References

• 1. 1)
     • Tsimbinos, J., Lever, K.: `Sampling frequency requirements for identificationand compensation of nonlinear systems', Proceedings of IEEE international conference on Acoustics,speech andsignal processing, 1994, Adelaide, Australia, p. III 513–516.
  2. 2)
     • L.J. Ticks . The estimation of transfer functions of quadratic systems. Technometrics , 563 - 567
  3. 3)
     • W.J. Rugh . (1981) Nonlinear system theory - the Volterra/Wiener approach.
  4. 4)
     • Y.S. Cho , S.B. Kim , E.J. Powers . A digital technique to estimatesecond-order distortion using higher order coherence spectra. IEEE Trans. Signal Process. , 5 , 1029 - 1040
  5. 5)
     • R. Tymerski . Volterra series modelling of power conversion systems. IEEE Trans. Power Electron. , 4 , 712 - 718
  6. 6)
     • M. Schetzen . (1989) The Volterra and Wiener theories of nonlinear systems.
  7. 7)
     • T. Koh , E.J. Powers . Second-order Volterra filtering and its applicationto nonlinear system identification. IEEE Trans. Acoust. Speech Signal Process. , 6 , 1445 - 1455
  8. 8)
     • Y.-C. Tseng , D.A. Linebarger . Linear-quadratic system identificationwith completed frequency domain region of support. IEEE Trans. Signal Process. , 1 , 254 - 261
  9. 9)
     • I.W. Sandberg . Uniform approximation with doubly finite Volterra series. IEEE Trans. Signal Process. , 6 , 1438 - 1442
  10. 10)
      • C.L. Nikias , M.R. Raghuveer . Bispectrum estimation: a digital signal processing framework. Proc. IEEE , 7 , 869 - 891
  11. 11)
      • J.S. Bendat . (1990) Nonlinear system analysis and identification from random data.
  12. 12)
      • N.A. Zervos , R.L. Cupo . Adaptive nondisruptive measurement of harmonicdistortion for voiceband data transmission. IEEE Trans. Commun. , 7 , 2184 - 2200
  13. 13)
      • D.R. Brillinger . Identification of polynomial systems by means of higher orderspectra. J. Sound Vib. , 301 - 313
  14. 14)
      • Im, S., Powers, E.J.: `Extended principal domain for Volterra models', Proceedings of IEEE signal processing ATHOS workshop on Higherorder statistics, 1995, Begur, Girona, Spain, p. 381–385.
  15. 15)
      • J.Y. Hong , Y.C. Kim , E.J. Powers . On modeling the nonlinear relationshipbetween fluctuations with nonlinear transfer functions. Proc. IEEE , 1026 - 1027
  16. 16)
      • S.W. Nam , E.J. Powers . Application of higher order spectral analysis tocubically nonlinear system identification. IEEE Trans. Signal Process. , 7 , 1746 - 1765
  17. 17)
      • K.I. Kim , E.J. Powers . A digital method of modeling quadratically non-linearsystems with a general random input. IEEE Trans. Acoust. Speech Signal Process. , 1758 - 1769
  18. 18)
      • A. Samelis , D. Pavlidis . Mechanisms determining third order intermodulationdistortion in AlGaAs/GaAs heterojunction bipolar transistors. IEEE Trans. Microw. Theory Tech. , 12 , 2374 - 2380
  19. 19)
      • C.-H. Tseng , E.J. Powers . Adaptive estimation of third-order frequencydomain Volterra kernels. Int. J. Adapt. Control Signal Process. , 319 - 342
  20. 20)
      • L.O. Chua , Y. Liao . Measuring Volterra kernels (II). Int. J. Circuit Theory Appl. , 151 - 190
  21. 21)
      • I.W. Sandberg . On Volterra expansions for time-varying nonlinear systems. IEEE Trans. Circuits Syst. , 2 , 61 - 67
  22. 22)
      • A.V. Oppenheim , R.W. Schafer . (1989) Discrete-time signal processing.
  23. 23)
      • I.W. Sandberg . The mathematical foundations of associated expansions formildly nonlinear systems. IEEE Trans. Circuits Syst. , 7 , 441 - 455