Parameter estimation by reduced-order linear associative memory (ROLAM)

IEEE Transactions on Biomedical Engineering

Volumn 44, Issue 4, 1997, Pages 297-305

  Tawfik, Bassel ^a   Durand, Dominique M ^b  

^a CAIRO UNIVERSITY   (Egypt)

^b Case Western Reserve University   (United States)

Author keywords

Linear associative memory; parameter estimation

Indexed keywords

ARTICLE; GRANULE CELL; MEMORY; NERVE CELL; NONLINEAR SYSTEM; OSCILLATOR; STATE DEPENDENT LEARNING;

ALGORITHMS; ASSOCIATION LEARNING; CYBERNETICS; DENTATE GYRUS; ELECTRIC IMPEDANCE; MEMORY; MODELS, NEUROLOGICAL; NEURAL CONDUCTION; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS;

EID: 0030898281     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/10.563299     Document Type: Article

References (19)

1. Y. Bard, Nonlinear Parameter Estimation. New York: Academic, 1974.
2. I. Borno and Z. Gajic, "Parallel algorithm for solving coupled algebraic Lyapunov equations of discrete-time jump linear systems," Computers Math. Applicat., vol. 30, no. 7, pp. 1-4, 1995.
3. J. J. Dongarra and D. W. Walker, "Software libraries for linear algebra computations on high performance computers," SI AM Rev., vol. 37, no. 2, pp. 151-180, 1995.
4. D. Durand, "The somatic shunt cable model for neurons," Biophys. J., vol. 46, pp. 645-653, 1984.
5. P. M. Frank, Introduction to System Sensitivity Theory. New York: Academic, 1978.
6. C. S. Hsu, Cell-to-Cell Mapping a Method of Global Analysis for Nonlinear Systems. Berlin, Germany: Springer-Verlag, 1987.
7. E. A. Jackson, Perspectives of Nonlinear Dynamics. Cambridge, U.K.: Cambridge Univ. Press, vol. 1, 1989.
8. R. E. Kalaba and F. E. Udwadia, "Associative memory approach to the identification od structural and mechanical systems," J. Optimization Theory, Applicat., vol. 76, no. 2, pp. 207-223, 1993.
9. T. Kohonen, Self-Organization and Associative Memory. Berlin, Germany: Springer-Verlag, 1988.
10. J. C. Lin and D. M. Durand, "Wieghted linear association memory approach to nonlinear parameter estimation," J. Optim. Theory, Applicat., 1996.
11. Z. S. Liu, "On-line parameter identification algorithms based on householder transformation," IEEE Trans. Signal Processing., vol. 41, no. 9, pp. 2863-2871, 1993.
12. H. Mino, "A parametric modeling of ionic channel current fluctuations using third-order statistics and its application to estimation of the kinetic parameters of single ionic channels," IEEE Trans. Biomed. Eng., vol. 40, no. 9, pp. 970-980, 1993.
13. F. Moss and K. Wiesenfeld, "The benefits of background noise," Scientific American, pp. 66-69, Aug. 1995.
14. B. N. Parlett, The Symmetric Eigenvalue Problem. Englewood Cliffs, NJ: Prentice Hall, 1980.
15. D. T. Raphael, "A radial solution of the van der Pol-Rayleigh limit cycle oscillator for small e," J. Acoust. Soc. Amer., vol. 94, no. 1, pp. 428-436, 1993.
16. G. W. Stewart and Ji-guang Sun, Matrix Perturbation Theory. New York: Academic, 1990.
17. B. Tawfik and D. M. Durand, "Nonlinear parameter estimation by linear association: Application to a five-parameter passive neuron model," IEEE Trans. Biomed. Eng., vol. 41, no. 5, pp. 461169, 1994.
18. J. Tellinghuisen, "Effect of background on the least-squares estimation of exponential decay parameters," Anal. Chem., vol. 65, pp. 1277-1280, 1993.
19. D. S. Watkins, Fundamentals of Matrix Computations. New York: Wiley, 1991. [20] D. A. Wismer and R. Chattergy, "Introduction to nonlinear optimization; A problem solving approach," in North Holland Series in Systems and Engineering. Amsterdam, The Netherlands: North Holand, 1978.