Results 31 to 40 of about 2,445,824 (337)
Variable neural networks for adaptive control of nonlinear systems [PDF]
, 1999 This paper is concerned with the adaptive control of continuous-time nonlinear dynamical systems using neural networks. A novel neural network architecture, referred to as a variable neural network, is proposed and shown to be useful in approximating the
Billings, S.A. +2 more
core +1 more source
IEEE Transactions on Emerging Topics in Computational Intelligence, 2019 Equality and incomparability multi-label ranking have not been introduced to learning before. This paper proposes new native ranker neural network to address the problem of multi-label ranking including incomparable preference orders using a new activation and error functions and new architecture.
Ayman Elgharabawy +2 more
openaire +7 more sources
Interacting neural networks [PDF]
Physical Review E, 2000 Several scenarios of interacting neural networks which are trained either in an identical or in a competitive way are solved analytically. In the case of identical training each perceptron receives the output of its neighbour. The symmetry of the stationary state as well as the sensitivity to the used training algorithm are investigated.
Ido Kanter +2 more
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Neural Plasticity, 2004 Functional and morphological studies in children affected by Attention Deficit Hyperactivity Disorder (ADHD) suggest a prefrontal cortex (PFc) dysfunction.
D. Viggiano +3 more
doaj +1 more source
ICC 2020 - 2020 IEEE International Conference on Communications (ICC), 2020 In this paper we introduce Neural Network Coding(NNC), a data-driven approach to joint source and network coding. In NNC, the encoders at each source and intermediate node, as well as the decoder at each destination node, are neural networks which are all trained jointly for the task of communicating correlated sources through a network of noisy point ...
Liu, Litian +3 more
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Voltage stability analysis of load buses in electric power system using adaptive neuro-fuzzy inference system (anfis) and probabilistic neural network (pnn) [PDF]
, 2017 This paper presents the application of neural networks for analysing voltage stability of load buses in electric power system. Voltage stability margin (VSM) and load power margin (LPM) are used as the indicators for analysing voltage stability.
Ab Ghani, Ahmad Raqib +4 more
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Neural Networks proposes to reconstruct situated practices, social histories, mediating techniques, and ontological assumptions that inform the computational project of the same name. If so-called machine learning comprises a statistical approach to pattern extraction, then neural networks can be defined as a biologically inspired model that relies on ...
Dhaliwal, Ranjodh Singh +2 more
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The use of adversaries for optimal neural network training [PDF]
, 2018 B-decay data from the Belle experiment at the KEKB collider have a substantial background from $e^{+}e^{-}\to q \bar{q}$ events. To suppress this we employ deep neural network algorithms.
Hawthorne-Gonzalvez, Anton +1 more
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Neural Networks, 2003 In the last decade, the use of neural networks (NN) and of other soft computing methods has begun to spread also in the astronomical community which, due to the required accuracy of the measurements, is usually reluctant to use automatic tools to perform even the most common tasks of data reduction and data mining. The federation of heterogeneous large
CIARAMELLA A. +12 more
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Spinal Cord Injury in Myelomeningocele: Prospects for Therapy
Frontiers in Cellular Neuroscience, 2020 Myelomeningocele (MMC) is the most common congenital defect of the central nervous system and results in devastating and lifelong disability. In MMC, the initial failure of neural tube closure early in gestation is followed by a progressive prenatal ...
Karolina Janik +3 more
doaj +1 more source