國立虎尾科技大學 |

A First Course in Statistics for Signal Analysis

Record Type:	Language materials, printed : Monograph/item
Title/Author:	A First Course in Statistics for Signal Analysis/ by Wojbor A. Woyczyński.
Author:	Woyczyński, Wojbor A.
Description:	XVIII, 332 p. 95 illus., 69 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Statistics . -
Online resource:	https://doi.org/10.1007/978-3-030-20908-7
ISBN:	9783030209087

A First Course in Statistics for Signal Analysis
Woyczyński, Wojbor A.

A First Course in Statistics for Signal Analysis[electronic resource] /by Wojbor A. Woyczyński. - 3rd ed. 2019. - XVIII, 332 p. 95 illus., 69 illus. in color.online resource. - Statistics for Industry, Technology, and Engineering,2662-5555. - Statistics for Industry, Technology, and Engineering,.

Description of Signals -- Spectral Representation of Deterministic Signals: Fourier Series and Transforms -- Uncertainty Principle and Wavelet Transforms -- Random Variables and Random Vectors -- Stationary Signals -- Power Spectra of Random Signals -- Transmission of Stationary Signals through Linear Systems -- Optimization of Signal-to-Noise Ratio in Linear Systems -- Gaussian Signals, Covariance Matrices, and Sample Path Properties -- Spectral Representation of Discrete-Time Signals and Their Computer Simulations -- Prediction Theory for Stationary Random Signals -- Solutions to Selected Problems and Exercises.

This essentially self-contained, deliberately compact, and user-friendly textbook is designed for a first, one-semester course in statistical signal analysis for a broad audience of students in engineering and the physical sciences. The emphasis throughout is on fundamental concepts and relationships in the statistical theory of stationary random signals, explained in a concise, yet fairly rigorous presentation. Topics and Features: · Fourier series and transforms—fundamentally important in random signal analysis and processing—are developed from scratch, emphasizing the time-domain vs. frequency-domain duality; · Basic concepts of probability theory, laws of large numbers, the central limit theorem, and statistical parametric inference procedures are presented so that no prior knowledge of probability and statistics is required; the only prerequisite is a basic two–three semester calculus sequence; · Computer simulation algorithms of stationary random signals with a given power spectrum density; · Complementary bibliography for readers who wish to pursue the study of random signals in greater depth; · Many diverse examples and end-of-chapter problems and exercises. Developed by the author over the course of many years of classroom use, A First Course in Statistics for Signal Analysis, Second Edition may be used by junior/senior undergraduates or graduate students in electrical, systems, computer, and biomedical engineering, as well as the physical sciences. The work is also an excellent resource of educational and training material for scientists and engineers working in research laboratories. This third edition contains two additional chapters that present wavelets and the uncertainty principle, and the forecasting problems for stationary time series. These two topics are essential for students to attain a deeper understanding of statistical analysis of random signals. Reviews from previous editions: A First Course in Statistics for Signal Analysis is a small, dense, and inexpensive book that covers exactly what the title says: statistics for signal analysis. The book has much to recommend it. The author clearly understands the topics presented. The topics are covered in a rigorous manner, but not so rigorous as to be ostentatious. JASA (Review of the First Edition) This is a nicely written self-contained book and it is a good candidate for adoption as a textbook for upper-level undergraduate and even for a graduate course for engineering and physical sciences students. … I have no hesitation in recommending it as a textbook for the targeted course and audience. Technometrics, Vol. 53 (4), November, 2011 (Review of the Second Edition).

