A model order selection criterion with applications to cardio-respiratory- renal systems

IEEE Transactions on Biomedical Engineering

Volumn 52, Issue 3, 2005, Pages 445-453

  Xiao, Xinshu ^a   Li, Ying ^b   Mukkamala, Ramakrishna ^b  

^a HARVARD MIT DIVISION OF HEALTH SCIENCES AND TECHNOLOGY   (United States)

^b Michigan State University   (United States)

Author keywords

AIC; BIC; FPE; Linear regression; LTI; MDL; Model order; SRM; System identification; VM

Indexed keywords

COMPUTER SIMULATION; ERROR ANALYSIS; LINEAR SYSTEMS; MATHEMATICAL MODELS; PHYSIOLOGY; REGRESSION ANALYSIS; SIGNAL PROCESSING; SIGNAL TO NOISE RATIO;

CARDIO-RESPIRATORY RENAL SYSTEMS; LINEAR REGRESSION MODELS; PHYSIOLOGIC SYSTEMS; SIGNAL PREDICTION ERROR (SPE);

CARDIOVASCULAR SYSTEM;

ANALYTICAL ERROR; ARTICLE; CARDIOVASCULAR SYSTEM; DATA ANALYSIS; FINAL PREDICTION ERROR; LINEAR REGRESSION ANALYSIS; MATHEMATICAL ANALYSIS; MEASUREMENT; MODEL; RESPIRATORY SYSTEM; SIGNAL NOISE RATIO; SIGNAL PREDICTION ERROR; SIMULATION; URINARY TRACT;

ALGORITHMS; BAROREFLEX; BLOOD PRESSURE; COMPUTER SIMULATION; HEART RATE; HUMANS; KIDNEY; LINEAR MODELS; MALE; MODELS, BIOLOGICAL; MODELS, CARDIOVASCULAR; MODELS, STATISTICAL; SIGNAL PROCESSING, COMPUTER-ASSISTED; TOTAL LUNG CAPACITY;

EID: 14844318118     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2004.843285     Document Type: Article

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