Results 71 to 80 of about 3,974,691 (210)

Universal approximation property of stochastic configuration networks for time series

Industrial Artificial Intelligence
For the purpose of processing sequential data, such as time series, and addressing the challenge of manually tuning the architecture of traditional recurrent neural networks (RNNs), this paper introduces a novel approach-the Recurrent Stochastic ...
Jin-Xi Zhang, Hangyi Zhao, Xuefeng Zhang
doaj   +1 more source

Improving the classification of a nanocomposite using nanoparticles based on a meta-analysis study, recurrent neural network and recurrent neural network Monte-Carlo algorithms

Nanocomposites
This paper may be the first meta-analysis that presents a comprehensive synthesis of scientific works spanning the last five years, focusing on methodologies and results related to the analysis of nanocomposite using nanoparticles.
Rania Loukil, Wejden Gazehi, Mongi Besbes   +2 more
doaj   +1 more source

Reservoir computing with output feedback [PDF]

, 2011
Reinhart RF. Reservoir computing with output feedback. Bielefeld: Bielefeld University; 2011.A dynamical system approach to forward and inverse modeling is proposed. Forward and inverse models are trained in associative recurrent neural networks that are
Reinhart, René Felix, Reinhart, Felix
core   +1 more source

A Model for Programmability and Virtuality in Dynamical Neural Networks [PDF]

, 2009
In this dissertation a fixed-weight architecture for Continuous Time Recurrent Neural Networks (CTRNNs) is proposed in order to give an account for biological phenomena, controlled by neuronal activity, in which changes of behavior occur so fast that ...
Donnarumma, Francesco
core   +1 more source

Comparative Analysis of Neural Network Architectures for Digital Predistortion in Power Amplifier Linearization [PDF]

EPJ Web of Conferences
In this study, we examine and contrast the effectiveness of different artificial neural network (ANN) topologies for power amplifier (PA) digital pre-distortion (DPD).
Laakouri Hafsa, Ouadefli Mostapha, Tribak Abdelwahed, Et-tolba Mohamed, Terhzaz Jaouad, Ibanez Tomas Fernandez   +5 more
doaj   +1 more source

Stability and synchronization of discrete-time Markovian jumping neural networks with mixed mode-dependent time delays [PDF]

, 2009
Copyright [2009] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services.
Liu, Y, Liu, X, Wang, Z, Liang, J, Liu, Xiaohui., J Liang (7713770), Wang, Zidong., Yurong Liu (9814022), Z Wang (81545), X Liu (7756691), Liang, Jinling., Liu, Yurong.   +11 more
core   +1 more source

Lipschitz Recurrent Neural Networks

CoRR, 2020
Published as a conference paper at ICLR ...
N. Benjamin Erichson, Omri Azencot, Alejandro F. Queiruga, Liam Hodgkinson, Michael W. Mahoney   +4 more
openaire   +3 more sources

Multistability in Recurrent Neural Networks [PDF]

SIAM Journal on Applied Mathematics, 2006
Stable stationary solutions correspond to memory capacity in the application of associative memory for neural networks. In this presentation, existence of multiple stable stationary solutions for Hopfield-type neural networks with delay and without delay is investigated. Basins of attraction for these stationary solutions are also estimated.
Chang-Yuan Cheng, Kuang-Hui Lin, Chih-Wen Shih   +2 more
openaire   +1 more source

Recurrent Neural Network Based Narrowband Channel Prediction

, 2006
In this contribution, the application of fully connected recurrent neural networks (FCRNNs) is investigated in the context of narrowband channel prediction.
Liu, W., Yang, L-L., Hanzo, L.
core   +1 more source

Refinement of matching costs for stereo disparities using recurrent neural networks

EURASIP Journal on Image and Video Processing, 2021
Depth is essential information for autonomous robotics applications that need environmental depth values. The depth could be acquired by finding the matching pixels between stereo image pairs. Depth information is an inference from a matching cost volume
Alper Emlek, Murat Peker
doaj   +1 more source