Results 11 to 20 of about 122,388 (186)
IET Intelligent Transport Systems, 2023 Rail transit has many advantages, such as large passenger capacity, convenience, safety, and environmental protection, making it the preferred travel mode for most passengers.
Xuanrong Zhang +3 more
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Temporal Modeling of Neural Net Input/Output Behaviors: The Case of XOR
Systems, 2017 In the context of the modeling and simulation of neural nets, we formulate definitions for the behavioral realization of memoryless functions. The definitions of realization are substantively different for deterministic and stochastic systems constructed
Bernard P. Zeigler, Alexandre Muzy
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SRI3D: Two‐stream inflated 3D ConvNet based on sparse regularization for action recognition
IET Image Processing, 2023 Although most state‐of‐the‐art action recognition models have adopted a two‐stream 3D convolutional structure as a backbone network, few works have studied the impact of loss functions on action recognition models.
Zhaoqilin Yang +4 more
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Predictions models with neural nets
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2008 The contribution is oriented to basic problem trends solution of economic pointers, using neural networks. Problems include choice of the suitable model and consequently configuration of neural nets, choice computational function of neurons and the way ...
Vladimír Konečný
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Quantum speed-up in global optimization of binary neural nets
New Journal of Physics, 2021 The performance of a neural network (NN) for a given task is largely determined by the initial calibration of the network parameters. Yet, it has been shown that the calibration, also referred to as training, is generally NP-complete.
Yidong Liao +3 more
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Multigrid meets neural nets [PDF]
Nuclear Physics B - Proceedings Supplements, 1993 We present evidence that multigrid (MG) works for wave equations in disordered systems, e.g. in the presence of gauge fields, no matter how strong the disorder. We introduce a "neural computations" point of view into large scale simulations: First, the system must learn how to do the simulations efficiently, then do the simulation (fast).
Baeker, M., Mack, G., Speh, M.
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Neural networks for modelling and control of a non-linear dynamic system [PDF]
, 1992 The authors describe the use of neural nets to model and control a nonlinear second-order electromechanical model of a drive system with varying time constants and saturation effects. A model predictive control structure is used.
Murray-Smith, R. +2 more
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Scientific Reports, 2022 Deep neural network (DNN) and Convolution neural network (CNN) algorithms have significantly increased the accuracies in cutting-edge large-scale image recognition and natural-language processing tasks.
Varun Bheemireddy
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Solving SAT in linear time with a neural-like membrane system [PDF]
, 2003 We present in this paper a neural-like membrane system solving the SAT problem in linear time. These neural Psystems are nets of cells working with multisets.
Pazos Sierra, Juan +2 more
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TIME SERIES PREDICTION BY NEURAL NETS [PDF]
فصلنامه پژوهشهای اقتصادی ایران, 2002 Application of non-classical methods in modeling complex systems and forecasting their behavior has become as more as usual for the scientists and professionals.
Mohammad Reza Asgari Oskoei
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