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Total Size:
39.5 MB
Info Hash:
349ED96E6DAAE670604BA44FAC128D62B88CBFDC
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Added:
April 20, 2026, 4:56 a.m.
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(Last updated: April 20, 2026, 5:01 a.m.)
| File | Size |
|---|---|
| Readme.txt | 1.3 KB |
| Cochard G. Mathematics for Digital Science 2. Digital Information 2025.pdf | 15.1 MB |
| Cochard G. Mathematics for Digital Science 1. Fundamentals 2025.pdf | 24.4 MB |
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19.9 MB
[40
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31]
2025-07-05
| Uploaded by andryold1 | Size 19.9 MB | Health [ 40 /31 ] | Added 2025-07-05 |
NOTE
SOURCE: Cochard G. Mathematics for Digital Science 2. Digital Information 2025
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COVER
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MEDIAINFO
Textbook in PDF format Over the past century, advancements in computer science have consistently resulted from extensive mathematical work. Even today, innovations in the digital domain continue to be grounded in a strong mathematical foundation. To succeed in this profession, both today’s students and tomorrow’s computer engineers need a solid mathematical background. The goal of this book series is to offer a solid foundation of the knowledge essential to working in the digital sector. Across three volumes, it explores fundamental principles, digital information, data analysis, and optimization. Whether the reader is pursuing initial training or looking to deepen their expertise, the Mathematics for Digital Science series revisits familiar concepts, helping them refresh and expand their knowledge while also introducing equally essential, newer topics. Preface. Representation of Numbers. Media Representation. Signals and Systems. Z-transforms, Fourier Transforms and Laplace Transforms. Digitizing an Analog Signal. Modulation. Filtering. The Digital Image. 2D Computer Graphics. Concepts in Image Processing and Analysis. Basics of Image Compression. Elements of Numerical Analysis. References. List of Authors. Index
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