Spectral Analysis of Signals (Record no. 85849)

000 -LEADER
fixed length control field 03338nam a22005295i 4500
001 - CONTROL NUMBER
control field 978-3-031-02525-9
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730164713.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220601s2005 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031025259
-- 978-3-031-02525-9
082 04 - CLASSIFICATION NUMBER
Call Number 620
100 1# - AUTHOR NAME
Author Wang, Yanwei.
245 10 - TITLE STATEMENT
Title Spectral Analysis of Signals
Sub Title The Missing Data Case /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2005.
300 ## - PHYSICAL DESCRIPTION
Number of Pages VIII, 99 p.
490 1# - SERIES STATEMENT
Series statement Synthesis Lectures on Signal Processing,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Linear Source Separation -- Nonlinear Separation -- Final Comments -- Statistical Concepts -- Online Software and Data.
520 ## - SUMMARY, ETC.
Summary, etc Spectral estimation is important in many fields including astronomy, meteorology, seismology, communications, economics, speech analysis, medical imaging, radar, sonar, and underwater acoustics. Most existing spectral estimation algorithms are devised for uniformly sampled complete-data sequences. However, the spectral estimation for data sequences with missing samples is also important in many applications ranging from astronomical time series analysis to synthetic aperture radar imaging with angular diversity. For spectral estimation in the missing-data case, the challenge is how to extend the existing spectral estimation techniques to deal with these missing-data samples. Recently, nonparametric adaptive filtering based techniques have been developed successfully for various missing-data problems. Collectively, these algorithms provide a comprehensive toolset for the missing-data problem based exclusively on the nonparametric adaptive filter-bank approaches, which are robust and accurate, and can provide high resolution and low sidelobes. In this book, we present these algorithms for both one-dimensional and two-dimensional spectral estimation problems.
700 1# - AUTHOR 2
Author 2 Li, Jian.
700 1# - AUTHOR 2
Author 2 Stoica, Petre.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-02525-9
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2005.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electrical engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal processing.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Technology and Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electrical and Electronic Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal, Speech and Image Processing.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1932-1694
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-- ZDB-2-SXSC

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