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» Verifying Properties of Neural Networks
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IJON
1998
119views more  IJON 1998»
13 years 5 months ago
Comment on "Recurrent neural networks: A constructive algorithm, and its properties"
In their paper [1], Tsoi and Tan present what they call a "canonical form", which they claim to be identical to that proposed in Nerrand et al [2]. They also claim that ...
Léon Personnaz, Gérard Dreyfus
JCC
2007
127views more  JCC 2007»
13 years 5 months ago
Prediction of GFP spectral properties using artificial neural network
Abstract: In this study, we applied artificial neural network, implementing the backpropagation algorithm, for the prediction of the excitation and emission maxima of green fluores...
Chanin Nantasenamat, Chartchalerm Isarankura-Na-Ay...
ESWA
2008
223views more  ESWA 2008»
13 years 5 months ago
Credit risk assessment with a multistage neural network ensemble learning approach
In this study, a multistage neural network ensemble learning model is proposed to evaluate credit risk at the measurement level. The proposed model consists of six stages. In the ...
Lean Yu, Shouyang Wang, Kin Keung Lai
IJCNN
2000
IEEE
13 years 9 months ago
Comparison of Text-Dependent Speaker Identification Methods for Short Distance Telephone Lines Using Artificial Neural Networks
The transition to democracy in South Africa has brought with it certain challenges. The main challenge is to get rid of crime and corruption.This paper presents a technique to com...
Ganesh K. Venayagamoorthy, Narend Sundepersadh
NIPS
1996
13 years 6 months ago
Monotonicity Hints
: Neural networks are competitive tools for classification problems. In this context, a hint is any piece of prior side information about the classification. Common examples are mo...
Joseph Sill, Yaser S. Abu-Mostafa