Generalized linear least squares algorithm for non-uniformly sampled biomedical system identification with possible repeated eigenvalues

Computer Methods and Programs in Biomedicine

Volumn 57, Issue 3, 1998, Pages 167-177

  Wong, Koon Pong ^a   Feng, Dagan ^a,b   Siu, Wan Chi ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b Biomed Multimedia Info Technol G ^*  (Australia)

Author keywords

Compartmental modeling; Parameter estimation; Repeated eigenvalues; System identification

Indexed keywords

EIGENVALUES AND EIGENFUNCTIONS; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; PARAMETER ESTIMATION; SIGNAL PROCESSING;

BIOMEDICAL SIGNAL PROCESSING; COMPARTMENT MODELING;

ALGORITHMS;

ALGORITHM; ARTICLE; BIOMEDICINE; COMPARTMENT MODEL; MATHEMATICAL MODEL; PARAMETER; SIGNAL PROCESSING; SYSTEM ANALYSIS;

ALGORITHMS; MATHEMATICS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 0032211362     PISSN: 01692607     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0169-2607(98)00035-2     Document Type: Article

References (23)

1. J.J. DiStefano III, Endocrine regulation: models and experimental design for system identification, In: Proceedings, Seminar on Large Scale Systems in the Mathematical Biosciences, Dubrovnik, Yugoslavia, 1968.
2. DiStefano III J.J. Matching the model and the experiment to the goals: data limitations, complexity and optimal experiment design for dynamic systems with biomedical signals. J. Cybern. Inf. Sci. 12:1979;6-20.
3. Wilson K., Fisher D.A., Sack J., DiStefano III J.J. System analysis and estimation of key parameters of thyroid hormone metabolism in sheep. Ann. Biomed. Eng. 5:1977;70-84.
4. Ogata K. Discrete-Time Control Systems. 1987;Prentice-Hall, Englewood Cliffs, NJ.
5. Crittenden J.T., Mulholland R.J., Hill J.I., Martinez E.F. Sampling and data analysis properties of Prony's method applied to model identification. Int. J. Syst. Sci. 14:1983;571-584.
6. Landaw E.M., DiStefano III J.J. Multiexponential, multicompartmental and non-compartmental modeling, II: Data analysis and statistical considerations. Am. J. Physiol. (Regulatory Integrative Comp. Physiol. 15). 246:1984;665-677.
7. Goodwin G.C., Payne R.L. Dynamic System Identification: Experiment Design and Data Analysis. 1977;Academic Press, New York.
8. T.C. Hsia, System Identification: Least Squares, Lexington Books, D.C. Heath and Company, 1977.
9. Mori F., DiStefano III J.J. Optimal non-uniform sampling interval and test input design for identification of physiological systems from very limited data. IEEE Trans. Autom. Control. 24:1979;893-899.
10. Yamamoto Y.L., Thompson C.J., Meyer E.E., Robertson J.S., Feindel W. Dynamic positron emission tomography for study of cerebral hemodynamics in a cross section of head using positron emitting 68Ga-EDTA and 77Kr. J. Comput. Assist. Tomogr. 1:1977;43-56.
11. Astrom K.J. Maximum-likelihood and prediction error methods. Automatica. 16:1980;551-557.
12. Ljung J. Asymptotic behaviour of the extended Kalman filter as a parameter estimator for linear systems. IEEE Trans. Autom. Control. 24:1979;36-50.
13. H. Unbehauen, G.P. Rao, Identification of continuous systems, Elsevier Science, 1987.
14. Feng D., Huang S.C., Wang Z., Ho D. An unbiased parametric imaging algorithm for non-uniformly sampled biomedical system parameter estimation. IEEE Trans. Med. Imag. 15:1996;512-518.
15. Chen K., Lawson M., Reiman E., Huang S.C., Feng D., Bandy D., Palant A., Yun L. Generalized least squares method for measuring myocardial blood flow with N-13 ammonia PET. J. Nucl. Med. 36:1995;7P.
16. Feng D., Wang Z., Huang S.C. A study on statistically reliable and computationally efficient algorithms for the measurement of local cerebral blood flow with positron emission tomography. IEEE Trans. Med. Imag. 12:1993;182-188.
17. Feng D., Ho D., Chen K., Wu L., Wang J., Liu R., Yeh S. An evaluation of the algorithms for determining local cerebral metabolic rates of glucose using positron emission tomography dynamic data. IEEE Trans. Med. Imag. 14:1995;697-710.
18. Feng D., Ho D., Iida H., Chen K. Techniques for functional imaging. Leondes C.T. Medical Imaging Techniques and Applications. 1997;85-145 Gordon and Breach, New York.
19. Fagarasan J.T., DiStefano III J.J. Hidden pools, hidden modes and visible repeated eigenvalues in compartmental models. Math. Biosci. 82:1986;87-113.
20. Akaike H. A new look at the statistical model identification. IEEE Trans. Autom. Control. 19:1974;716-723.
21. Akaike H. A Bayesian analysis of the minimum AIC procedure. Ann. Inst. Stat. Math. 30:1978;9-14.
22. Schwarz G. Estimating the dimension of a model. Ann. Stat. 6:1978;461-464.
23. Koehler A.B., Murphee E.S. A comparison of the Akaike and Schwarz criteria for selecting model order. Appl. Stat. 37:1988;187-195.