A computer program for linear nonparametric and parametric identification of biological data.

A computer program package for parametric ad nonparametric linear system identification of both static and dynamic biological data, written for an LSI-11 minicomputer with 28 K of memory, is described. The program has 11 possible commands including an instructional help command. A user can perform nonparametric spectral analysis and estimation of autocorrelation and partial autocorrelation functions of univariate data and estimate nonparametrically the transfer function and possibly an associated noise series of bivariate data. In addition, the commands provide the user the means to derive a parametric autoregressive moving average model for univariate data, to derive a parametric transfer function and noise model for bivariate data, and to perform several model evaluation tests such as pole-zero cancellation, examination of residual whiteness and uncorrelatedness with the input. The program, consisting of a main program and driver subroutine as well as six overlay segments, may be run interactively or automatically.

[1]  P. Matthews,et al.  Comparison of electromyogram spectra with force spectra during human elbow tremor. , 1980, The Journal of physiology.

[2]  L. Zetterberg.  Estimation of parameters for a linear difference equation with application to EEG analysis , 1969 .

[3]  D. O. Walter,et al.  Spectral analysis for electroencephalograms: mathematical determination of neurophysiological relationships from records of limited duration. , 1963, Experimental neurology.

[4]  Joseph J. DiStefano,et al.  Identification of the dynamics of thyroid hormone metabolism , 1975, Autom..

[5]  Lennart Ljung,et al.  Analysis of recursive stochastic algorithms , 1977 .

[6]  T. Söderström.  On model structure testing in system identification , 1977 .

[7]  M. Bartlett.  On the Theoretical Specification and Sampling Properties of Autocorrelated Time‐Series , 1946 .

[8]  G. Box,et al.  Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models , 1970 .

[9]  Karl Johan Åström,et al.  BOOK REVIEW SYSTEM IDENTIFICATION , 1994, Econometric Theory.

[10]  W. Gersch.  Spectral analysis of EEG's by autoregressive decomposition of time series , 1970 .

[11]  J. Tukey,et al.  An algorithm for the machine calculation of complex Fourier series , 1965 .

[12]  Autoregressive Analysis Applied to Surface and Serosal Measurements of the Human Stomach , 1979, IEEE Transactions on Biomedical Engineering.

[13]  S. B. Davis.  Preliminary results using inverse filtering of speech for automatic evaluation of laryngeal pathology , 1975 .

[14]  Daniel Graupe,et al.  Functional Separation of EMG Signals via ARMA Identification Methods for Prosthesis Control Purposes , 1975, IEEE Transactions on Systems, Man, and Cybernetics.

[15]  George A. Bekey,et al.  Tactile Information Processing by Human Operators in Control Systems , 1978, IEEE Transactions on Systems, Man, and Cybernetics.

[16]  James Durbin,et al.  The fitting of time series models , 1960 .

[17]  R. Poppele.  Systems Approach to the Study of Muscle Spindles , 1973 .

[18]  A. Jazwinski.  Stochastic Processes and Filtering Theory , 1970 .

[19]  A.J.W. van den Boom,et al.  The determination of the orders of process-and noise dynamics , 1974, Autom..

[20]  Heinz Unbehauen,et al.  Tests for determining model order in parameter estimation , 1974, Autom..

[21]  C. Metzler.  Usefulness of the Two-Compartment Open Model in Pharmacokinetics , 1971 .

[22]  Arthur Gelb,et al.  Applied Optimal Estimation , 1974 .

[23]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[24]  C. Woodside.  Estimation of the order of linear systems , 1971 .

[25]  Gwilym M. Jenkins,et al.  Time series analysis, forecasting and control , 1971 .

[26]  D. Twieg,et al.  Parameter estimation applied to noninvasive radiocardiographic data for determination of left ventricular ejection and valvular regurgitant fractions , 1977 .

[27]  Thomas D. Pollard,et al.  Actin And Myosin And Cell Movemen , 1974 .

[28]  D. G. Watts,et al.  Spectral analysis and its applications , 1968 .

[29]  G. C. Joyce,et al.  The effects of load and force on tremor at the normal human elbow joint , 1974, The Journal of physiology.

[30]  Lawrence Stark,et al.  Neurological Control Systems: Studies in Bioengineering , 1995 .

[31]  Chris Chatfield,et al.  Introduction to Statistical Time Series. , 1976 .

[32]  A. Papoulis.  Signal Analysis , 1977 .

[33]  George E. P. Box,et al.  Time Series Analysis: Forecasting and Control , 1977 .

[34]  V. Barnett,et al.  Applied Linear Statistical Models , 1975 .

[35]  D.G. Dudley,et al.  Dynamic system identification experiment design and data analysis , 1979, Proceedings of the IEEE.

[36]  A M Junker,et al.  Study of Identification Methods and Structural Modeling Techniques on Empirical Data from a Motion Study , 1977 .

[37]  J. McConnell,et al.  Identification techniques for the renal function , 1979 .

[38]  Yonemoto,et al.  Automatic classification of EEGs: A parametric model new features for classification approach , 1977 .

[39]  V. Panuska.  A new form of the extended Kalman filter for parameter estimation in linear systems , 1979, 1979 18th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[40]  Lennart Ljung,et al.  Analysis of some On-Line Identification Methods , 1976 .

[41]  Ewart R. Carson,et al.  The Identification of Metabolic Systems - A Review , 1979 .

[42]  Lennart Ljung,et al.  A theoretical analysis of recursive identification methods , 1978, Autom..