Results 31 to 40 of about 2,008,811 (296)

A VLSI neuromorphic device for implementing spike-based neural networks [PDF]

, 2011
Indiveri G, Chicca E. A VLSI neuromorphic device for implementing spike-based neural networks. Presented at the Proceedings of the 21st Italian Workshop on Neural Nets (WIRN).We present a neuromorphic VLSI device which comprises hybrid analog/digital ...
Morabito, C. F., Indiveri, G., Apolloni, B., Esposito, A., Chicca, Elisabetta ; https://orcid.org/, Bassis, S.   +5 more
core   +1 more source

Evolutionary optimization of echo state networks: multiple motor pattern learning [PDF]

, 2010
Krause AF, Dürr V, Bläsing B, Schack T. Evolutionary optimization of echo state networks: multiple motor pattern learning. In: Artificial neural networks and intelligent information processing : proceedings of the 6th International Workshop on ...
Krause, André Frank, Bläsing, Bettina, Schack, Thomas, Dürr, Volker ; https://orcid.org/   +3 more
core   +1 more source

A BiLSTM cardinality estimator in complex database systems based on attention mechanism

CAAI Transactions on Intelligence Technology, 2022
An excellent cardinality estimation can make the query optimiser produce a good execution plan. Although there are some studies on cardinality estimation, the prediction results of existing cardinality estimators are inaccurate and the query efficiency ...
Qiang Zhou, Guoping Yang, Haiquan Song, Jin Guo, Yadong Zhang, Shengjie Wei, Lulu Qu, Louis Alberto Gutierrez, Shaojie Qiao   +8 more
doaj   +1 more source

A comprehensive framework from real‐time prognostics to maintenance decisions

IET Collaborative Intelligent Manufacturing, 2021
Studying the influence of imperfect prognostics information on maintenance decisions is an underexplored area. To bridge this gap, a new comprehensive maintenance support system is proposed. First, a survival theory‐based prognostics module employing the
Amit Kumar Jain, Maharshi Dhada, Marco Perez Hernandez, Manuel Herrera, Ajith Kumar Parlikad   +4 more
doaj   +1 more source

PNNARMA model: an alternative to phenomenological models in chemical reactors [PDF]

, 2001
This paper is focused on the development of non-linear neural models able to provide appropriate predictions when acting as process simulators. Parallel identification models can be used for this purpose.
J.M. Zaldı́var, Zaldívar, J.M., Galván, Inés M., I.M. Galván, P. Isasi, Isasi, Pedro   +5 more
core   +1 more source

Parallelizing Linear Recurrent Neural Nets Over Sequence Length

CoRR, 2017
9 pages.
Eric Martin, Chris Cundy
openaire   +4 more sources

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, Yaochu Jin, Bernhard Sendhoff, Jin, Yaochu, Kowalczykiewicz, Michal, Yi Cao, Cao, Yi, Michal Kowalczykiewicz, Sendhoff, B, Kowalczykiewicz, M, Cao, Y, Jin, Y, Jin, Yaochu ; https://orcid.org/   +12 more
core   +1 more source

A Model for Programmability and Virtuality in Dynamical Neural Networks [PDF]

, 2009
In this dissertation a fixed-weight architecture for Continuous Time Recurrent Neural Networks (CTRNNs) is proposed in order to give an account for biological phenomena, controlled by neuronal activity, in which changes of behavior occur so fast that ...
Donnarumma, Francesco
core   +1 more source

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, Ritter, Helge ; https://orcid.org/, Haschke, Robert ; https://orcid.org/, Steil, Jochen J., Hornik, Kurt, Bischof, Horst, Jochen J. Steil, Robert Haschke, Helge Ritter   +8 more
core   +1 more source

Performance evaluation of deep neural networks for forecasting time‐series with multiple structural breaks and high volatility

CAAI Transactions on Intelligence Technology, 2021
The problem of automatic and accurate forecasting of time‐series data has always been an interesting challenge for the machine learning and forecasting community.
Rohit Kaushik, Shikhar Jain, Siddhant Jain, Tirtharaj Dash   +3 more
doaj   +1 more source