cheah - IEEE/ASME Transactions on …, 2022 - ieeexplore.ieee.org
Neural networks have been extensively used in robot control for various applications
because of their powerful capability in approximation of nonlinear functions. However …
because of their powerful capability in approximation of nonlinear functions. However …
A theoretical framework for end-to-end learning of deep neural networks with applications to robotics
S Li, HT Nguyen, CC Cheah - IEEE Access, 2023 - ieeexplore.ieee.org
Deep Learning (DL) systems are difficult to analyze and proving convergence of DL
algorithms like backpropagation is an extremely challenging task as it is a highly non …
algorithms like backpropagation is an extremely challenging task as it is a highly non …
Real-time modular deep neural network-based adaptive control of nonlinear systems
A real-time deep neural network (DNN) adaptive control architecture is developed for
uncertain control-affine nonlinear systems to track a time-varying desired trajectory. A …
uncertain control-affine nonlinear systems to track a time-varying desired trajectory. A …
A layer-wise theoretical framework for deep learning of convolutional neural networks
HT Nguyen, S Li, CC Cheah - IEEE Access, 2022 - ieeexplore.ieee.org
As research attention in deep learning has been focusing on pushing empirical results to a
higher peak, remarkable progress has been made in the performance race of machine …
higher peak, remarkable progress has been made in the performance race of machine …
EVOLVER: Online Learning and Prediction of Disturbances for Robot Control
In nature, when encountering unexpected uncertainty, animals tend to react quickly to
ensure safety as the top priority, and gradually adapt to it based on recent valuable …
ensure safety as the top priority, and gradually adapt to it based on recent valuable …
Self-calibrating colorimetric sensor assisted deep learning strategy for efficient and precise Fe (II) detection
Z Liu, T Yang, Y Yan, Y Tang, J Meng, F Li - Surfaces and Interfaces, 2024 - Elsevier
Colorimetry is to determine the component content usually comparing or measuring the
“RGB” values, which has the advantages of quick response and visual comparison …
“RGB” values, which has the advantages of quick response and visual comparison …
A construction cost estimation framework using DNN and validation unit
S Saeidlou, N Ghadiminia - Building Research & Information, 2024 - Taylor & Francis
Accurate construction cost estimation is crucial to completing projects within the planned
timeframe and expenditure. The estimation process depends on multiple variables …
timeframe and expenditure. The estimation process depends on multiple variables …
An analytic end-to-end deep learning algorithm based on collaborative learning
S Li, CC Cheah - arXiv preprint arXiv:2305.18594, 2023 - arxiv.org
In most control applications, theoretical analysis of the systems is crucial in ensuring stability
or convergence, so as to ensure safe and reliable operations and also to gain a better …
or convergence, so as to ensure safe and reliable operations and also to gain a better …
Deep learning-assisted self-volume-calibrating colorimetric sensor for chloride ion detection
X Tan, Y Yan, B Li, M Lin, J Qu, J Meng, F Li - Microchemical Journal, 2024 - Elsevier
Chloride ions (Cl−) are widely present in nature, and accurate measurement of Cl− is of
great significance for health management and water quality monitoring. Based on the …
great significance for health management and water quality monitoring. Based on the …