Adaptive IIR Filtering Algorithms for System Identification: A General Framework

IEEE Transactions on Education

Volumn 38, Issue 1, 1995, Pages 54-66

  Netto, Sergio L ^a   Diniz, Paulo S R ^b   Agathoklis, Panajotis ^c  

^a PONTIFICAL CATHOLIC UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^b FEDERAL UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^c UNIVERSITY OF VICTORIA   (Canada)

Author keywords

adaptive algorithms; adaptive filters

Indexed keywords

ADAPTIVE ALGORITHMS; ADAPTIVE FILTERING; COMPUTATIONAL COMPLEXITY; COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; IDENTIFICATION (CONTROL SYSTEMS); MATHEMATICAL MODELS; POLES AND ZEROS; SYSTEM STABILITY;

ADAPTIVE SIGNAL PROCESSING;

DIGITAL FILTERS;

EID: 0029253876     PISSN: 00189359     EISSN: 15579638     Source Type: Journal    
DOI: 10.1109/13.350221     Document Type: Article

References (71)

1. B. D. O. Anderson and C. R. Johnson, Jr., “On reduced-order adaptive output error identification and adaptive IIR filtering,” IEEE Trans. Automat. Cont., vol. AC-27, no. 4, pp. 927-933, Aug. 1982.
2. K. J. Astrom and P. Eykhoff. “System identification-A survey,” Automation, vol. 7, no. 2, pp. 123-162, Mar. 1971.
3. K. J. Astrom and T. Soderstrom, “Uniqueness of the maximum likelihood estimates of the parameters of an ARMA model,” IEEE Trans. Automat. Cont., vol. AC-19, no. 6, pp. 769-773, Dec. 1974.
4. J. A. Cadzow, “Recursive digital filter synthesis via gradient based algorithms,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-24, no. 5, pp. 349-355, Oct. 1976.
5. J. E. Cousseau and P. S. R. Diniz, “Alternative parallel realization for adaptive IIR filters,” in Proc. Int. Symp. Circuits Syst., 1990, pp. 1927-1930.
6. R. A. David, “A modified cascade structure for IIR adaptive algorithms,” in Proc. 15th Asilomar Conf Circuits, Syst. Comput., 1981, pp. 175-179.
7. M. Dentino, J. M. MeCool, and B. Widrow, “Adaptive filtering in the frequency domain,” Proc. IEEE, vol. 66, no. 12, pp. 1658-1659, Dec. 1978.
8. H. Fan and W. K. Jenkins, “A new adaptive IIR filter,” IEEE Trans. Circuits Syst., vol. CAS-33. no. 10, pp. 939-947, Oct. 1986.
9. H. Fan, “A unified analysis of direct form adaptive IIR filters using an ODE method,” in Proc. 21st Asilomar Conf. Circuits, Syst., Comput., 1987. pp. 139-143.
10. Application of Benveniste's convergence results in a study of adaptive IIR filtering algorithms,” IEEE Trans. Inform. Theory, vol. 34, no. 4, pp. 692-709, July 1988.
11. H. Fan and M. Nayeri, “On error surfaces of sufficient order adaptive IIR filters: Proofs and counterexamples to a unimodality conjecture,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, no. 9, pp. 1436-1442, Sept. 1989.
12. H. Fan and Y. Yang, “Analysis of a frequency-domain adaptive IIR filter,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 38, no. 4, pp. 864-870, May 1990.
13. H. Fan and M. Nayeri. “On reduced order identification; revisiting “On some system identification techniques for adaptive filtering”,” IEEE Trans. Circuits Syst. vol. 37, no. 9. pp. 1144-1151, Sept. 1990.
14. P. L. Feintuch, “An adaptive recursive LMS filter,” Proc. IEEE, vol. 64. no. 11, pp. 1622-1624. Nov. 1976.
15. E. R. Ferrara. “Fast implementation of LMS adaptive filters,” IEEE Trans. Acoust. Speech, Signal Processing, vol. ASSP-28, no. 4, pp. 474-475, Aug. 1980.
16. B. Friedlander, “System identification techniques for adaptive signal processing,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-30, no. 2, pp. 240-246. Apr. 1982.
17. S. Gee and M. Rupp, “A comparison of adaptive IIR echo canceller hybrids,” Proc. Int. Conf. Acoust., Speech, Signal Processing, 1991, pp. 1541-1544.
18. J A. B. Gerald, N. L. Esteves, and M. M. Silva, “An adaptive IIR echo canceller combining output-error and equation-error criteria,” in Proc. Int. Symp. Circuits Syst., 1990, pp. 779-783.
19. G. C. Goodwin and K. S. Sin, Adaptive Filtering Prediction and Control. Englewood Cliffs, NJ: Prentice-Hall, 1984.
20. M. C. Hall and P. M. Hughes. “The master-slave IIR filter adaptation algorithm,” in Proc. Int. Symp. Circuits Syst., 1988, pp. 2145-2148.
