000			04231nam a2200961 i 4500
001			6198917
003			IEEE
005			20200421114417.0
006			m o d
007			cr |n|||||||||
008			151221s2012 nju ob 001 eng d
020			_a9781118161968 _qebook
020			_z9780470948477 _qprint
020			_z1118161963 _qelectronic
024	7		_a10.1002/9781118161968 _2doi
035			_a(CaBNVSL)mat06198917
035			_a(IDAMS)0b000064818125ed
040			_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL
050		4	_aQ386 _b.M54 2012eb
082	0	4	_a003/.54 _223
100	1		_aMiddleton, David, _d1920-
245	1	0	_aNon-Gaussian statistical communication theory / _cDavid Middleton.
250			_a1st ed.
264		1	_aHoboken, New Jersey : _bWiley-IEEE Press, _c2012.
264		2	_a[Piscataqay, New Jersey] : _bIEEE Xplore, _c[2012]
300			_a1 PDF.
336			_atext _2rdacontent
337			_aelectronic _2isbdmedia
338			_aonline resource _2rdacarrier
490	1		_aIEEE series on digital & mobile communication ; _v22
505	8		_aReception as a Statistical Decision Problem -- Space-Time Covariances and Wave Number Frequency Spectra: I. Noise and Signals with Continuous and Discrete Sampling -- Optimum Detection, Spaceb6sTime Matched Filters, and Beam Forming in Gaussian Noise Fields -- Multiple Alternative Detection -- Bayes Extraction Systems: Signal Estimation and Analysis, () = 1 -- Joint Detection and Estimation, () = 1: I. Foundations -- Joint Detection and Estimation under Uncertainty, () < 1. II. Multiple Hypotheses and Sequential Observations -- The Canonical Channel I: Scalar Field Propagation in a Deterministic Medium -- The Canonical Channel II: Scattering in Random Media; 'Classical' Operator Solutions -- Appendix A1 -- Index -- IEEE Press Series on Digital and Mobile Communication.
506	1		_aRestricted to subscribers or individual electronic text purchasers.
520	8		_a"The book is based on the observation that communication is the central operation of discovery in all the sciences. In its "active mode" we use it to "interrogate" the physical world, sending appropriate "signals" and receiving nature's "reply". In the "passive mode" we receive nature's signals directly. Since we never know a priori what particular return signal will be forthcoming, we must necessarily adopt a probabilistic model of communication"-- _cR�esum�e de l'�editeur
530			_aAlso available in print.
538			_aMode of access: World Wide Web
588			_aDescription based on PDF viewed 12/21/2015.
650		0	_aStatistical communication theory.
650		0	_aInformation theory _xStatistical methods.
650		0	_aGaussian processes.
655		0	_aElectronic books.
695			_aApertures
695			_aArrays
695			_aBayes methods
695			_aComputer aided software engineering
695			_aCost function
695			_aCouplings
695			_aCovariance matrix
695			_aData mining
695			_aData processing
695			_aDecision theory
695			_aEigenvalues and eigenfunctions
695			_aEquations
695			_aEstimation
695			_aFading channels
695			_aFeature extraction
695			_aIndexes
695			_aJoints
695			_aManganese
695			_aMatched filters
695			_aMinimization
695			_aNarrowband
695			_aNoise
695			_aNoise measurement
695			_aNonhomogeneous media
695			_aProbability density function
695			_aRandom media
695			_aReceivers
695			_aScattering
695			_aSections
695			_aSensors
695			_aSignal detection
695			_aSilicon compounds
695			_aStatistical analysis
695			_aSymmetric matrices
695			_aUnsupervised learning
695			_aVectors
710	2		_aIEEE Xplore (Online Service), _edistributor.
710	2		_aJohn Wiley & Sons, _epublisher.
776	0	8	_iPrint version: _z9780470948477
830		0	_aIEEE series on digital & mobile communication ; _v22
856	4	2	_3Abstract with links to resource _uhttp://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=6198917
942			_cEBK
999			_c59827 _d59827