Description: Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing by Michael Elad (Springer, Hardcover, 2010). 376 pages. Condition is Very Good; clean, firm binding, no writing or highlighting, no folded or torn pages. “Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing" by Michael Elad offers an in-depth exploration of sparse and redundant representation modeling. The book begins with a thorough introduction to the theoretical and numerical foundations of these representations, providing readers with a solid understanding of the underlying principles. Elad then delves into various applications of these models in signal and image processing, showcasing how they can be effectively utilized in real-world scenarios. The book is particularly valuable for practitioners in the field, as it offers practical insights and examples that demonstrate the advantages of using sparse and redundant representations for tasks such as image denoising, compression, and feature extraction. The book also includes supplementary material, such as a formula list and additional resources, to aid readers in applying these concepts to their own work. We welcome all offers and inquiries, more photos and information available upon request. Shipped securely and promptly with USPS mail.
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End Time: 2024-11-11T02:15:38.000Z
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Number of Pages: Xx, 376 Pages
Language: English
Publication Name: Sparse and Redundant Representations : from Theory to Applications in Signal and Image Processing
Publisher: Springer New York
Subject: Signals & Signal Processing, Image Processing, Applied, Optimization, Mathematical Analysis
Publication Year: 2010
Item Weight: 29.3 Oz
Type: Textbook
Subject Area: Mathematics, Computers, Technology & Engineering
Author: Michael Elad
Item Length: 9.3 in
Item Width: 6.1 in
Format: Hardcover