21. S. S. Haykin, Adaptive Filter Theory. Englewood Cliffs, NJ: Prentice-Hall, 1991.
22. S. Horvath, Jr., “A new adaptive recursive LMS filter,” Digital Signal Processing, V. Cappellini and A. G. Constantinides, Eds. San Diego, CA: Academic Press, 1980. pp. 21-26.
23. T. C. Hsia, “A simplified adaptive recursive filter design,” Proc. IEEE, vol. 69, no. 9, pp. 1153-1155. Sept. 1981.
24. A. W. Hull and W. K. Jenkins, “A comparison of two IIR filter structures for adaptive digital filtering,” in Proc. Int. Symp. Circuits Syst., 1988, pp. 527-530.
25. D. A. Johns, W. M. Snelgrove. and A. S. Sedra, “Nonideal effects in continuous-time adaptive recursive filters,” in Proc. 32nd. Midwest Symp. Circuits Syst., 1990, pp. 594-587.
26. C. R. Johnson Jr., and M. G. Larimore, “Comments on and additions to ‘An adaptive recursive LMS filter’,” Proc. IEEE, vol. 65, no. 9, pp. 1399-1402, Sept. 1977.
27. C. R. Johnson Jr., “A convergence proof for a hyperstable adaptive recursive filter,” IEEE Trans. Inform. Theory, vol. IT-25, no. 6, pp. 745-749, Nov. 1979.
28. “An output error identification interpretation of model reference adaptive control,” Automalica, vol. 16, pp. 419-421, July 1980.
29. C. R. Johnson Jr., and T. Taylor. “Failure of a parallel adaptive identifier with adaptive error filtering,” IEEE Trans. Automat. Cont., vol. AC-25, no. 6, pp. 1248-1250. Dec. 1980.
30. C. R. Johnson Jr., M. G. Larimore, J. R. Treichler, and B. D. O. Anderson, “SHARP convergence properties,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-29, no. 3, pp. 659-670, June 1981.
31. C. R. Johnson, Jr., and B. D. O. Anderson, “Sufficient excitation and stable reduced-order adaptive IIR filtering,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-29. no. 6, pp. 1212-1215, Dec. 1981.
32. C. R. Johnson Jr., “'The common parameter estimation basis of adaptive filtering, identification, and control,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-30, no. 4. pp. 587-595, Aug. 1982.
33. “Adaptive IIR filtering: Current results and open issues,” IEEE Trans. Inform. Theory, vol. IT-30. no. 2, pp. 237-250, Mar. 1984.
34. J. B. Kenney and C. E. Rohrs. “The composite regressor algorithm for IIR adaptive systems,” Trans. Signal Processing, vol. 41, no. 2, pp. 617-628, Feb. 1993.
35. K. Kurosawa and S. Tsujii, “An IIR parallel-type adaptive algorithm using the fast least squares method,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, no. 8. pp. 1226-1230, Aug. 1989.
36. I. D. Landau, “Unbiased recursive identification using model reference adaptive techniques,” IEEE Trans. Automat. Cont., vol. AC-21, no. 2, pp. 194-202, Apr. 1976.
37. I. D. Landau, “An addendum to ‘Unbiased recursive identification using model reference adaptive techniques’,” IEEE Trans. Automat. Cont., vol. AC-23, no. 1, pp. 97-99, Feb. 1978.
38. I. D. Landau, “Elimination of the real positivity condition in the design of parallel MRAS,” IEEE Trans. Automat. Cont., vol. AC-23, no. 6, pp. 1015-1020, Dec. 1978.
39. M. G. Larimore, J. R. Treichler, and C. R. Johnson Jr., “SHARF: an algorithm for adapting IIR digital filters,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-28. no. 4, pp. 428-440, Aug. 1980.
40. J.-N. Lin and R. Unbehauen, “Bias-remedy least mean square equation error algorithm for IIR parameter recursive estimation,” IEEE Trans. Signal Processing, vol. 40, no. 1, pp. 62-69. Jan. 1992.
41. L. Ljung, System Identification: Theory for the User. Englewood Cliffs, NJ: Prentice-Hall, 1987.
42. D. G. Luenberger, Introduction to Linear and Nonlinear Programming. Reading, MA: Addison-Wesley. 1973.
43. D. F. Marshall, W. K. Jenkins, and J. J. Murphy, “The use of orthogonal transforms for improving performance of adaptive filters,” IEEE Trans. Circuits Syst., vol. 36, no. 4, pp. 474-484, Apr. 1989.
44. U. Menzi and G. S. Moschytz, “Adaptive switched capacitor filters based on the LMS algorithm,” Proc. Int. Symp. Circuits Syst. 1990, pp. 2220-2223.
45. S. S. Narayan and A. M. Peterson, “Frequency domain least-mean-square algorithm,” Proc. IEEE, vol. 69, no. 1, pp. 124-126, Jan. 1981.
