Computer-Based Exercises for Signal Processing Using MATLAB 5. Cet article n’est pas disponible.
McClellan, James H., Oppenheim, Alan V., Burrus, C. Sidney, Schafer, Ronald W., Parks, Thomas W.
Langue : anglais
Edité par Pearson Education, Limited, 1997
- Livre broché
- Occasion

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A propos de cet article
Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
N° de réf. du vendeur 4512221-6
- Titre
- Computer-Based Exercises for Signal Processing Using MATLAB 5
- Auteur
- McClellan, James H., Oppenheim, Alan V., Burrus, C. Sidney, Schafer, Ronald W., Parks, Thomas W.
- Éditeur
- Pearson Education, Limited
- Année de publication
- 1997
- État de l'article
- Very Good
- Reliure
- Couverture souple
- Langue
- anglais
- ISBN à 10 chiffres
- 0137890095
- ISBN à 13 chiffres
- 9780137890095
- Poids de l'article
- 0,221 livre
- Dimensions
- N/A
For senior or introductory graduate-level courses in digital signal processing.
Developed by a group of six eminent scholars and teachers, this book offers a rich collection of exercises and projects which guide students in the use of MATLAB v5 to explore major topical areas in digital signal processing.
« Synopsis » peut appartenir à une autre édition de cet ouvrage.
À propos de la quatrième de couverture
FEATURES:
- Presents many computer-based problems that can be done in conjunction with a course in DSP theory.
- Projects relate to practical systems and implementations so the reader can learn and understand how DSP is applied.
- Includes projects and exercises, which make full use of the power of MATLAB v5 to explore conceptual, analytical, and computational issues in digital signal processing.
- Many projects provide hints to introduce pitfalls, limitations and tricks for getting the most out of MATLAB v5.
- Discusses both the power and limitations of MATLAB v5 functions and regularly explores the issue of using built-in functions versus developing code to solve problems.
- Exercises consistently reinforce important problem solving behaviors, such as verifying results, experimenting with parameters as a means of building understanding and intuition, exploring the realism of formulations, comparing theoretical and numerical or measured results, and developing predictions and then comparing them to actual results.
« A propos de ce titre » peut appartenir à une autre édition de cet ouvrage.