Improved nonlinear PCA for process monitoring using support vector data description

Journal of Process Control

Volumn 21, Issue 9, 2011, Pages 1306-1317

  Liu, Xueqin ^a   Li, Kang ^a   McAfee, Marion ^b   Irwin, George W ^a  

^a QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

^b Atlantic Technological University   (Ireland)

Author keywords

Fast Recursive Algorithm; Nonlinear principal component analysis; Principal curves; Radial basis function network; Support vector datadescription

Indexed keywords

FAST RECURSIVE ALGORITHMS; NONLINEAR PRINCIPAL COMPONENT ANALYSIS; PRINCIPAL CURVE; RADIAL BASIS FUNCTIONS; SUPPORT VECTOR DATADESCRIPTION;

ALGORITHMS; DATA DESCRIPTION; DATA HANDLING; DISTRIBUTION FUNCTIONS; ELECTRIC NETWORK TOPOLOGY; IMAGE SEGMENTATION; METADATA; NEURAL NETWORKS; PROBABILITY DISTRIBUTIONS; PROCESS CONTROL; PROCESS MONITORING; RADIAL BASIS FUNCTION NETWORKS; RECURSIVE FUNCTIONS; TOPOLOGY; VECTOR SPACES;

PRINCIPAL COMPONENT ANALYSIS;

EID: 80052565753     PISSN: 09591524     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jprocont.2011.07.003     Document Type: Article

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