ISBN: 9783030209087

Standard No.: 10.1007/978-3-030-20908-7doiSubjects--Topical Terms:

1253516
Statistics .

LC Class. No.: QA276-280

Dewey Class. No.: 519.5

A First Course in Statistics for Signal Analysis
LDR:04768nam a22004095i 4500 001 1013323
003 DE-He213
005 20200702005918.0
007 cr nn 008mamaa
008 210106s2019 gw | s |||| 0|eng d
020 $a 9783030209087 $9 978-3-030-20908-7
024 7 $a 10.1007/978-3-030-20908-7 $2 doi
035 $a 978-3-030-20908-7
050 4 $a QA276-280
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.5 $2 23
100 1 $a Woyczyński, Wojbor A. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1307620
245 1 2 $a A First Course in Statistics for Signal Analysis $h [electronic resource] / $c by Wojbor A. Woyczyński.
250 $a 3rd ed. 2019.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Birkhäuser, $c 2019.
300 $a XVIII, 332 p. 95 illus., 69 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Statistics for Industry, Technology, and Engineering, $x 2662-5555
505 0 $a Description of Signals -- Spectral Representation of Deterministic Signals: Fourier Series and Transforms -- Uncertainty Principle and Wavelet Transforms -- Random Variables and Random Vectors -- Stationary Signals -- Power Spectra of Random Signals -- Transmission of Stationary Signals through Linear Systems -- Optimization of Signal-to-Noise Ratio in Linear Systems -- Gaussian Signals, Covariance Matrices, and Sample Path Properties -- Spectral Representation of Discrete-Time Signals and Their Computer Simulations -- Prediction Theory for Stationary Random Signals -- Solutions to Selected Problems and Exercises.
520 $a This essentially self-contained, deliberately compact, and user-friendly textbook is designed for a first, one-semester course in statistical signal analysis for a broad audience of students in engineering and the physical sciences. The emphasis throughout is on fundamental concepts and relationships in the statistical theory of stationary random signals, explained in a concise, yet fairly rigorous presentation. Topics and Features: · Fourier series and transforms—fundamentally important in random signal analysis and processing—are developed from scratch, emphasizing the time-domain vs. frequency-domain duality; · Basic concepts of probability theory, laws of large numbers, the central limit theorem, and statistical parametric inference procedures are presented so that no prior knowledge of probability and statistics is required; the only prerequisite is a basic two–three semester calculus sequence; · Computer simulation algorithms of stationary random signals with a given power spectrum density; · Complementary bibliography for readers who wish to pursue the study of random signals in greater depth; · Many diverse examples and end-of-chapter problems and exercises. Developed by the author over the course of many years of classroom use, A First Course in Statistics for Signal Analysis, Second Edition may be used by junior/senior undergraduates or graduate students in electrical, systems, computer, and biomedical engineering, as well as the physical sciences. The work is also an excellent resource of educational and training material for scientists and engineers working in research laboratories. This third edition contains two additional chapters that present wavelets and the uncertainty principle, and the forecasting problems for stationary time series. These two topics are essential for students to attain a deeper understanding of statistical analysis of random signals. Reviews from previous editions: A First Course in Statistics for Signal Analysis is a small, dense, and inexpensive book that covers exactly what the title says: statistics for signal analysis. The book has much to recommend it. The author clearly understands the topics presented. The topics are covered in a rigorous manner, but not so rigorous as to be ostentatious. JASA (Review of the First Edition) This is a nicely written self-contained book and it is a good candidate for adoption as a textbook for upper-level undergraduate and even for a graduate course for engineering and physical sciences students. … I have no hesitation in recommending it as a textbook for the targeted course and audience. Technometrics, Vol. 53 (4), November, 2011 (Review of the Second Edition).
650 0 $a Statistics . $3 1253516
650 0 $a Fourier analysis. $3 639284
650 0 $a Signal processing. $3 561459
650 0 $a Image processing. $3 557495
650 0 $a Speech processing systems. $3 564428
650 1 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 782247
650 2 4 $a Fourier Analysis. $3 672627
650 2 4 $a Signal, Image and Speech Processing. $3 670837
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030209070
776 0 8 $i Printed edition: $z 9783030209094
776 0 8 $i Printed edition: $z 9783030209100
830 0 $a Statistics for Industry, Technology, and Engineering, $x 2662-5555 $3 1307621
856 4 0 $u https://doi.org/10.1007/978-3-030-20908-7
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)