46. S. S. Narayan, A. M. Peterson, and N. J. Narasimha, “Transform domain LMS algorithm,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-31, no. 3, pp. 609-615, June 1983.
47. M. Nayeri and W. K. Jenkins, “Alternate realizations to adaptive IIR filters and properties of their performance surfaces,” IEEE Trans. Circuits Syst. vol. 36. no. 4, pp. 485-496, Apr. 1989.
48. M. Nayeri, “Uniqueness of MSOE estimates in IIR adaptive filtering; a search for necessary conditions,” in Proc. Int. Conf. Acoust., Speech, Signal Processing, 1989, pp. 1047-1050. 1989.
49. M. Nayeri, H. Fan, and W. K. Jenkins. “Some characteristics of error surfaces for insufficient order adaptive IIR filters,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 38, no. 7. pp. 1222-1227, July 1990.
50. S. L. Netto and P. S. R. Diniz, “Composite algorithms for adaptive IIR filtering,” IEE Electron. Lett., vol. 28, no. 9, pp. 886-888, Apr. 1992.
51. D. Parikh and N. Ahmed, “On an adaptive algorithm for IIR filters,” Proc. IEEE, vol. 66. no. 5, pp. 585-588, May 1978.
52. P. A. Regalia, “Stable and efficient lattice algorithms for adaptive IIR filtering,” IEEE Trans. Signal Processing, vol. 40, no. 2, pp. 375-388, Feb. 1992.
53. J. J. Shynk and R. P. Gooch, “Frequency-domain adaptive pole-zero filtering,” Proc. IEEE, vol. 73, no. 10, pp. 1526-1528, Oct. 1985.
54. J. J. Shynk, “Adaptive IIR filtering using parallel-form realizations,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, no. 4, pp. 519-533, Apr. 1989.
55. J. J. Shynk, “Adaptive IIR filtering,” IEEE Acoust., Speech, Signal Processing Mag., vol. 6, no. 2, pp. 4-21, Apr. 1989.
56. T. Soderstrom, “On the uniqueness of maximum likelihood identification,” Automatica, vol. 11, no. 2, pp. 193-197, Mar. 1975.
57. T. Soderstrom, L. Ljung, and I. Gustavsson, “A theoretical analysis of recursive identification methods,” Automatica, vol. 14, no. 3, pp. 231-244, May 1978.
58. T. Soderstrom and P. Stoica, “On the stability of dynamic models obtained by least-squares identification,” IEEE Trans. Automat. Com., vol. AC-26, no. 2, pp. 575-577, Apr. 1981.
59. “Some properties of the output error method,” Automatica, vol. 18, no. 1, pp. 93-99, Jan. 1982.
60. “On some system identification techniques for adaptive filtering,” IEEE Trans. Circuits Syst., vol. 35, no. 4, pp. 457-461, Apr. 1988.
61. S. D. Stearns, G. R. Elliott, and N. Ahmed, “On adaptive recursive filtering,” in Proc. 10th Asilomar Conf. Circuits, Syst., Comput., 1976, pp. 5-11.
62. S. D. Stearns, “Error surfaces of recursive adaptive filters,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-29, no. 3, pp. 763-766, June 1981.
63. K. Steiglitz and L. E. McBride, “A technique for the identification of linear systems,” IEEE Trans. Automat. Cont., vol. AC-10, no. 4, pp. 461-464, Oct. 1965.
64. P. Stoica and T. Soderstrom, “The Steiglitz-McBride identification algorithm revisited-Convergence analysis and accuracy aspects,” IEEE Trans. Automat. Cont., vol. AC-26, no. 3, pp. 712-717, June 1981.
65. V. L. Stonick and S. T. Alexander, “Numerical methods for globally optimal adaptive IIR filtering,” in Proc. 22th Asilomar Conf. Circuits, Syst., Comput., 1990, pp. 745-749.
66. J. R. Treichler, C. R. Jonhson Jr., and M. G. Larimore, Theory and Design of Adaptive Filters. New York: Wiley, 1987.
67. C.-P. J. Tzeng, “An adaptive offset cancellation technique for adaptive filters,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 38, no. 5, pp. 799-803, May 1990.
68. B. E. Usevitch and W. K. Jenkins, “A cascade implementation of a new IIR adaptive digital filter with global convergence and improved convergence rates,” in Proc. Int. Symp. Circuits Syst., 1989, pp. 2140-2143.
69. S. A. White, “An adaptive recursive digital filter,” in Proc. 9th Asilomar Conf. Circuits, Syst., Comput., 1975, pp. 21-25, 1975.
70. B. Widrow and J. M. McCool, “Comments on ‘An adaptive recursive LMS filter’,” Proc. IEEE, vol. 65, no. 9, pp. 1402-1404, Sept. 1977.
71. B. Widrow and S. Steams, Adaptive Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1985.