000			01719cam a22002897a 4500
001			004461
003			armpuni
005			20160923153929.0
008			160923s1996####xx#a##########000#0#und#d
040			_aarmpuni _carmpuni
041			_aen
080			_a621.372
100	1		_aHaykin, Simon
245	1	0	_aAdaptive filter theory / _cSimon Haykin
250			_athird edition
260			_aNew Jersey : _bPrentice Hall, _c1996
300			_axii, 989 p.: _bil.; _c23 cm.
500			_aabbreviations p. 932
500			_aAppendix p.
500			_aBibliography p. 941
500			_aIncluye glosario p. 928
500			_aPrincipal symbols p. 933
550			_aLinear filter structures. Backround material.Discrete-time signal processing. Stationary processes and models. Spectrum analysis. Eigenanalysis. Linear optimum filtering. Wiener filters. Linear prediction. Kalman filters. Linear adaptive filtering. Method of steepes descent. Least-Mean-Square algorithm. Frequency-domain adaptive filters. Method of least squares. Rotations and reflections. Recursive least-squares algorithm. Square-Root Adaptive filters. Order-recursive adaptive filters. Tracking of time-varyng systems. Finite-precision effects. Nonlinear adaptive filtering. Blind deconvolution. Back-propagation learning. Radial basis function networks. Complex variables. Differentiation with respect to a vector. Methods of lagrange multipliers. Estimation theory. Maximum-entropy method. Minimum-variance distortionless response spectrum. Grandient adaptive lattice algorithm. Steady-state analysis of the LMS Algorithm without invoking the independence assumption.
650		7	_aFILTROS _2LEMB
942			_cLB _2cdu
945			_aMDC _d1999-09-14
999			_c4460 _d5635