| 000 | 01679nam a2200349 4500 | ||
|---|---|---|---|
| 001 | 10251 | ||
| 003 | GR-kaGGEEl | ||
| 005 | 20220622205651.0 | ||
| 010 |
_a0-13-504135-X _bV.II |
||
| 035 | _a13135 | ||
| 090 | _a10251 | ||
| 100 | _a20040415d1998 k y0engy50 ba | ||
| 101 | 0 | _aeng | |
| 102 | _aUS | ||
| 105 | _ay z 001yy | ||
| 106 | _ar | ||
| 200 | 1 |
_aFundamentals of statistical signal processing _fSteven M. Kay _hII _idetection theory |
|
| 210 |
_aUpper Saddle River, New Jersey _cPrentice - Hall _dc 1998 |
||
| 215 | _a2 v. | ||
| 225 | 0 | _aPrentice Hall signal processing series / Alan V. Oppenheim, series editor | |
| 320 | _av.1: Estimation theory. - Includes bibliographical references and index | ||
| 327 | 1 | _aEstimation in signal processing. The mathematical estimation problem. Assessing estimator performance. Some notes to the reader. Minimum variance unbiased estimation. Cramer - Rao lower bound. Linear models. General minimum variance unbiased estimation. Best linear unbiased estimators. Maximum likelihood estimation. Least squares. Method of moments. The Bayesian philosophy. General Bayesian estimators. Linear Bayesian estimators. Kalman filters. Summary of estimators. Extensions for complex data and parameters. | |
| 606 | 1 |
_aEstimation theory _92248 |
|
| 606 | 1 |
_aSignal processing _xStatistical methods _96518 |
|
| 606 | 1 |
_aDetection theory _91787 |
|
| 606 | 1 |
_aΕπεξεργασία σημάτων _913310 |
|
| 606 | 1 |
_aΕπεξεργασία σημάτων _xΣτατιστικές μέθοδοι _913311 |
|
| 676 | _a626.822 | ||
| 701 | 1 |
_4070 _aKay _bSteven M. |
|
| 712 | _aPrentice - Hall | ||
| 942 | _cBK | ||