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» Neural Networks - A Systematic Introduction
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TSMC
1998
91views more  TSMC 1998»
13 years 7 months ago
Toward the border between neural and Markovian paradigms
— A new tendency in the design of modern signal processing methods is the creation of hybrid algorithms. This paper gives an overview of different signal processing algorithms si...
Piotr Wilinski, Basel Solaiman, A. Hillion, W. Cza...
BMCBI
2006
133views more  BMCBI 2006»
13 years 7 months ago
Web-based analysis of the mouse transcriptome using Genevestigator
Background: Gene function analysis often requires a complex and laborious sequence of laboratory and computer-based experiments. Choosing an effective experimental design generall...
Oliver Laule, Matthias Hirsch-Hoffmann, Tomas Hruz...
EELC
2006
128views Languages» more  EELC 2006»
13 years 11 months ago
Evolving Distributed Representations for Language with Self-Organizing Maps
We present a neural-competitive learning model of language evolution in which several symbol sequences compete to signify a given propositional meaning. Both symbol sequences and p...
Simon D. Levy, Simon Kirby
IWANN
2009
Springer
14 years 2 months ago
Fuzzy Logic, Soft Computing, and Applications
We survey on the theoretical and practical developments of the theory of fuzzy logic and soft computing. Specifically, we briefly review the history and main milestones of fuzzy ...
Inma P. Cabrera, Pablo Cordero, Manuel Ojeda-Acieg...
ML
1998
ACM
153views Machine Learning» more  ML 1998»
13 years 7 months ago
Bayesian Landmark Learning for Mobile Robot Localization
To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optim...
Sebastian Thrun