Results 301 to 310 of about 7,083,147 (335)

MARKOV RECURRENT NEURAL NETWORKS

2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP), 2018
Deep learning has achieved great success in many real-world applications. For speech and language processing, recurrent neural networks are learned to characterize sequential patterns and extract the temporal information based on dynamic states which are evolved through time and stored as an internal memory.
Che-Yu Kuo, Jen-Tzung Chien
openaire   +2 more sources

Fault diagnosis of rolling bearings with recurrent neural network-based autoencoders.

ISA transactions, 2018
As the rolling bearings being the key part of rotary machine, its healthy condition is quite important for safety production. Fault diagnosis of rolling bearing has been research focus for the sake of improving the economic efficiency and guaranteeing ...
Han Liu, Jianzhong Zhou, Yang Zheng, Wei Jiang, Yun-Cheng Zhang   +4 more
semanticscholar   +1 more source

Recurrent Neural Networks Are Universal Approximators

International Journal of Neural Systems, 2006
Recurrent Neural Networks (RNN) have been developed for a better understanding and analysis of open dynamical systems. Still the question often arises if RNN are able to map every open dynamical system, which would be desirable for a broad spectrum of applications.
Anton Maximilian Schäfer, Hans-Georg Zimmermann   +1 more
openaire   +3 more sources

Recurrent neural networks for syllabification

Speech Communication, 1993
Abstract An important procedure in many prosodic analysis systems is locating syllables. The location of syllables is used in the identification of stress and of pitch accents, which in turn form the basis for the analysis of rhythm and intonation. This paper presents a novel syllabification system utilising recurrent neural networks which operates ...
openaire   +1 more source

Recurrent neural network based language model

Interspeech, 2010
Tomas Mikolov, M. Karafiát, Lukáš Burget, J. Černocký, S. Khudanpur   +4 more
semanticscholar   +1 more source

Application of recurrent neural network to mechanical fault diagnosis: a review

Journal of Mechanical Science and Technology, 2022
Junjun Zhu, Q. Jiang, Yehu Shen, Chen-Hui Qian, Feng-Yu Xu, Qi-Xin Zhu   +5 more
semanticscholar   +1 more source

Randomized Recurrent Neural Networks.

2018
Neural Networks (NNs) with random weights represent nowadays a topic of consolidated use in the Machine Learning research community. In this contribution we focus in particular on recurrent NN models, which in a randomized setting represent a case of particular interest per se, entailing a number of intriguing research challenges primarily related to ...
Claudio Gallicchio, Alessio Micheli, Peter Tino   +2 more
openaire   +2 more sources

Selective Recurrent Neural Network

Neural Processing Letters, 2012
It is known that recurrent neural networks may have difficulties remembering data over long time lags. To overcome this problem, we propose an extended architecture of recurrent neural networks, which is able to deal with long time lags between relevant input signals.
openaire   +1 more source

Long short-term memory recurrent neural network architectures for large scale acoustic modeling

Interspeech, 2014
Hasim Sak, A. Senior, F. Beaufays
semanticscholar   +1 more source

Reservoir computing approaches to recurrent neural network training

Computer Science Review, 2009
M. Lukoševičius, Herbert Jaeger
semanticscholar   +1 more source