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ICCAD
2003
IEEE
161views Hardware» more  ICCAD 2003»
14 years 4 months ago
A General S-Domain Hierarchical Network Reduction Algorithm
This paper presents an efficient method to reduce complexities of a linear network in s-domain. The new method works on circuit matrices directly and reduces the circuit complexi...
Sheldon X.-D. Tan
CORR
2010
Springer
150views Education» more  CORR 2010»
13 years 7 months ago
Extraction of Symbolic Rules from Artificial Neural Networks
Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions c...
S. M. Kamruzzaman, Md. Monirul Islam
ICDM
2006
IEEE
130views Data Mining» more  ICDM 2006»
14 years 1 months ago
Efficient Clustering for Orders
Lists of ordered objects are widely used as representational forms. Such ordered objects include Web search results or best-seller lists. Clustering is a useful data analysis tech...
Toshihiro Kamishima, Shotaro Akaho
ISNN
2007
Springer
14 years 1 months ago
Recurrent Fuzzy CMAC for Nonlinear System Modeling
Normal fuzzy CMAC neural network performs well because of its fast learning speed and local generalization capability for approximating nonlinear functions. However, it requires hu...
Floriberto Ortiz Rodriguez, Wen Yu, Marco A. Moren...
NN
2006
Springer
163views Neural Networks» more  NN 2006»
13 years 7 months ago
Machine learning approaches for estimation of prediction interval for the model output
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Durga L. Shrestha, Dimitri P. Solomatine