The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and F
This second edition of The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance has been fully updated and revised to reflect recent developments in the theory and practical applications of wavelet transform methods.
The book is designed specifically for the applied reader in science, engineering, medicine and finance. Newcomers to the subject will find an accessible and clear account of the theory of continuous and discrete wavelet transforms, while readers already acquainted with wavelets can use the book to broaden their perspective.
One of the many strengths of the book is its use of several hundred illustrations, some in colour, to convey key concepts and their varied practical uses. Chapters exploring these practical applications highlight both the similarities and differences in wavelet transform methods across different disciplines and also provide a comprehensive list of over 1000 references that will serve as a valuable resource for further study.
Paul Addison is a Technical Fellow with Medtronic, a global medical technology company. Previously, he was co-founder and CEO of start-up company, CardioDigital Ltd (and later co-founded its US subsidiary, CardioDigital Inc) - a company concerned with the development of novel wavelet-based methods for biosignal analysis. He has a master’s degree in engineering and a PhD in fluid mechanics, both from the University of Glasgow, Scotland (founded 1451). His former academic life as a tenured professor of fluids engineering included the output of a large number of technical papers, covering many aspects of engineering and bioengineering, and two textbooks: Fractals and Chaos: An Illustrated Course and the first edition of The Illustrated Wavelet Transform Handbook. At the time of publication, the author has over 100 issued US patents concerning a wide range of medical device technologies, many of these concerning the wavelet transform analysis of biosignals. He is both a Chartered Engineer and Chartered Physicist.
Why Read This Book
You will get a highly visual, application-focused introduction to continuous and discrete wavelet transforms that makes complex theory intuitive through hundreds of figures and worked examples. You will learn practical techniques for denoising, compression, time–frequency analysis and real-world applications in engineering, medicine and finance—without requiring a deep pure-math background.
Who Will Benefit
Practicing engineers, applied researchers and graduate students in signal processing, audio/speech, radar, communications or biomedical analytics who need a hands-on, visually guided entry to wavelet methods and their applications.
Level: Intermediate — Prerequisites: Undergraduate calculus and linear algebra, a working knowledge of Fourier transforms and basic signals & systems concepts, and some familiarity with numerical computing (MATLAB or Python recommended).
Key Takeaways
- Understand the mathematical foundations and intuition behind continuous and discrete wavelet transforms and multiresolution analysis.
- Design and implement discrete wavelet filter banks and DWT algorithms for practical DSP tasks.
- Apply wavelet methods for denoising, compression and time–frequency analysis of audio, speech, radar and biomedical signals.
- Interpret wavelet scalograms, wavelet spectra and use wavelet packets and scalings for feature extraction and classification.
- Integrate wavelet transforms with FFT-based spectral tools and software toolboxes to process real datasets.
Topics Covered
- Preface and overview of wavelet history and applications
- Mathematical preliminaries: signals, transforms and time–frequency concepts
- Continuous wavelet transform (CWT): theory, admissibility and scalograms
- Discrete wavelet transform (DWT) and multiresolution analysis (MRA)
- Wavelet filter banks: design, implementation and perfect reconstruction
- Wavelet packets, best-basis selection and tiling the time–frequency plane
- Connections to Fourier/FFT methods and short-time Fourier transform
- Practical algorithms: lifting scheme, fast wavelet transforms and numerical issues
- Wavelet denoising, thresholding methods and compression techniques
- Applications: audio & speech processing, radar signal processing and communications
- Applications: biomedical signals, medical imaging and finance
- Software, implementation notes, examples and case studies
- Appendices: tables of wavelets, transforms and further reading
Languages, Platforms & Tools
How It Compares
More application-oriented and heavily illustrated than Mallat's A Wavelet Tour of Signal Processing and less abstract than Daubechies' Ten Lectures on Wavelets, making Addison a better practical entry for applied engineers.
