Fundamentals of Statistical Signal Processing, Volume III; Steven M. Kay; 2013

Fundamentals of Statistical Signal Processing, Volume III Upplaga 1

av Steven M. Kay
The Complete, Modern Guide to Developing Well-Performing Signal Processing Algorithms  

In Fundamentals of Statistical Signal Processing, Volume III: Practical Algorithm Development, author Steven M. Kay shows how to convert theories of statistical signal processing estimation and detection into software algorithms that can be implemented on digital computers. This final volume of Kays three-volume guide builds on the comprehensive theoretical coverage in the first two volumes. Here, Kay helps readers develop strong intuition and expertise in designing well-performing algorithms that solve real-world problems.

 

Kay begins by reviewing methodologies for developing signal processing algorithms, including mathematical modeling, computer simulation, and performance evaluation. He links concepts to practice by presenting useful analytical results and implementations for design, evaluation, and testing. Next, he highlights specific algorithms that have stood the test of time, offers realistic examples from several key application areas, and introduces useful extensions. Finally, he guides readers through translating mathematical algorithms into MATLABcode and verifying solutions.

 

Topics covered include

Step by step approach to the design of algorithms Comparing and choosing signal and noise models Performance evaluation, metrics, tradeoffs, testing, and documentation Optimal approaches using the big theorems Algorithms for estimation, detection, and spectral estimation Complete case studies: Radar Doppler center frequency estimation, magnetic signal detection, and heart rate monitoring  

Exercises are presented throughout, with full solutions, and executable MATLAB code that implements all the algorithms, is provided on the accompanying CD.

 

This new volume is invaluable to engineers, scientists, and advanced students in every discipline that relies on signal processing; researchers will especially appreciate its timely overview of the state of the practical art. Volume III complements Dr. Kays Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory (Prentice Hall, 1993; ISBN-13: 978-0-13-345711-7), and Volume II: Detection Theory (Prentice Hall, 1998; ISBN-13: 978-0-13-504135-2).
The Complete, Modern Guide to Developing Well-Performing Signal Processing Algorithms  

In Fundamentals of Statistical Signal Processing, Volume III: Practical Algorithm Development, author Steven M. Kay shows how to convert theories of statistical signal processing estimation and detection into software algorithms that can be implemented on digital computers. This final volume of Kays three-volume guide builds on the comprehensive theoretical coverage in the first two volumes. Here, Kay helps readers develop strong intuition and expertise in designing well-performing algorithms that solve real-world problems.

 

Kay begins by reviewing methodologies for developing signal processing algorithms, including mathematical modeling, computer simulation, and performance evaluation. He links concepts to practice by presenting useful analytical results and implementations for design, evaluation, and testing. Next, he highlights specific algorithms that have stood the test of time, offers realistic examples from several key application areas, and introduces useful extensions. Finally, he guides readers through translating mathematical algorithms into MATLABcode and verifying solutions.

 

Topics covered include

Step by step approach to the design of algorithms Comparing and choosing signal and noise models Performance evaluation, metrics, tradeoffs, testing, and documentation Optimal approaches using the big theorems Algorithms for estimation, detection, and spectral estimation Complete case studies: Radar Doppler center frequency estimation, magnetic signal detection, and heart rate monitoring  

Exercises are presented throughout, with full solutions, and executable MATLAB code that implements all the algorithms, is provided on the accompanying CD.

 

This new volume is invaluable to engineers, scientists, and advanced students in every discipline that relies on signal processing; researchers will especially appreciate its timely overview of the state of the practical art. Volume III complements Dr. Kays Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory (Prentice Hall, 1993; ISBN-13: 978-0-13-345711-7), and Volume II: Detection Theory (Prentice Hall, 1998; ISBN-13: 978-0-13-504135-2).
Upplaga: 1a upplagan
Utgiven: 2013
ISBN: 9780132808033
Förlag: Prentice Hall
Format: Bok
Språk: Engelska
Sidor: 496 st
The Complete, Modern Guide to Developing Well-Performing Signal Processing Algorithms  

In Fundamentals of Statistical Signal Processing, Volume III: Practical Algorithm Development, author Steven M. Kay shows how to convert theories of statistical signal processing estimation and detection into software algorithms that can be implemented on digital computers. This final volume of Kays three-volume guide builds on the comprehensive theoretical coverage in the first two volumes. Here, Kay helps readers develop strong intuition and expertise in designing well-performing algorithms that solve real-world problems.

