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خرید و دانلود کتاب Understanding Fourier Transforms with Python: A Practical Approach
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English [en] · PDF · 0.7MB · 2024 · 📘 Book (non-fiction)
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دسته: کتاب الکترونیکی و صوتی
توضیحات
Understanding Fourier Transforms with Python: A Practical Approach
Publishing, Reactive; Van Der Post, Hayden Reactive Publishing, 2024
English [en] · EPUB · 0.7MB · 2024 · 📘 Book (non-fiction) · 🚀/lgli/lgrs · Save · 323
description
Reactive Publishing
Unlock the power of one of the most essential tools in signal processing and data analysis with *Understanding Fourier Transforms with Python: A Practical Approach*. This indispensable guide dives beyond the basics, welcoming enthusiasts and professionals eager to expand their knowledge and apply sophisticated techniques to their projects.
Building on the foundations laid by top-selling introductory texts, this book delves into advanced concepts and practical applications of Fourier transforms using Python, the increasingly popular language of scientific computing. With clear explanations, hands-on examples, and practical insights, you’ll discover how to harness the full potential of Fourier analysis to solve complex problems in various domains, from engineering and physics to data science and beyond.
Inside, you’ll find
– A thorough review of fundamental principles, ensuring a solid grounding before progressing to more advanced topics.
– Step-by-step guidance on implementing Fourier transforms using Python, accompanied by code snippets and detailed explanations.
– Real-world applications and case studies that illustrate how Fourier analysis can be leveraged to tackle challenging issues.
– Expert tips and tricks to optimize your Python code for performance and efficiency.
– Exercises and projects designed to reinforce learning and encourage experimentation.
Unlock the power of one of the most essential tools in signal processing and data analysis with *Understanding Fourier Transforms with Python: A Practical Approach*. This indispensable guide dives beyond the basics, welcoming enthusiasts and professionals eager to expand their knowledge and apply sophisticated techniques to their projects.
Building on the foundations laid by top-selling introductory texts, this book delves into advanced concepts and practical applications of Fourier transforms using Python, the increasingly popular language of scientific computing. With clear explanations, hands-on examples, and practical insights, you’ll discover how to harness the full potential of Fourier analysis to solve complex problems in various domains, from engineering and physics to data science and beyond.
Inside, you’ll find
– A thorough review of fundamental principles, ensuring a solid grounding before progressing to more advanced topics.
– Step-by-step guidance on implementing Fourier transforms using Python, accompanied by code snippets and detailed explanations.
– Real-world applications and case studies that illustrate how Fourier analysis can be leveraged to tackle challenging issues.
– Expert tips and tricks to optimize your Python code for performance and efficiency.
– Exercises and projects designed to reinforce learning and encourage experimentation.
Alternative filename
lgli/Understanding Fourier Transforms with Python: A Practical Approach.epub
Alternative description
Title Page
Preface
Chapter 1: Introduction to Fourier Transforms
Chapter 2: Mathematical Foundations
Chapter 3: The Discrete Fourier Transform (DFT)
Chapter 4: Fast Fourier Transform (FFT)
Chapter 5: Fourier Transform in Signal Processing
Chapter 6: Fourier Transform in Image Processing
Chapter 7: Advanced Topics in Fourier Transforms
Chapter 8: Fourier Transform in Data Analysis
Chapter 9: Practical Applications and Projects
Appendix A: Tutorials
Appendix B: Glossary of Terms
Appendix C: Additional Resources
Epilogue
Preface
Chapter 1: Introduction to Fourier Transforms
Chapter 2: Mathematical Foundations
Chapter 3: The Discrete Fourier Transform (DFT)
Chapter 4: Fast Fourier Transform (FFT)
Chapter 5: Fourier Transform in Signal Processing
Chapter 6: Fourier Transform in Image Processing
Chapter 7: Advanced Topics in Fourier Transforms
Chapter 8: Fourier Transform in Data Analysis
Chapter 9: Practical Applications and Projects
Appendix A: Tutorials
Appendix B: Glossary of Terms
Appendix C: Additional Resources
Epilogue
date open sourced
2024-08-10
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