Digital spectral analysis : with appplications / S. Lawrence Marple, Jr.

By: Marple, S. LawrenceSeries: Prentice-Hall signal processing seriesPublisher: Englewood Cliffs, N.J. : Prentice-Hall, cop. 1987Description: xx, 492 p. : ill. + 1 diskettISBN: 0-13-214149-3Subject(s): Signal processing -- Digital techniques | Signalteori: teleteknik | Signalteori: teleteknik | Spectral theory (Mathematics) | TidsserierDDC classification: 519.55, MAR
Contents:
1.introduction(Page-1), 2.Review of linear systems and transform theory (Page-25), 3.Review of matrix algebra (Page -57) 4.Review of random process theory (Page-111), 5.classical spectral estimation (Page -130), 6.Parametric models of random processes (Page -172), 7.autoregressive spectral estimation: block data algorithms (Page -206), 8.autoregressive spectral estimation (Page- 261),10.autoregressive -moving average spectral (Page -285), 11.Prony,s method(Page -303), 12.minimum variance spectral estimation (Page -350), 13.eigenanalysis based frequency estimation (Page- 361), 14.summary of spectral estimation (Page -386), 16.Two-dimensional spectral estimation (Page -432).
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Item type Current location Home library Shelving location Call number URL Status Notes Date due Barcode Item holds
Book Book Military College of Signals (MCS)
Military College of Signals (MCS)
General Stacks 519.55,MAR (Browse shelf) Link to resource Available Almirah No.14, Shelf No.6 MCS27069
Total holds: 0

1.introduction(Page-1), 2.Review of linear systems and transform theory (Page-25), 3.Review of matrix algebra (Page -57) 4.Review of random process theory (Page-111), 5.classical spectral estimation (Page -130), 6.Parametric models of random processes (Page -172), 7.autoregressive spectral estimation: block data algorithms (Page -206), 8.autoregressive spectral estimation (Page- 261),10.autoregressive -moving average spectral (Page -285), 11.Prony,s method(Page -303), 12.minimum variance spectral estimation (Page -350), 13.eigenanalysis based frequency estimation (Page- 361), 14.summary of spectral estimation (Page -386), 16.Two-dimensional spectral estimation (Page -432).

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