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ITNG
2010
IEEE
13 years 7 months ago
Scalable Intrusion Detection with Recurrent Neural Networks
The ever-growing use of the Internet comes with a surging escalation of communication and data access. Most existing intrusion detection systems have assumed the one-size-fits-all...
Longy O. Anyanwu, Jared Keengwe, Gladys A. Arome
DSS
2006
118views more  DSS 2006»
13 years 9 months ago
Part family formation through fuzzy ART2 neural network
In order to overcome some unavoidable factors, like shift of the part, that influence the crisp neural networks' recognition, the present study is dedicated in developing a n...
R. J. Kuo, Y. T. Su, C. Y. Chiu, Kai-Ying Chen, Fa...
IJCNN
2000
IEEE
14 years 1 months ago
Sensitivity Analysis for Conic Section Function Neural Networks
Sensitivity analysis is a method for extracting the cause and effect relationship between the inputs and outputs of the network. After training a neural network, one may want to k...
Lale Özyilmaz, Tülay Yildirim

Publication
273views
12 years 7 months ago
 Beyond Graphs: A New Synthesis.
Artificial neural networks, electronic circuits, and gene networks are some examples of systems that can be modeled as networks, that is, as collections of interconnected nodes. I...
Mattiussi, Claudio, Dürr, Peter, Marbach, Daniel ...
NN
1998
Springer
112views Neural Networks» more  NN 1998»
13 years 8 months ago
Continuous attractors and oculomotor control
A recurrent neural network can possess multiple stable states, a property that many brain theories have implicated in learning and memory. There is good evidence for such multista...
H. Sebastian Seung