Controlling oscillatory behaviour of a two neuron recurrent neural network using inputs [PDF]
, 2001 Haschke R, Steil JJ, Ritter H. Controlling oscillatory behaviour of a two neuron recurrent neural network using inputs. In: Dorffner G, Bischof H, Hornik K, eds. Artificial Neural Networks - ICANN 2001. Lecture notes in computer science.
Dorffner, Georg +5 more
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Parralel Recurrent Convolutional Neural Network for Abnormal Heart Sound Classification [PDF]
, 2023 This paper presents the results of a study performed on Parallel Convolutional Neural Network (PCNN) toward detecting heart abnormalities from the heart sound signals.
Gharehbaghi, Arash, +5 more
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Nonlinear system identification for predictive control using continuous time recurrent neural networks and automatic differentiation. [PDF]
, 2008 In this paper, a continuous time recurrent neural network (CTRNN) is developed to be used in nonlinear model predictive control (NMPC) context. The neural network represented in a general nonlinear state-space form is used to predict the future ...
Cao, Yi, Al Seyab, Rihab Khalid Shakir
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Research on epileptic EEG recognition based on improved residual networks of 1-D CNN and indRNN
BMC Medical Informatics and Decision Making, 2021 Background Epilepsy is one of the diseases of the nervous system, which has a large population in the world. Traditional diagnosis methods mostly depended on the professional neurologists’ reading of the electroencephalogram (EEG), which was time ...
Mengnan Ma +4 more
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Inception recurrent convolutional neural network for object recognition [PDF]
Machine Vision and Applications, 2021 Deep convolutional neural network (DCNN) is an influential tool for solving various problems in machine learning and computer vision. Recurrent connectivity is a very important component of visual information processing within the human brain. The idea of recurrent connectivity is rarely applied within convolutional layers, the exceptions being a ...
Md. Zahangir Alom +4 more
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Prediction of Convergence Dynamics of Design Performance using Differential Recurrent Neural Networks [PDF]
, 2008 Computational Fluid Dynamics (CFD) simulations have been extensively used in many aerodynamic design optimization problems, such as wing and turbine blade shape design optimization.
Sendhoff, Bernhard +12 more
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An infrastructure for neural network construction [PDF]
, 2005 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.After many years of research the area of Artificial Intelligence is still searching for ways to construct a truly intelligent system.
Stewart, Richard
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Multi-step learning rule for recurrent neural models: an application to time series forecasting [PDF]
, 2001 Multi-step prediction is a difficult task that has attracted increasing interest in recent years. It tries to achieve predictions several steps ahead into the future starting from current information.
Galván, Inés M. +3 more
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Remaining useful life prediction for proton exchange membrane fuel cells using combined convolutional neural network and recurrent neural network [PDF]
, 2023 The search for sustainable but environmentally friendly medium of harnessing energy for the automotive industry has led to the evolution of various energy generating and converting devices. One of such energy converting device is fuel cells.
Alaswad, Abed +5 more
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Deep neural network model for group activity recognition using contextual relationship
Engineering Science and Technology, an International Journal, 2019 In this paper, we present contextual relationship-based learning model using deep neural network for recognizing the activities performed by a group of people in a video sequence.
S.A. Vahora, N.C. Chauhan
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