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  • TUTORIAL CHAPTER 1 - Preview of Wavelets, Wavelet Filters, and Wavelet Transforms

  • 1.1 What is a Wavelet?
    1.2 What is a Wavelet Filter and how is it different from a Wavelet?
    1.3 The value of Transforms and Examples of Everyday Use
    1.4 Short-Time Transforms, Sheet Music, and a first look at Wavelet Transforms
    1.5 Example of the Fast Fourier Transform (FFT) with an Embedded Pulse Signal
    1.6 Examples using the Continuous Wavelet Transform
    1.7 A First Glance at the Undecimated Discrete Wavelet Transform (UDWT)
    1.8 A First Glance at the conventional Discrete Wavelet Transform (DWT)
    1.9 Examples of use of the conventional DWT
    1.10 Tutorial Summary

  • TUTORIAL CHAPTER 2 - The Continuous Wavelet Transform (CWT) Step-by-Step

  • 2.1 Simple Scenario: Comparing Exam Scores using the Haar Wavelet
    2.2 Above Comparison Process seen as simple Correlation or Convolution
    2.3 CWT Display of the Exam Scores using the Haar Wavelet Filter
    2.4 Tutorial Summary

  • TUTORIAL CHAPTER 3 - The Undecimated Discrete Wavelet Transform (UDWT) Step-by-Step

  • 3.1 Single-Level Undecimated Discrete Wavelet Transform (UDWT) of Exam Data
    3.2 Frequency Allocation of a Single-Level UDWT
    3.3 Multi-Level Undecimated Discrete Wavelet Transform (UDWT)
    3.4 Frequency Allocation of a Multiple-Level UDWT
    3.5 The Haar UDWT as a Moving Averager
    3.6 Tutorial Summary

  • TUTORIAL CHAPTER 4 - The Conventional (Decimated) DWT Step-by-Step

  • 4.1 Single-Level (Decimated) Discrete Wavelet Transform (DWT) of Exam Data
    4.2 Additional Example of Perfect Reconstruction in a Single-Level DWT
    4.3 Compression and Denoising Example using the Single-Level DWT
    4.4 Multi-Level Conventional (Decimated) DWT of Exam Data using Haar Filters
    4.5 Frequency Allocation in a (Conventional, Decimated) DWT
    4.6 Final Approximations and Details and how to read the DWT Display
    4.7 Denoising using a Multi-Level DWT
    4.8 Tutorial Summary

  • TUTORIAL CHAPTER 11 - Case Studies of Wavelet Applications

  • 11.1 White Noise in a Chirp Signal
    11.2 Binary Signal Buried in Chirp Noise
    11.3 Binary Signal with White Noise
    11.4 Image Compression/De-noising
    11.5 Improved Performance using the UDWT
    11.6 Tutorial Summary

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