| 000 | 01524pam a2200253 a 4500 | ||
|---|---|---|---|
| 999 |
_c3273 _d3273 |
||
| 001 | 3978129 | ||
| 003 | OSt | ||
| 005 | 20200122061833.0 | ||
| 008 | 950427s1996 -usa g b 001 0 eng | ||
| 010 | _a 95011120 | ||
| 020 | _a013322760X(pbk) | ||
| 040 | _cNCL | ||
| 082 | 0 | 0 |
_a621.3815 _bHAY-A 1996 4558 |
| 100 | 1 |
_aHaykin, Simon S., _d1931- |
|
| 245 | 1 |
_aAdaptive filter theory / _cby Simon Haykin. |
|
| 250 | _a3rd ed. | ||
| 260 |
_aUpper Saddle River, N.J. : _bPrentice Hall, _cc1996. |
||
| 300 |
_avii, 989 p. : _bill. ; _c24 cm. |
||
| 440 | 0 | _aPrentice Hall information and system sciences series | |
| 504 | _aIncludes bibliographical references (p. 941-977) and index. | ||
| 505 | _aCONTENTS Chapter 1: Discrete time signal processing Chapter 2: Stationary processes and models Chapter 3: spectrum analysis Chapter 4: Eigen-analysis Chapter 5: Wiener Fillers Chapter 6: Linear prediction Chapter 7: Kalman filters Chapter 8: Method of steepest descent Chapter 9: Least mean square algorithm Chapter 10: Frequency domain adoptive filters Chapter 11: Methods of least squares Chapter 12: Rotations and reflections Chapter 13: Recursive least squares algorithm Chapter 14: Square root adaptive filters Chapter 15: Order recursive adaptive filters Chapter 16: Tracking of time varying systems Chapter 17: Finite Precision effects Chapter 18: Blind deconvolution Chapter 19: Back Propagation learning Chapter 20: Radial bases function networks | ||
| 650 | 0 | _aAdaptive filters. | |
| 942 |
_2ddc _cBK |
||