Dynamic Adjustment of Hidden Layer Structure for Convex Incremental Extreme Learning Machine
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1007/978-3-319-28373-9_30
Abstract: Extreme Learning Machine (ELM) is a learning algorithm based on generalized single-hidden-layer feed-forward neural network. Since ELM has an excellent performance on regression and classification problems, it has been paid more and more attention recently.… read more here.
Keywords: extreme learning; elm; learning machine; hidden layer ... See more keywords
Model NOx emission and thermal efficiency of CFBB based on an ameliorated extreme learning machine
Sign Up to like & getrecommendations! Published in 2018 at "Soft Computing"
DOI: 10.1007/s00500-017-2653-0
Abstract: Extreme learning machine (ELM) is a novel single hidden layer feed-forward network, which has become a research hotspot in various domains. Through in-depth analysis on ELM, there are four factors mainly affect its model performance,… read more here.
Keywords: machine; extreme learning; learning machine; model ... See more keywords
A new variant of restricted Boltzmann machine with horizontal connections
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3460-y
Abstract: Restricted Boltzmann machines (RBMs) are successfully employed to construct deep architectures because their power of expression and the inference is tractable and easy. In this paper, we propose a model named self-connected restricted Boltzmann machine… read more here.
Keywords: horizontal connections; restricted boltzmann; layer; hidden layer ... See more keywords
N-hidden layer artificial neural network architecture computer code: geophysical application example
Sign Up to like & getrecommendations! Published in 2020 at "Heliyon"
DOI: 10.1016/j.heliyon.2020.e04108
Abstract: We provide a MATLAB computer code for training artificial neural network (ANN) with N+1 layer (N-hidden layer) architecture. Currently, the ANN application to solving geophysical problems have been confined to the 2-layer, i.e. 1-hidden layer,… read more here.
Keywords: code; layer ann; application; hidden layer ... See more keywords
Greedy Broad Learning System
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3084610
Abstract: In order to overcome the extremely time-consuming drawback of deep learning (DL), broad learning system (BLS) was proposed as an alternative method. This model is simple, fast, and easy to update. To ensure the fitting… read more here.
Keywords: learning system; bls; hidden layer; layer ... See more keywords
Incorporating Structural Plasticity Approaches in Spiking Neural Networks for EEG Modelling
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3099492
Abstract: Structural Plasticity (SP) in the brain is a process that allows structural neuronal changes, in response to learning. Spiking Neural Networks (SNN) are an emerging form of artificial neural networks that use brain-inspired techniques to… read more here.
Keywords: incorporating structural; neural networks; hidden layer; spiking neural ... See more keywords
Fuzzy Multiple Hidden Layer Neural Sliding Mode Control of Active Power Filter With Multiple Feedback Loop
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3104030
Abstract: A fuzzy multiple hidden layer neural sliding mode control with multiple feedback loop (FMHLNSMCMFL) is proposed for a single-phase active power filter (APF), where a sliding mode controller is designed to make the current tracking… read more here.
Keywords: sliding mode; control; hidden layer; multiple feedback ... See more keywords
Structured DNN-Based Receiver for Millimeter-Wave MIMO With Nonlinear Distortions
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Wireless Communications Letters"
DOI: 10.1109/lwc.2021.3130894
Abstract: This work deals with the combined effect of nonlinear distortions and inter-channel interference in millimeter wave multi-input multi-output (MIMO) communications. Deep neural networks (DNNs) can be used to handle the effect, but they often require… read more here.
Keywords: millimeter wave; nonlinear distortions; hidden layer; based receiver ... See more keywords
Adaptive Global Sliding-Mode Control for Dynamic Systems Using Double Hidden Layer Recurrent Neural Network Structure
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2019.2919676
Abstract: In this paper, a full-regulated neural network (NN) with a double hidden layer recurrent neural network (DHLRNN) structure is designed, and an adaptive global sliding-mode controller based on the DHLRNN is proposed for a class… read more here.
Keywords: neural network; hidden layer; structure; layer ... See more keywords
Guaranteed Recovery of One-Hidden-Layer Neural Networks via Cross Entropy
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2020.2993153
Abstract: We study model recovery for data classification, where the training labels are generated from a one-hidden-layer neural network with sigmoid activations, also known as a single-layer feedforward network, and the goal is to recover the… read more here.
Keywords: layer neural; hidden layer; layer; cross entropy ... See more keywords
Optical Neural Ordinary Differential Equations
Sign Up to like & getrecommendations! Published in 2022 at "Optics letters"
DOI: 10.1364/ol.477713
Abstract: Increasing the layer number of on-chip photonic neural networks (PNNs) is essential to improve its model performance. However, the successive cascading of network hidden layers results in larger integrated photonic chip areas. To address this… read more here.
Keywords: neural networks; optical neural; hidden layer; ordinary differential ... See more keywords