Fuel-type identification using joint probability density arbiter and soft-computing techniques

IEEE Transactions on Instrumentation and Measurement

Volumn 61, Issue 2, 2012, Pages 286-296

  Xu, Lijun ^a   Tan, Cheng ^a   Li, Xiaomin ^a   Cheng, Yanting ^a   Li, Xiaolu ^a  

^a BEIHANG UNIVERSITY   (China)

Author keywords

Feature extraction; fuel; identification; joint probability density; principal component analysis (PCA); soft computing technique

Indexed keywords

FEATURE DATA; FLAME OSCILLATIONS; FUEL TYPES; INDUSTRIAL BOILERS; JOINT PROBABILITY; JOINT PROBABILITY DENSITY ARBITERS; NEURAL NETWORK MODEL; PRINCIPAL COMPONENT ANALYSIS (PCA); PRINCIPAL COMPONENTS; SOFTCOMPUTING TECHNIQUES; SUPPORT VECTOR; TIME AND FREQUENCY DOMAINS;

ASYNCHRONOUS SEQUENTIAL LOGIC; FEATURE EXTRACTION; FUELS; IDENTIFICATION (CONTROL SYSTEMS); NEURAL NETWORKS; PROBABILITY; PROBABILITY DENSITY FUNCTION;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84855465705     PISSN: 00189456     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIM.2011.2164836     Document Type: Article

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