[1] BERNARD W. Adaptive Signal Processing［M］. New Jersey: Pearson Education Inc, 2008.
[2] LEE L,MATHEWS V J.A fast recursive least squares adaptive second-order Volterra filter and its performance analysis［J］. IEEE Trans. On Signal Processing, 1993,41:1087-1101.
[3] LI Y,KASHIWAGI H. High-order volterra model predictive control and its application to a nonlinear polymerization process［J］. International Journal of Automation and Computing , 2005(2):208-214.
[4] XIE SH Y,ZHANG CH J. Variable learning rate LMS based linear adaptive inverse control［J］. Journal of Information and Computing Science, 2006,1(3):139-148.
[5] IFEACHOR E C,JERVIS B W.Digital Signal Processing:A Practical Approach［M］.New Jersey:Pearson Education Inc., 2002.
[6] MARTHEWS V J.Adaptive Volterra filters using orthogonal structures［J］.IEEE Signal Processing Letters,1996,3(12):307-309.
[7] SYED M A,MATHEWS V J. Lattice algorithms for recursive least squares adaptive second-order Volterra filtering［J］. IEEE Trans. on Circuits and systems II: Analog and Digital Signal Processing,1994,41(3):202-214.
[8] SCHETZEN M. The Volterra and Wiener Theories of Non-linear Systems［M］. New York:Wiley and Sons,1980.
[9] RAMPONI G,SICURANZA G L. Quadratic digital filters for image processing［J］. IEEE Transactions on Acoustics, Speech and Signal Processing, 1988,36:937-939.
[10] PAULO S R. Diniz. Adaptive Filtering: Algorithms and Practical Implementation［M］. UK: Kluwer Academic Publishers, 2004.
[11] SMALLWOOD D A. Adaptive identification of dynamically positioned underwater robotic vehicles［J］. IEEE Trans. on Control Systems Technology, 2003,11(7):505-514.
