Fourier and wavelet analysis in artificial intelligence
Foundations techniques and applications in feature extraction and computer vision
How does a machine recognize a face?
How can AI distinguish speech from noise?
Why do modern computer vision systems still rely on mathematical techniques developed decades ago?
The answer lies in Fourier and Wavelet Analysis.
In Fourier and Wavelet Analysis in Artificial Intelligence, Anshuman Mishra reveals how frequency-domain representations, multi-resolution analysis, and signal-processing techniques continue to shape the future of Machine Learning, Deep Learning, Computer Vision, Speech Recognition, Biomedical AI, and Edge Intelligence.
From Fourier Transforms and Fast Fourier Algorithms to Wavelet Scattering Networks and Hybrid CNN Architectures, this book demonstrates how mathematical signal analysis becomes intelligent feature extraction.
Discover the mathematics behind perception, representation, and intelligent decision-making.
Minimum price
$9.99
$19.99
You pay
Author earns
About
About the Book
Fourier and Wavelet Analysis in Artificial Intelligence
Foundations, Techniques, and Applications in Feature Extraction and Computer VisionArtificial Intelligence systems are only as powerful as the representations they learn from data. Whether analyzing speech signals, recognizing faces, interpreting medical images, processing sensor streams, or understanding complex visual environments, intelligent systems depend on effective methods for extracting meaningful information from raw data.
Among the most influential mathematical tools for signal representation and feature extraction are Fourier Analysis and Wavelet Analysis.
The book "Fourier and Wavelet Analysis in Artificial Intelligence: Foundations, Techniques, and Applications in Feature Extraction and Computer Vision" provides a comprehensive exploration of these two transformative mathematical frameworks and demonstrates how they contribute to modern Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Speech Processing, Biomedical Analytics, and Sensor Intelligence.
Fourier analysis revolutionized science by enabling signals to be represented in the frequency domain, revealing patterns hidden from direct observation. Wavelet analysis extended this capability by introducing multi-resolution representations capable of analyzing signals simultaneously in both time and frequency domains.
Today, these mathematical foundations power numerous AI applications including:
• Computer Vision and Image Recognition
• Speech and Audio Processing
• Biomedical Signal Analysis
• Edge AI and Embedded Systems
• Sensor Networks and Internet of Things (IoT)
• Feature Engineering for Machine Learning
• Deep Learning Architectures
• Pattern Recognition and Classification
• Signal Compression and Denoising
• Intelligent Decision Support Systems
This book begins with the mathematical foundations of Fourier and wavelet transforms before progressing toward modern applications in machine learning and deep learning.
Readers will learn:
• Fourier Series and Fourier Transform Theory
• Discrete Fourier Transform (DFT)
• Fast Fourier Transform (FFT)
• Continuous and Discrete Wavelet Transforms
• Multiresolution Analysis
• Wavelet Packets and Filter Banks
• Signal Processing Foundations
• Time-Frequency Analysis
• Feature Extraction Techniques
• Fourier Descriptors and Texture Analysis
• Wavelet-Based Feature Engineering
• Fourier Neural Operators
• Wavelet Scattering Networks
• CNN-Wavelet Hybrid Models
• Image Compression and Enhancement
• Speech Recognition Systems
• Biomedical Signal Classification
• IoT Sensor Analytics
• Emerging Quantum Fourier Applications
Unlike traditional signal-processing textbooks that focus exclusively on engineering applications, this book emphasizes Artificial Intelligence perspectives, showing how signal representations become intelligent features that drive machine learning and deep learning models.
The content balances mathematical rigor, practical implementation, real-world applications, and future research directions, making it equally useful for students, researchers, educators, and industry professionals.
Who Should Read This Book?• BCA, MCA, B.Tech, M.Tech, BSc and MSc Students
• Artificial Intelligence and Machine Learning Learners
• Data Scientists and AI Engineers
• Computer Vision Researchers
• Signal Processing Professionals
• Biomedical Engineering Students
• Electronics and Communication Engineers
• Researchers in AI, Pattern Recognition, and Deep Learning
What Makes This Book Unique?✔ Bridges mathematics, signal processing, and Artificial Intelligence
✔ Covers both classical and modern transform techniques
✔ Includes machine learning and deep learning applications
✔ Provides practical implementations using Python, MATLAB, TensorFlow, PyTorch, and OpenCV
✔ Features real-world case studies across multiple domains
✔ Explores emerging research areas such as Fourier Neural Operators and Wavelet Scattering Networks
✔ Suitable for academic courses, self-study, research, and professional development
By combining theoretical foundations with practical AI applications, this book helps readers understand not only how Fourier and wavelet transforms work, but also why they remain essential in the age of deep learning and intelligent systems.
