Understanding the importance of process alarms based on the analysis of deep recurrent neural networks trained for fault isolation
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Chemometrics"
DOI: 10.1002/cem.3006
Abstract: The identification of process faults is a complex and challenging task due to the high amount of alarms and warnings of control systems. To extract information about the relationships between these discrete events, we utilise… read more here.
Keywords: network; fault isolation; analysis; process ... See more keywords
A k-space-to-image reconstruction network for MRI using recurrent neural network.
Sign Up to like & getrecommendations! Published in 2020 at "Medical physics"
DOI: 10.1002/mp.14566
Abstract: PURPOSE Reconstructing the images from undersampled k-space data is an ill-posed inverse problem. As a solution to this problem, we propose a method to reconstruct MR images directly from k-space data using a recurrent neural… read more here.
Keywords: space; network; space data; proposed method ... See more keywords
A Novel Fractional Gradient-Based Learning Algorithm for Recurrent Neural Networks
Sign Up to like & getrecommendations! Published in 2018 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-017-0572-z
Abstract: In this research, we propose a novel algorithm for learning of the recurrent neural networks called as the fractional back-propagation through time (FBPTT). Considering the potential of the fractional calculus, we propose to use the… read more here.
Keywords: novel fractional; based learning; neural networks; gradient based ... See more keywords
Recurrent Neural Network-Based Dictionary Learning for Compressive Speech Sensing
Sign Up to like & getrecommendations! Published in 2019 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-019-01058-5
Abstract: We propose a novel dictionary learning technique for compressive sensing of speech signals based on the recurrent neural network. First, we exploit the recurrent neural network to solve an $$\ell _{0}$$ℓ0-norm optimization problem based on… read more here.
Keywords: neural network; dictionary learning; speech; recurrent neural ... See more keywords
A parametric recurrent neural network scheme for solving a class of fuzzy regression models with some real-world applications
Sign Up to like & getrecommendations! Published in 2020 at "Soft Computing"
DOI: 10.1007/s00500-020-05008-1
Abstract: In this paper, a hybrid scheme based on recurrent neural networks for approximate fuzzy coefficients (parameters) of fuzzy linear and polynomial regression models with fuzzy output and crisp inputs is presented. Here, a neural network… read more here.
Keywords: network; regression models; recurrent neural; fuzzy regression ... See more keywords
Exponential stability analysis for delayed complex-valued memristor-based recurrent neural networks
Sign Up to like & getrecommendations! Published in 2017 at "Neural Computing and Applications"
DOI: 10.1007/s00521-017-3166-6
Abstract: The exponential stability problem for complex-valued memristor-based recurrent neural networks (CVMRNNs) with time delays is studied in this paper. As an extension of real-valued memristor-based recurrent neural networks, CVMRNNs can be separated into real and… read more here.
Keywords: valued memristor; based recurrent; memristor based; complex valued ... See more keywords
Character-level recurrent neural networks in practice: comparing training and sampling schemes
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-017-3322-z
Abstract: Recurrent neural networks are nowadays successfully used in an abundance of applications, going from text, speech and image processing to recommender systems. Backpropagation through time is the algorithm that is commonly used to train these… read more here.
Keywords: neural networks; level recurrent; recurrent neural; sampling schemes ... See more keywords
Recurrent neural network with attention mechanism for language model
Sign Up to like & getrecommendations! Published in 2019 at "Neural Computing and Applications"
DOI: 10.1007/s00521-019-04301-x
Abstract: The rapid growth of the Internet promotes the growth of textual data, and people get the information they need from the amount of textual data to solve problems. The textual data may include some potential… read more here.
Keywords: neural network; language model; network; recurrent neural ... See more keywords
Anti-periodic solutions for state-dependent impulsive recurrent neural networks with time-varying and continuously distributed delays
Sign Up to like & getrecommendations! Published in 2017 at "Annals of Operations Research"
DOI: 10.1007/s10479-016-2192-6
Abstract: In this paper, we address a new model of neural networks related to the impulsive phenomena which is called state-dependent impulsive recurrent neural networks with time-varying and continuously distributed delays. We investigate sufficient conditions on… read more here.
Keywords: networks time; neural networks; impulsive recurrent; state dependent ... See more keywords
A recurrent neural network for urban long-term traffic flow forecasting
Sign Up to like & getrecommendations! Published in 2020 at "Applied Intelligence"
DOI: 10.1007/s10489-020-01716-1
Abstract: This paper investigates the use of recurrent neural network to predict urban long-term traffic flows. A representation of the long-term flows with related weather and contextual information is first introduced. A recurrent neural network approach,… read more here.
Keywords: traffic; long term; traffic flow; recurrent neural ... See more keywords
Pullback Exponential Attractors for Non-autonomous Recurrent Neural Networks with Discrete and Distributed Time-Varying Delays
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Dynamics and Differential Equations"
DOI: 10.1007/s10884-021-09991-3
Abstract: First some sufficient conditions are presented for the existence and the construction of pullback exponential attractors for infinite dimensional non-autonomous dynamical systems with delays. This abstract result is then used to establish the existence of… read more here.
Keywords: pullback exponential; non autonomous; neural networks; recurrent neural ... See more keywords