D. C. Farden, Tracking properties of adaptive signal processing algorithms,IEEE Trans. Acoust., Speech Signal Process., ASSP-29(3):439–446, 1981.
W. Gardner, Nonstationary learning characteristics of the LMS algorithms: A general study, analysis and critique,IEEE Trans. Circuits and Systems, CAS-34(10):1199–1207, 1987.
L. Guo and L. Ljung, Performance analysis of general tracking algorithms,IEEE Trans. Automat. Control, AC-40:1388–1402, August 1995.
N. Kaloupsides and S. Theodoridis, eds.,Adaptive System Identification and Signal Processing Algorithms, Prentice-Hall International, Hemel Hampstead, 1993.
L. Ljung,System Identification—Theory for the User, 2nd ed., Prentice-Hall, Upper Saddle River, NJ, 1999.
L. Ljung, G. Pflug, and H. Walk,Stochastic Approximation and Optimization of Random Systems, Birkhäuser, Berlin, 1992.
L. Ljung and T. Söderström,Theory and Practice of Recursive Identification, MIT Press, Cambridge, MA, 1983.
O. Macchi,Adaptive Processing: The Least Mean Squares Approach with Applications in Transmission, Wiley, Chichester, 1995.
O. Macchi and E. Eweda, Second-order convergence analysis of stochastic adaptive linear filtering,IEEE Trans. Automat. Control, AC-28(1):76–85, 1983.
V. Solo and X. Kong,Adaptive Signal Processing Algorithms, Prentice-Hall, Englewood Cliffs, NJ, 1995.
B. Widrow, J. M. McCool, M. G. Larimore, and C. R. Johnson Jr. Stationary and nonstationary learning characteristics of the lms adaptive filter,Proc. IEEE, 64(8):1151–1162, 1976.
B. Widrow and S. Stearns,Adaptive Signal Processing. Prentice-Hall, Englewood-Cliffs, NJ, 1985.
P. C. Young,Recursive Estimation and Time-Series Analysis, Springer Verlag, Berlin, 1984.