Multiway kernel independent component analysis based on feature samples for batch process monitoring

Neurocomputing

Volumn 72, Issue 7-9, 2009, Pages 1584-1596

  Tian, Xuemin ^a   Zhang, Xiaoling ^a   Deng, Xiaogang ^a   Chen, Sheng ^b  

^a CHINA UNIVERSITY OF PETROLEUM   (China)

^b UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

Batch process; Feature samples; Kernel independent component analysis; Nonlinearity

Indexed keywords

BATCH PROCESS; BATCH PROCESS MONITORING; COMPUTATIONAL COSTS; DATA SETS; DATA SPACES; FEATURE SAMPLES; FED BATCHES; HIGH-DIMENSIONAL; INDEPENDENT COMPONENTS; INPUT SAMPLES; KERNEL FUNCTIONS; KERNEL ICA; KERNEL INDEPENDENT COMPONENT ANALYSIS; LINEAR SPACES; MONITORING METHODS; MONITORING TECHNIQUES; NON-LINEAR FEATURES; NON-LINEAR VARIATIONS; NONLINEARITY; ON-LINE MONITORING; PENICILLIN FERMENTATION PROCESS; PROCESS VARIATIONS; SIMULATION RESULTS; SQUARED PREDICTION ERRORS; TRAINING DATASET;

BATCH DATA PROCESSING; BENCHMARKING; BIOCHEMICAL ENGINEERING; ERROR STATISTICS; FEATURE EXTRACTION; FERMENTATION; HEMODYNAMICS; MICA; NONLINEAR ANALYSIS; OPTICAL COMMUNICATION; PROCESS CONTROL; PROCESS MONITORING; SILICATE MINERALS;

INDEPENDENT COMPONENT ANALYSIS;

ALGORITHM; ANALYTICAL ERROR; ARTICLE; BATCH PROCESS; FERMENTATION; INDEPENDENT COMPONENT ANALYSIS; INTERMETHOD COMPARISON; KERNEL METHOD; LINEAR SYSTEM; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; NONLINEAR SYSTEM; PREDICTION; PRIORITY JOURNAL; STATISTICAL ANALYSIS;

EID: 61849101892     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2008.09.003     Document Type: Article

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