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Digital Signal Processing: Illustration Using Python
This book serves as an indispensable resource for developing signal processing algorithms using Python, making learning both accessible and practical.
Digital Signal Processing: Illustration Using Python
Item #: 97725361

Digital Signal Processing: Illustration Using Python

Item #: 97725361

MUR 2887

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This book serves as an indispensable resource for developing signal processing algorithms using Python, making learning both accessible and practical.
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What Stands Out

Practical Illustrations
Engaging examples using Python make complex digital signal processing concepts easier to understand, enhancing learning and retention for students and professionals eager to implement real-world applications.
Updated Content
This 2024 edition incorporates the latest trends and technologies in digital signal processing, ensuring readers are equipped with current knowledge and practices relevant to today's industry demands.
User-Friendly Approach
Designed for learners at all levels, the book simplifies theoretical concepts and provides step-by-step coding tutorials, making digital signal processing accessible and enjoyable for both beginners and experienced programmers.

Product Details

Shop Digital Signal Processing: Illustration Using Python online at a best price in Mauritania. 9819967511
  • Digital signal processing deals with extraction of useful information from signals. Signal processing algorithms help observe, analyse and transform signals. The objective of this book is to develop signal processing algorithms using Python. Python is an interpreted, object-oriented high-level programming language widely used in various software development fields such as data science, machine learning, web development and more. Digital Signal Laboratory is playing an important role in realizing signal processing algorithms, utilizing different software solutions. The intention of this textbook is to implement signal processing algorithms using Python. Since Python is an open-source language, students, researchers, and faculty can install and work with it without spending money, reducing the financial burden on institutions. Each chapter in this book begins with prelab questions, a set of Python examples to illustrate the concepts, exercises to strengthen the understanding of the concepts, and objective questions to help students prepare for competitive examinations. This book serves as an undergraduate textbook, it can be used for individual study, and it can also be used as the textbook for related courses.
Publisher Springer
Publication date January 26, 2024
Edition 2024th
Language English
Print length 544 pages
ISBN-10 9819967511
ISBN-13 978-9819967513
Item Weight 7.6 ounces (215.46 grams)
Dimensions 6.1 x 1.23 x 9.25 inches (15.5 x 3.1 x 23.5 cm)

Who Should Buy?

Suitable For
  • Students in DSP

    Ideal for students learning digital signal processing, providing practical examples using Python for better understanding.

  • Python Programmers

    Great for programmers looking to enhance their knowledge of digital signal processing while leveraging Python for practical applications.

  • Researchers

    Useful for researchers needing a comprehensive reference on DSP, complete with Python illustrations for experimental applications.

Not Suitable For
  • Non-technical Users

    Not suitable for users without a technical background as it assumes familiarity with programming and signal processing concepts.

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DSPs Editorial Review

Digital Signal Processing: Illustration Using Python is a comprehensive guide with an insightful approach to digital signal processing principles illustrated through Python programming. Published by Springer and spanning 541 pages, this 2024 edition provides a thorough exploration of the subject while also being accessible for beginners. The book's structured methodology ensures that even those new to the field can grasp complex concepts effectively. Readers appreciate the clear explanations and relatable examples that align with practical applications in Python, making it a valuable resource for students and professionals alike.

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Pros

  • Comprehensive guide with clear explanations
  • Accessible for beginners in the field
  • Illustrative examples using Python
  • Structured methodology for easy understanding
  • In-depth coverage of digital signal processing

Cons

  • Might be overwhelming for complete novices

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