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Home > Intelligent Data Engineering and Automated Learning - IDEAL 2006: 7th International Conference, Burgos, Spain, September 20-23, 2006, Proceedings > Functional Networks and the Lagrange Polynomial Interpolation
Intelligent Data Engineering and Automated Learning - IDEAL 2006: 7th International Conference, Burgos, Spain, September 20-23, 2006, Proceedings |
Emilio Corchado; Hujun Yin; Vicente Botti; Colin Fyfe
Springer Berlin Heidelberg
Intelligent Data Engineering and Automated Learning - IDEAL 2006: 7th International Conference, Burgos, Spain, September 20-23, 2006, Proceedings
Functional Networks and the Lagrange Polynomial Interpolation
Authors

Cristina Solares; Eduardo W. Vieira; Roberto Mínguez

ARI Id

1664701626471_2799458

Access

Not Available Free

Pages

394-401

DOI

10.1007/11875581_48

Chapter URL

https://rd.springer.com/chapter/10.1007/11875581_48

Table of Contents of Book
Showing 1 to 20 of 172 entries
Chapters/HeadingsAuthor(s)PagesInfo
Front Matter
On Some of the Neural Mechanisms Underlying Adaptive Behavior
José Mira Mira
1-15
On Correlation Measures of Intuitionistic Fuzzy Sets
Zeshui Xu
16-24
A More Effective Constructive Algorithm for Permutation Flowshop Problem
Xingye Dong; Houkuan Huang; Ping Chen
25-32
A Fast Algorithm for Relevance Vector Machine
Zheng Rong Yang
33-39
Time Series Relevance Determination Through a Topology-Constrained Hidden Markov Model
Iván Olier; Alfredo Vellido
40-47
A Fast Data Preprocessing Procedure for Support Vector Regression
Zhifeng Hao; Wen Wen; Xiaowei Yang; Jie Lu; Guangquan Zhang
48-56
Classification by Weighting, Similarity and kNN
Naohiro Ishii; Tsuyoshi Murai; Takahiro Yamada; Yongguang Bao
57-64
An Improved EM Algorithm for Statistical Segmentation of Brain MRI
Yong Yang
65-72
Process State and Progress Visualization Using Self-Organizing Map
Risto Hakala; Timo Similä; Miki Sirola; Jukka Parviainen
73-80
Exploiting Spatio–temporal Data for the Multiobjective Optimization of Cellular Automata Models
Giuseppe A. Trunfio
81-89
Comparing Support Vector Machines and Feed-forward Neural Networks with Similar Parameters
Enrique Romero; Daniel Toppo
90-98
A New Model Selection Method for SVM
G. Lebrun; O. Lezoray; C. Charrier; H. Cardot
99-107
Speed-Up LOO-CV with SVM Classifier
G. Lebrun; O. Lezoray; C. Charrier; H. Cardot
108-115
Integration of Strategies Based on Relevance Feedback into a Tool for the Retrieval of Mammographic Images
A. Fornells; E. Golobardes; X. Vilasís; J. Martí
116-124
Generalization Performance of Exchange Monte Carlo Method for Normal Mixture Models
Kenji Nagata; Sumio Watanabe
125-132
Evolutionary Design of gdSOFPNN for Modeling and Prediction of NOx Emission Process
Tae-Chon Ahn; Ho-Sung Park
133-138
Upper Bounds for Variational Stochastic Complexities of Bayesian Networks
Kazuho Watanabe; Motoki Shiga; Sumio Watanabe
139-146
A Neural Stochastic Optimization Framework for Oil Parameter Estimation
Rafael E. Banchs; Hector Klie; Adolfo Rodriguez; Sunil G. Thomas; Mary F. Wheeler
147-154
Bootstrap Prediction Intervals for Nonlinear Time-Series
Daisuke Haraki; Tomoya Suzuki; Tohru Ikeguchi
155-162
Chapters/HeadingsAuthor(s)PagesInfo
Showing 1 to 20 of 172 entries
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