Files in this item

FilesDescriptionFormat

application/pdf

application/pdf3023164.pdf (6MB)Restricted to U of Illinois
(no description provided)PDF

Description

Title:A Bayesian Fusion Approach and Its Application to Integrating Audio and Visual Signals in HCI
Author(s):Pan, Hao
Doctoral Committee Chair(s):Liang, Zhi-Pei
Department / Program:Electrical Engineering
Discipline:Electrical Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Computer Science
Abstract:Finally, kernel canonical correlation analysis (CCA) is developed to model nonlinear or high-order correlations between signals from two sources. Kernel CCA uses kernel principal component analysis (PCA), which elegantly combines a nonlinear transformation and linear PCA into a one-step calculation, so as to avoid the computational burden of high/infinite-dimensional nonlinear transformations.
Issue Date:2001
Type:Text
Language:English
Description:140 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2001.
URI:http://hdl.handle.net/2142/80738
Other Identifier(s):(MiAaPQ)AAI3023164
Date Available in IDEALS:2015-09-25
Date Deposited:2001


This item appears in the following Collection(s)

Item Statistics