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ACSC
2008
IEEE
13 years 9 months ago
An investigation of the state formation and transition limitations for prediction problems in recurrent neural networks
Recurrent neural networks are able to store information about previous as well as current inputs. This "memory" allows them to solve temporal problems such as language r...
Angel Kennedy, Cara MacNish
IJACTAICIT
2010
153views more  IJACTAICIT 2010»
13 years 2 months ago
Prediction Using Recurrent Neural Network Based Fuzzy Inference system by the Modified Bees Algorithm
In this paper, a recurrent neural network based fuzzy inference system (RNFIS) for prediction is proposed. A recurrent network is embedded in the RNFIS by adding feedback connecti...
Zahra Khanmirzaei, Mohammad Teshnehlab
MLMI
2007
Springer
14 years 1 months ago
Binaural Speech Separation Using Recurrent Timing Neural Networks for Joint F0-Localisation Estimation
A speech separation system is described in which sources are represented in a joint interaural time difference-fundamental frequency (ITD-F0) cue space. Traditionally, recurrent t...
Stuart N. Wrigley, Guy J. Brown
EUROCOLT
1997
Springer
13 years 11 months ago
Vapnik-Chervonenkis Dimension of Recurrent Neural Networks
Most of the work on the Vapnik-Chervonenkis dimension of neural networks has been focused on feedforward networks. However, recurrent networks are also widely used in learning app...
Pascal Koiran, Eduardo D. Sontag
EUSFLAT
2009
184views Fuzzy Logic» more  EUSFLAT 2009»
13 years 5 months ago
Recurrent Neural Kalman Filter Identification and Indirect Adaptive Control of a Continuous Stirred Tank Bioprocess
The aim of this paper is to propose a new Kalman Filter Recurrent Neural Network (KFRNN) topology and a recursive Levenberg-Marquardt (L-M) algorithm of its learning capable to est...
Ieroham S. Baruch, Carlos Román Mariaca Gas...