 

Kay begins by reviewing methodologies for developing signal processing algorithms, including mathematical modeling, computer simulation, and performance evaluation. He links concepts to practice by presenting useful analytical results and implementations for design, evaluation, and testing. Next, he highlights specific algorithms that have stood the test of time, offers realistic examples from several key application areas, and introduces useful extensions. Finally, he guides readers through translating mathematical algorithms into MATLABcode and verifying solutions.

 

Topics covered include

Step by step approach to the design of algorithms Comparing and choosing signal and noise models Performance evaluation, metrics, tradeoffs, testing, and documentation Optimal approaches using the big theorems Algorithms for estimation, detection, and spectral estimation Complete case studies: Radar Doppler center frequency estimation, magnetic signal detection, and heart rate monitoring  

Exercises are presented throughout, with full solutions, and executable MATLAB code that implements all the algorithms, is provided on the accompanying CD.

 

This new volume is invaluable to engineers, scientists, and advanced students in every discipline that relies on signal processing; researchers will especially appreciate its timely overview of the state of the practical art. Volume III complements Dr. Kays Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory (Prentice Hall, 1993; ISBN-13: 978-0-13-345711-7), and Volume II: Detection Theory (Prentice Hall, 1998; ISBN-13: 978-0-13-504135-2).
The Complete, Modern Guide to Developing Well-Performing Signal Processing Algorithms  

In Fundamentals of Statistical Signal Processing, Volume III: Practical Algorithm Development, author Steven M. Kay shows how to convert theories of statistical signal processing estimation and detection into software algorithms that can be implemented on digital computers. This final volume of Kays three-volume guide builds on the comprehensive theoretical coverage in the first two volumes. Here, Kay helps readers develop strong intuition and expertise in designing well-performing algorithms that solve real-world problems.

 

Kay begins by reviewing methodologies for developing signal processing algorithms, including mathematical modeling, computer simulation, and performance evaluation. He links concepts to practice by presenting useful analytical results and implementations for design, evaluation, and testing. Next, he highlights specific algorithms that have stood the test of time, offers realistic examples from several key application areas, and introduces useful extensions. Finally, he guides readers through translating mathematical algorithms into MATLABcode and verifying solutions.

 

Topics covered include

Step by step approach to the design of algorithms Comparing and choosing signal and noise models Performance evaluation, metrics, tradeoffs, testing, and documentation Optimal approaches using the big theorems Algorithms for estimation, detection, and spectral estimation Complete case studies: Radar Doppler center frequency estimation, magnetic signal detection, and heart rate monitoring  

Exercises are presented throughout, with full solutions, and executable MATLAB code that implements all the algorithms, is provided on the accompanying CD.

 

This new volume is invaluable to engineers, scientists, and advanced students in every discipline that relies on signal processing; researchers will especially appreciate its timely overview of the state of the practical art. Volume III complements Dr. Kays Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory (Prentice Hall, 1993; ISBN-13: 978-0-13-345711-7), and Volume II: Detection Theory (Prentice Hall, 1998; ISBN-13: 978-0-13-504135-2).
Begagnad bok (0 st)

Om Fundamentals of Statistical Signal Processing, Volume III (2013)

I mars 2013 släpptes boken Fundamentals of Statistical Signal Processing, Volume III skriven av Steven M. Kay. Det är den 1a upplagan av kursboken. Den är skriven på engelska och består av 496 sidor djupgående information. Förlaget bakom boken är Prentice Hall som har sitt säte i Upper saddle river.

Köp boken Fundamentals of Statistical Signal Processing, Volume III direkt från en annan student på Studentapan och spara pengar.

Bokens omdömen
Ingen har recenserat den här boken ännu.

Sälj vidare boken när du är klar

När du är klar med boken säljer du enkelt vidare och tjänar pengar på nolltid med Studentapan. Vi tar hand om allt det krångliga så att du får mer tid över till annat. På det sättet kan du tjäna tillbaka det mesta av kostnaden för boken.
Värdera & sälj böcker

Klimatsmart kurslitteratur

Bli en miljöhjälte under din studietid och ge dina gamla kursböcker ett nytt liv. Genom att återanvända dina kursböcker minskar du utsläppen av koldioxid (CO2) med hela 59%. För en psykologstudent skulle det innebära minskade CO2-utsläpp med cirka 240 kg under studietiden. En stor vinst för din plånbok och miljön. Det kallar vi klimatsmart kurslitteratur.

Liknande kurslitteratur

Begagnad bok (0 st)