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TCAD
2008
107views more  TCAD 2008»
15 years 6 months ago
Power Grid Analysis and Optimization Using Algebraic Multigrid
Abstract--This paper presents a class of power grid analysis and optimization techniques, all of which are based on the algebraic-multigrid (AMG) method. First, a new AMG-based red...
Cheng Zhuo, Jiang Hu, Min Zhao, Kangsheng Chen
TEC
2008
135views more  TEC 2008»
15 years 6 months ago
Quantum Genetic Optimization
Abstract--The complexity of the selection procedure of a genetic algorithm that requires reordering, if we restrict the class of the possible fitness functions to varying fitness f...
Andrea Malossini, Enrico Blanzieri, T. Calarco
209
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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
JCP
2007
121views more  JCP 2007»
15 years 6 months ago
Learning by Discrimination: A Constructive Incremental Approach
Abstract— This paper presents i-AA1 , a constructive, incremental learning algorithm for a special class of weightless, self-organizing networks. In i-AA1 , learning consists of ...
Christophe G. Giraud-Carrier, Tony R. Martinez
JCSS
2007
116views more  JCSS 2007»
15 years 6 months ago
The most probable annotation problem in HMMs and its application to bioinformatics
Hidden Markov models (HMMs) are often used for biological sequence annotation. Each sequence feature is represented by a collection of states with the same label. In annotating a ...
Brona Brejová, Daniel G. Brown 0001, Tom&aa...