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Mathematical Summary for Digital Signal Processing Applications with Matlab

Mathematical Summary for Digital Signal Processing Applications with Matlab
Kataloginformation
Feldname Details
Vorliegende Sprache eng
ISBN 978-90-481-3746-6
Name Gopi, E. S.
T I T E L Mathematical Summary for Digital Signal Processing Applications with Matlab
Verlagsort Dordrecht
Verlag Springer Science+Business Media B.V
Erscheinungsjahr 2010
2010
Umfang Online-Ressource (XIV, 250p, digital)
Reihe SpringerLink. Bücher
Notiz / Fußnoten Description based upon print version of record
Weiterer Inhalt Mathematical Summaryfor Digital Signal ProcessingApplications with Matlab; 1 Matrices; 1.1 Properties of Vectors; 1.2 Properties of Matrices; 1.3 LDU Decomposition of the Matrix; 1.4 PLDU Decomposition of an Arbitrary Matrix; 1.5 Vector Space and Its Properties; 1.6 Linear Independence, Span, Basis and the Dimension of the Vector Space; 1.6.1 Linear Independence; 1.6.2 Span; 1.6.3 Basis; 1.6.4 Dimension; 1.7 Four Fundamental Vector Spaces of the Matrix; 1.7.1 Column Space; 1.7.2 Null Space; 1.7.3 Row Space; 1.7.4 Left Null Space; 1.8 Basis of the Four Fundamental Vector Spaces of the Matrix. 1.8.1 Column Space1.9 Observations on Results of the Example 1.12; 1.9.1 Column Space; 1.9.2 Null Space; 1.9.3 Left Column Space (Row Space); 1.9.4 Left Null Space; 1.9.5 Observation; 1.10 Vector Representation with Different Basis; 1.11 Linear Transformation of the Vector; 1.11.1 Trick to Compute the Transformation Matrix; 1.12 Transformation Matrix with Different Basis; 1.13 Orthogonality; 1.13.1 Basic Definitions and Results; 1.13.2 Orthogonal Complement; 1.14 System of Linear Equation; 1.15 Solutions for the System of Linear Equation [A] x=b; 1.15.1 Trick to Obtain the Solution. 1.16 Gram Schmidt Orthonormalization Procedure for Obtaining Orthonormal Basis1.17 QR Factorization; 1.18 Eigen Values and Eigen Vectors; 1.19 Geometric Multiplicity (Versus) Algebraic Multiplicity; 1.20 Diagonalization of the Matrix; 1.21 Schur's Lemma; 1.22 Hermitian Matrices and Skew Hermitian Matrices; 1.23 Unitary Matrices; 1.24 Normal Matrices; 1.25 Applications of Diagonalization of the Non-deficient Matrix; 1.26 Singular Value Decomposition; 1.27 Applications of Singular Value Decomposition; 2 Probability; 2.1 Introduction; 2.2 Axioms of Probability; 2.3 Class of Events or Field (F). 2.4 Probability Space (S, F, P)2.5 Probability Measure; 2.6 Conditional Probability; 2.7 Total Probability Theorem; 2.8 Bayes Theorem; 2.9 Independence; 2.10 Multiple Experiments (Combined Experiments); 2.11 Random Variable; 2.12 Cumulative Distribution Function (cdf) of the Random Variable `x'; 2.13 Continuous Random Variable; 2.14 Discrete Random Variable; 2.15 Probability Mass Function; 2.16 Probability Density Function; 2.17 Two Random Variables; 2.18 Conditional Distributions and Densities; 2.19 Independent Random Variables; 2.20 Some Important Results on Conditional Density Function. 2.21 Transformation of Random Variables of the Type Y=g(X)2.22 Transformation of Random Variables of the Type Y1 = g1(X1,X2), Y2 = g2(X1, X2); 2.23 Expectations; 2.24 Indicator; 2.25 Moment Generating Function; 2.26 Characteristic Function; 2.27 Multiple Random Variable (Random Vectors); 2.28 Gaussian Random Vector with Mean Vector X and Covariance Matrix CX; 2.29 Complex Random Variables; 2.30 Sequence of the Number and Its Convergence; 2.31 Sequence of Functions and Its Convergence; 2.32 Sequence of Random Variable; 2.33 Example for the Sequence of Random Variable. 2.34 Central Limit Theorem
Titelhinweis Buchausg. u.d.T.ISBN: 978-90-481-3746-6
ISBN ISBN 978-90-481-3747-3
Klassifikation TTBM
UYS
TEC008000
COM073000
*00A06
94-01
94A12
15-01
60-01
60G10
90-01
90C90
621.382
621.38220151
TK5102.9
TA1637-1638
TK7882.S65
Kurzbeschreibung Mathematical summary for Digital Signal Processing Applications with Matlab consists of Mathematics which is not usually dealt in the DSP core subject, but used in DSP applications. Matlab programs with illustrations are given for the selective topics such as generation of Multivariate Gaussian distributed sample outcomes, Bacterial foraging algorithm, Newton's iteration, Steepest descent algorithm, etc. are given exclusively in the separate chapter. Also Mathematical summary for Digital Signal Processing Applications with Matlab is written in such a way that it is suitable for Non-Mathematica
SWB-Titel-Idn 322308976
Signatur Springer E-Book
Bemerkungen Elektronischer Volltext - Campuslizenz
Elektronische Adresse $uhttp://dx.doi.org/10.1007/978-90-481-3747-3
Internetseite / Link Volltext
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