Construction of feedforward neural networks with simple architectures and approximation abilities
Sign Up to like & getrecommendations! Published in 2020 at "Mathematical Methods in the Applied Sciences"
DOI: 10.1002/mma.6876
Abstract: The universal approximation property of feedforward neural networks (FNNs) is the basis for all FNNs applications. In almost all existing FNN approximation studies, it is always assumed that the activation function of the network satisfies… read more here.
Keywords: feedforward neural; neural networks; activation function; function ... See more keywords
An online self-organizing algorithm for feedforward neural network
Sign Up to like & getrecommendations! Published in 2020 at "Neural Computing and Applications"
DOI: 10.1007/s00521-020-04907-6
Abstract: Feedforward neural network (FNN) is the most popular network model, and the appropriate structure and learning algorithms are the key of its performance. This paper proposes an online self-organizing algorithm for feedforward neural network (OSNN)… read more here.
Keywords: network; self organizing; structure; feedforward neural ... See more keywords
Predicting death by suicide using administrative health care system data: Can feedforward neural network models improve upon logistic regression models?
Sign Up to like & getrecommendations! Published in 2019 at "Journal of affective disorders"
DOI: 10.1016/j.jad.2019.07.063
Abstract: BACKGROUND Suicide is a leading cause of death worldwide. With the increasing volume of administrative health care data, there is an opportunity to evaluate whether machine learning models can improve upon statistical models for quantifying… read more here.
Keywords: feedforward neural; neural network; logistic regression; administrative health ... See more keywords
Online gradient method with smoothing ℓ0 regularization for feedforward neural networks
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2016.10.057
Abstract: źp regularization has been a popular pruning method for neural networks. The parameter p was usually set as 0 < p ź 2 in the literature, and practical training algorithms with ź0 regularization are lacking… read more here.
Keywords: neural networks; smoothing regularization; method; regularization ... See more keywords
Functional connectome fingerprinting using shallow feedforward neural networks
Sign Up to like & getrecommendations! Published in 2021 at "Proceedings of the National Academy of Sciences of the United States of America"
DOI: 10.1073/pnas.2021852118
Abstract: Although individual subjects can be identified with high accuracy using correlation matrices computed from resting-state functional MRI (rsfMRI) data, the performance significantly degrades as the scan duration is decreased. Recurrent neural networks can achieve high… read more here.
Keywords: neural networks; connectome fingerprinting; functional connectome; shallow feedforward ... See more keywords
HDL Implementation of feedforward neural network (FNN)
Sign Up to like & getrecommendations! Published in 2025 at "Physica Scripta"
DOI: 10.1088/1402-4896/addc48
Abstract: Feedforward neural network (FNN) based classifiers have been widely applied to classification tasks such as speech and image recognition. FNN classifier’s computations require matrix-vector multiplications; hardware implementations of the classifier are a good option for… read more here.
Keywords: technology; feedforward neural; network fnn; corner ... See more keywords
Inference of parameters for the back-shifted Fermi gas model using a feedforward neural network
Sign Up to like & getrecommendations! Published in 2024 at "Physical Review C"
DOI: 10.1103/physrevc.109.044325
Abstract: The back-shifted Fermi gas model is widely employed for calculating nuclear level density (NLD) as it can effectively reproduce experimental data by adjusting parameters. However, selecting parameters for nuclei lacking experimental data poses a challenge.… read more here.
Keywords: back shifted; experimental data; feedforward neural; gas model ... See more keywords
Temperature Estimation of PMSM Using a Difference-Estimating Feedforward Neural Network
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3009503
Abstract: Keeping the temperature of a permanent magnet synchronous machine (PMSM) in a safe range is essential for maintaining machine performance. In this paper, a feedforward neural network (FNN) for the temperature estimation of a PMSM… read more here.
Keywords: neural network; pmsm; temperature; feedforward neural ... See more keywords
Feedforward Neural Network Enabled Optical Multi-Path Interference Mitigation for High-Speed IM-DD Transmissions
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Lightwave Technology"
DOI: 10.1109/jlt.2024.3412654
Abstract: The performance of high-speed intensity modulation direct detection (IM-DD) transmission can be severely degraded by the optical multipath interference (MPI), due to the repeated reflections from polluted fiber connectors. Here, we propose a data-driven MPI… read more here.
Keywords: feedforward neural; high speed; mitigation; mpi mitigation ... See more keywords
Feedforward Neural Network-Based Data Aggregation Scheme for Intrabody Area Nanonetworks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Systems Journal"
DOI: 10.1109/jsyst.2020.3043827
Abstract: An intrabody area nanonetwork (intra-BANN) is a set of nanoscale devices, which have outstanding cellular level precision and accuracy for enabling noninvasive healthcare monitoring and disease diagnosis. In this article, we design a novel feedforward… read more here.
Keywords: based data; data aggregation; intrabody area; scheme ... See more keywords
An Online Growing-and-Pruning Algorithm of a Feedforward Neural Network for Nonlinear Systems Modeling
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Automation Science and Engineering"
DOI: 10.1109/tase.2024.3407518
Abstract: In recent decades, many researchers and practitioners have always been focusing on the optimal design approach of feedforward neural network (FNN). However, it is still a challenge that FNN has a compact structure, while meeting… read more here.
Keywords: agpa fnn; fnn; feedforward neural; structure ... See more keywords