Results 51 to 60 of about 3,974,691 (210)
Behavioral Classification of Sequential Neural Activity Using Time Varying Recurrent Neural Networks
IEEE Transactions on Neural Systems and Rehabilitation EngineeringShifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in devising corrective neural stimulation before the onset of behavior.
Yongxu Zhang +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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Quaternion Recurrent Neural Networks
CoRR, 2018 ICLR Update - Full ...
Parcollet, Titouan +6 more
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Learning extreme vegetation response to climate drivers with recurrent neural networks [PDF]
Nonlinear Processes in GeophysicsThe spectral signatures of vegetation are indicative of ecosystem states and health. Spectral indices used to monitor vegetation are characterized by long-term trends, seasonal fluctuations, and responses to weather anomalies. This study investigates the
F. Martinuzzi +13 more
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Sensors, 2023 This paper presents a systematic approach for solving complex prediction problems with a focus on energy efficiency. The approach involves using neural networks, specifically recurrent and sequential networks, as the main tool for prediction. In order to
Francisco Rau +6 more
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Asymptotic stability for neural networks with mixed time-delays: The discrete-time case [PDF]
, 2009 This is the post print version of the article. The official published version can be obtained from the link - Copyright 2009 Elsevier LtdThis paper is concerned with the stability analysis problem for a new class of discrete-time recurrent neural ...
Liu, Y +8 more
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Analyzing Echo-state Networks Using Fractal Dimension [PDF]
, 2022 This work joins aspects of reservoir optimization, information-theoretic optimal encoding, and at its center fractal analysis. We build on the observation that, due to the recursive nature of recurrent neural networks, input sequences appear as fractal ...
Obst, Oliver +3 more
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Network of Recurrent Neural Networks
CoRR, 2017 Under review as a conference paper at AAAI ...
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NLOS Identification in WLANs Using Deep LSTM with CNN Features
Sensors, 2018 Identifying channel states as line-of-sight or non-line-of-sight helps to optimize location-based services in wireless communications. The received signal strength identification and channel state information are used to estimate channel conditions for ...
Viet-Hung Nguyen +3 more
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Generalised Analog LSTMs Recurrent Modules for Neural Computing
Frontiers in Computational Neuroscience, 2021 The human brain can be considered as a complex dynamic and recurrent neural network. There are several models for neural networks of the human brain, that cover sensory to cortical information processing. Large majority models include feedback mechanisms
Kazybek Adam +2 more
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