Related references
Note: Only part of the references are listed.On the approximation by single hidden layer feedforward neural networks with fixed weights
Namig J. Guliyev et al.
NEURAL NETWORKS (2018)
A self-organizing interval Type-2 fuzzy-neural-network for modeling nonlinear systems
Hong-Gui Han et al.
NEUROCOMPUTING (2018)
An improved algorithm for building self-organizing feedforward neural networks
Junfei Qiao et al.
NEUROCOMPUTING (2017)
An adaptive growing and pruning algorithm for designing recurrent neural network
Hong-Gui Han et al.
NEUROCOMPUTING (2017)
Sensitivity analysis: A review of recent advances
Emanuele Borgonovo et al.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2016)
A new deep neural network based on a stack of single-hidden-layer feedforward neural networks with randomly fixed hidden neurons
Junying Hu et al.
NEUROCOMPUTING (2016)
Constructive algorithm for fully connected cascade feedforward neural networks
Junfei Qiao et al.
NEUROCOMPUTING (2016)
Development of a Self-Regulating Evolving Spiking Neural Network for classification problem
S. Dora et al.
NEUROCOMPUTING (2016)
Applications of feedforward multilayer perceptron artificial neural networks and empirical correlation for prediction of thermal conductivity of Mg(OH)2-EG using experimental data
Mohammad Hemmat Esfe et al.
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER (2015)
A Hybrid Constructive Algorithm for Single-Layer Feedforward Networks Learning
Xing Wu et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015)
Generalized Single-Hidden Layer Feedforward Networks for Regression Problems
Ning Wang et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015)
A unified evolutionary training scheme for single and ensemble of feedforward neural network
Wen-Ching Chen et al.
NEUROCOMPUTING (2014)
An online supervised learning method for spiking neural networks with adaptive structure
Jinling Wang et al.
NEUROCOMPUTING (2014)
Online sequential extreme learning machine with kernels for nonstationary time series prediction
Xinying Wang et al.
NEUROCOMPUTING (2014)
An online self-adaptive modular neural network for time-varying systems
Junfei Qiao et al.
NEUROCOMPUTING (2014)
Nonlinear Systems Modeling Based on Self-Organizing Fuzzy-Neural-Network With Adaptive Computation Algorithm
Honggui Han et al.
IEEE TRANSACTIONS ON CYBERNETICS (2014)
A structure optimisation algorithm for feedforward neural network construction
Hong-Gui Han et al.
NEUROCOMPUTING (2013)
Adaptive Evolutionary Artificial Neural Networks for Pattern Classification
Tatt Hee Oong et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2011)
Convergence analysis of online gradient method for BP neural networks
Wei Wu et al.
NEURAL NETWORKS (2011)
Boundedness and convergence of online gradient method with penalty and momentum
Hongmei Shao et al.
NEUROCOMPUTING (2011)
Regularized online sequential learning algorithm for single-hidden layer feedforward neural networks
Hieu Trung Huynh et al.
PATTERN RECOGNITION LETTERS (2011)
Boundedness and Convergence of Online Gradient Method With Penalty for Feedforward Neural Networks
Huisheng Zhang et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2009)
A New Adaptive Merging and Growing Algorithm for Designing Artificial Neural Networks
Md. Monirul Islam et al.
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS (2009)
Adaptive growing-and-pruning neural network control for a linear piezoelectric ceramic motor
Chun-Fei Hsu
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2008)
Structure learning by pruning in independent component analysis
Andreas Brinch Nielsen et al.
NEUROCOMPUTING (2008)
A fast and accurate online sequential learning algorithm for feedforward networks
Nan-Ying Liang et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2006)
A node pruning algorithm fulased on a Fourier amplitude sensitivity test method
P Lauret et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2006)
Deterministic convergence of an online gradient method for BP neural networks
W Wu et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2005)
An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks
GB Huang et al.
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS (2004)
A constructive algorithm for feedforward neural networks with incremental training
DR Liu et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS (2002)
A new pruning heuristic based on variance analysis of sensitivity information
AP Engelbrecht
IEEE TRANSACTIONS ON NEURAL NETWORKS (2001)