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TNN
2008
119views more  TNN 2008»
15 years 6 months ago
Selecting Useful Groups of Features in a Connectionist Framework
Abstract--Suppose for a given classification or function approximation (FA) problem data are collected using sensors. From the output of the th sensor, features are extracted, ther...
Debrup Chakraborty, Nikhil R. Pal
TNN
2008
82views more  TNN 2008»
15 years 6 months ago
Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks
In this paper, a general method for the numerical solution of maximum-likelihood estimation (MLE) problems is presented; it adopts the deterministic learning (DL) approach to find ...
Cristiano Cervellera, Danilo Macciò, Marco ...
TOG
2008
100views more  TOG 2008»
15 years 6 months ago
Interactive procedural street modeling
This paper addresses the problem of interactively modeling large street networks. We introduce a modeling framework that uses tensor fields to guide the generation of a street gra...
Guoning Chen, Gregory Esch, Peter Wonka, Pascal M&...
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CEE
2005
92views more  CEE 2005»
15 years 6 months ago
An adaptive call admission algorithm for cellular networks
In this paper, we first propose a new continuous action-set learning automaton and theoretically study its convergence properties and show that it converges to the optimal action....
Hamid Beigy, Mohammad Reza Meybodi
TPDS
2008
93views more  TPDS 2008»
15 years 6 months ago
Evaluating Dynamic Task Mapping in Network Processor Runtime Systems
Modern network processor systems require the ability to adapt their processing capabilities at runtime to changes in network traffic. Traditionally, network processor applications ...
Xin Huang, Tilman Wolf