Variance Reduction in Analytical Chemistry : New Numerical Methods in Chemometrics and Molecular Simulation

Variance Reduction in Analytical Chemistry : New Numerical Methods in Chemometrics and Molecular Simulation

This thesis is based on five papers addressing variance reduction in different ways. The papers have in common that they all present new numerical methods. Paper I investigates quantitative structure-retention relationships from an image processing perspective, using an artificial neural network to...

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Bibliographic Details
Main Author: Åberg, K. Magnus
Format: Doctoral Thesis
Language:English
Published: Stockholms universitet, Institutionen för analytisk kemi 2004
Subjects:
chemometrics
pulse-coupled neural networks
peak alignment
class separability
molecular dynamics
Monte Carlo
expanded ensembles
free energy
Analytical chemistry
Analytisk kemi
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-283
http://nbn-resolving.de/urn:isbn:91-7265-968-8

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-283
http://nbn-resolving.de/urn:isbn:91-7265-968-8

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