Digital Signal Processing Reference
In-Depth Information
33. P.S.R. Diniz,
Adaptive Filtering: Algorithms And Practical Implementation
, 3rd edn. (Springer,
Boston, 2008)
34. B. Farhang-Boroujeny,
Adaptive Filters: Theory and Applications
(Wiley, New York, 1998)
35. R.A. Horn, C.R. Johnson,
Matrix Analysis
(Cambridge University Press, New York, 1990)
36. R. Price, A useful theorem for nonlinear devices having Gaussian inputs. IRE Trans. Inform.
Theory.
IT-4
, 69-72 (1958)
37. L. Rey Vega, H. Rey, J. Benesty, Stability analysis of a large family of adaptive filters. Elsevier
Sig. Process.
91
, 2091-2100 (2011)
38. T. Hu, A. Rosalsky, A. Volodin, On convergence properties of sums of dependent random
variables under second moment and covariance restrictions. Stat. and Prob. Lett.
78
, 1999-20
(2008)
39. A. Papoulis,
Probability, Random Variables, and Stochastic Processes
(McGraw-Hill, New
York, 1965)
40. T. Al-Naffouri, A. Sayed, Transient analysis of data normalized adaptive filters. IEEE Trans.
Signal Process.
51
, 639-652 (2003)
41. M. Tarrab, A. Feuer, Convergence and performance analysis of the normalized LMS algorithm
with uncorrelated gaussian data. IEEE Trans. Inform. Theory
34
, 680-691 (1988)
42. D.T. Slock, On the convergence behaviour of the LMS and the normalized LMS algorithms.
IEEE Trans. Sig. Process.
41
, 2811-2825 (1993)
43. M. Rupp, The behaviour of LMS and NLMS algorithms in the presence of spherically invariant
processes. IEEE Trans. Sig. Process.
41
, 1149-1160 (1993)
44. W. Sethares, I. Mareels, B. Anderson, C. Johnson, R. Bitmead, Excitation conditions for signed
regressor least mean squares adaptation. IEEE Trans. Circuits Syst.
35
, 613-624 (1988)
45. A.H. Sayed,
Adaptive Filters
(Wiley, Hoboken, 2008)
46. L. Rrtveit, J.H. Husy, A new prewhitening-based adaptive filter which converges to theWiener-
solution.
Proc. Asilomar Conf. Sig. Syst. Comp.
1360-1364 (2009)
47. C. Breining, P. Dreiscitel, E. Hansler, A. Mader, B. Nitsch, H. Puder, T. Schertler, G. Schmidt,
J. Tilp, Acoustic echo control. An application of very-high-order adaptive filters. IEEE Signal
Process. Mag.
16
, 42-69 (1999)
48. N. Yousef, A. Sayed, A unified approach to the steady-state and tracking analyses of adaptive
filters. IEEE Trans. Signal Process.
49
, 314-324 (2001)
49. K. Ozeki, T. Umeda, An adaptive filtering algorithm using an orthogonal projection to an affine
subspace and its properties. Electron. Commun. Japan
67-A
, 19-27 (1984)
50. J. Apolinário Jr, M.L.R. Campos, P.S.R. Diniz, Convergence analysis of the binormalized
data-reusing LMS algorithm. IEEE Trans. Signal Process.
48
, 3235-3242 (2000)
51. S.G. Sankaran, A.A.L. Beex, Convergence behavior of affine projection algorithms. IEEE
Trans. Signal Process.
48
, 1086-1096 (2000)
52. S. Gay, S. Tavathia, The fast affine projection algorithm.
Proc. IEEE ICASSP
, 3023-3026
(1995)
53. H. Ding, Fast affine projection adaptation algorithms with stable and robust symmetric linear
system solvers. IEEE Trans. Sig. Process.
55
, 1730-1740 (2007)
54. M. Tanaka, S. Makino, J. Kojima, A block exact fast affine projection algorithm. IEEE Trans.
Speech Audio Process.
7
, 79-86 (1999)
55. M. Rupp, A.H. Sayed, A time-domain feedback analysis of filtered-error adaptive gradient
algorithms. IEEE Trans. Sig. Process.
44
, 1428-1439 (1996)
56. H. Rey, L. ReyVega, S. Tressens, J. Benesty, Variable explicit regularization in affine projection
algorithm: robustness issues and optimal choice. IEEE Trans. Sig. Process.
55
, 2096-2109
(2007)
57. G. Meng, T. Elmedyb, S. Jensen, J. Jensen, Analysis of acoustic feedback/echo cancellation in
multiple-microphone and single-loudspeaker systems using a power transfer function method.
IEEE Trans. Sig. Process.
59
, 5774-5788 (2011)
58. M. Honig, M.K. Tsatsanis, Adaptive techniques for multiuser CDMA receivers. IEEE Sig.
Process. Mag.
17
, 49-61 (2000)