Author
About the Author
Anshuman Kumar Mishra, M.Tech (Computer Science) Assistant Professor, Doranda College, Ranchi University
Prolific Author of 50+ Books on AI, Machine Learning & Computer Science | 20+ Years Experience
Anshuman Kumar Mishra is a dedicated educator, researcher, and highly prolific author with over 20 years of experience in Computer Science and Information Technology. Holding an M.Tech in Computer Science from BIT Mesra, he brings a rare combination of academic depth and practical teaching expertise.
Currently serving as Assistant Professor at Doranda College under Ranchi University, he has mentored thousands of students, helping them build strong foundations in programming, data science, and artificial intelligence. His student-centric teaching style emphasizes conceptual clarity, hands-on practice, and real-world application.
Anshuman is a prolific author with more than 50 books published across a wide spectrum of computer science and emerging technology domains. From foundational programming languages to advanced topics in Artificial Intelligence, Machine Learning, Reinforcement Learning, Decision Theory, and Computer Vision — his books are widely appreciated by students, educators, and professionals for their clear explanations, strong theoretical foundation, and practical approach.
His extensive body of work reflects his deep commitment to making complex subjects accessible and meaningful for learners at all levels. He is particularly recognized for creating well-structured learning paths that help readers progress from beginner to advanced levels with confidence.
Driven by the mission to democratize quality technical education, Anshuman continues to write and update books that bridge the gap between academic theory and industry practice.
When not teaching or writing, he actively follows and explores new developments in AI, Quantum Machine Learning, and Ethical Intelligence systems.
Contents
Table of Contents
The Leanpub 60 Day 100% Happiness Guarantee
Within 60 days of purchase you can get a 100% refund on any Leanpub purchase, in two clicks.
Now, this is technically risky for us, since you'll have the book or course files either way. But we're so confident in our products and services, and in our authors and readers, that we're happy to offer a full money back guarantee for everything we sell.
You can only find out how good something is by trying it, and because of our 100% money back guarantee there's literally no risk to do so!
So, there's no reason not to click the Add to Cart button, is there?
See full terms...
Earn $8 on a $10 Purchase, and $16 on a $20 Purchase
We pay 80% royalties on purchases of $7.99 or more, and 80% royalties minus a 50 cent flat fee on purchases between $0.99 and $7.98. You earn $8 on a $10 sale, and $16 on a $20 sale. So, if we sell 5000 non-refunded copies of your book for $20, you'll earn $80,000.
(Yes, some authors have already earned much more than that on Leanpub.)
In fact, authors have earned over $15 million writing, publishing and selling on Leanpub.
Learn more about writing on Leanpub
Free Updates. DRM Free.
If you buy a Leanpub book, you get free updates for as long as the author updates the book! Many authors use Leanpub to publish their books in-progress, while they are writing them. All readers get free updates, regardless of when they bought the book or how much they paid (including free).
Most Leanpub books are available in PDF (for computers) and EPUB (for phones, tablets and Kindle). The formats that a book includes are shown at the top right corner of this page.
Finally, Leanpub books don't have any DRM copy-protection nonsense, so you can easily read them on any supported device.
Learn more about Leanpub's ebook formats and where to read them
Write and Publish on Leanpub
You can use Leanpub to easily write, publish and sell in-progress and completed ebooks and online courses!
Leanpub is a powerful platform for serious authors, combining a simple, elegant writing and publishing workflow with a store focused on selling in-progress ebooks.
Leanpub is a magical typewriter for authors: just write in plain text, and to publish your ebook, just click a button. (Or, if you are producing your ebook your own way, you can even upload your own PDF and/or EPUB files and then publish with one click!) It really is that easy.