Recursive Linear Smoothed Newton Predictors for Polynomial Extrapolation

IEEE Transactions on Instrumentation and Measurement

Volumn 41, Issue 4, 1992, Pages 510-516

  Ovaska, Seppo J ^a   Vainio, Olli ^b  

^a Research Center KONE Elevators ^*  (Finland)

^b TAMPERE UNIVERSITY OF TECHNOLOGY   (Finland)

Author keywords

forward prediction; Newton type prediction; Polynomial extrapolation; recursive prediction

Indexed keywords

POLYNOMIALS; SIGNAL PROCESSING; TRANSFER FUNCTIONS;

IIR PREDICTORS; LINEAR SMOOTHED NEWTON PREDICTORS;

SIGNAL FILTERING AND PREDICTION;

EID: 0026909557     PISSN: 00189456     EISSN: 15579662     Source Type: Journal    
DOI: 10.1109/19.155917     Document Type: Article

References (16)

1. D. R. Morgan and A. A. Aridgides, “Interpolation and extrapolation of an ideal bandlimited random process,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 35, pp. 43-47, Jan. 1987.
2. P. Heinonen and Y. Neuvo, “FIR-median hybrid filters with predictive FIR substructures,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 36, pp. 892-899, June 1988.
3. R. W. Schafer and L. R. Rabiner, “A digital signal processing approach to interpolation,” Proc. IEEE, vol. 61, pp. 692-702, June 1973.
4. R. Pintelon and J. Schoukens, “Real-time integration and differentiation of analog signals by means of digital filtering,” IEEE Trans. Instrum. Meas., vol. 39, pp. 923-927, Dec. 1990.
5. W. Feller, An Introduction to Probability Theory and Its Applications Vol. II (2nd ed.). New York: John Wiley & Sons, 1971.
6. S. J. Ovaska, “Newton-type predictors-a signal processing oriented viewpoint,” Signal Processing, vol. 25, pp. 251-257, Nov. 1991.
7. V. V. Athani, “Microprocessor based data acquisition system,” Microprocessors and Microsystems, vol. 3, pp. 359-364, Oct. 1979.
8. S. J. Ovaska, “Distributed architecture of an adaptive positioning servo,” IEEE Trans. Instrum. Meas., vol. 39, pp. 403-408, Apr. 1990.
9. S. J. Ovaska, “Lost-sample predictor to replace a conventional transmission error correction method in instrumentation and measurement applications,” in Proc. 7th IMEKO Int. Symp. Techn. Diagn., Helsinki, Finland, Sept. 1990, pp. 384-391.
10. S. J. Ovaska, “FIR prediction using Newton's backward interpolation algorithm with smoothed successive differences,” IEEE Trans. Instrum. Meas., vol. 40, pp. 811-815, Oct. 1991.
11. S. S. Rao, Optimization Theory and Applications (2nd ed.). New Delhi, India: Wiley Eastern, 1984.
12. R. W. Daniels, An Introduction to Numerical Methods and Optimization Techniques. New York, NY: North-Holland, 1978.
13. A. V. Oppenheim and R. W. Schafer, Discrete-Time Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1989.
14. T. G. Campbell and Y. Neuvo, “Predictive FIR filters with low computational complexity,” IEEE Trans. Circuits Syst., vol. 38, pp. 1067-1071, Sept. 1991.
15. P. Heinonen, “Linear median hybrid filters,” Doctoral dissertation, Tampere University of Technology, Department of Electrical Engineering, Tampere, Finland, 1986.
16. S. J. Ovaska, “Improving the velocity sensing resolution of pulse encoders by FIR prediction,” IEEE Trans. Instrum. Meas., vol. 40, pp. 657-658, June 1991.