Introduction: Signals and Signal Processing. Local Analysis. A Roadmap for the Book -- Continuous Analysis: The Short Time Fourier Transform STFT. The Continuous Wavelet Transform CWT. Case Studies. Notes and Exercises -- The Discrete Wavelet Transform: Redundancy of the CWT and the STFT. The Haar-System. Generalization to Daubechies Wavelets. Multiscale Analysis. A Unifying Viewpoint: Basis Systems. Case Studies. Notes and Exercises -- More Applications: The Transform Compression Scheme. Wavelet-Based Similarity Retrieval in Image Archives -- Appendix: Fourier Transform and Uncertainty Relation. Discrete Fourier Transform DFT. Digital Filters. Solution to Selected Problems. Notations and Symbols -- References -- Index .

As the applications of wavelet transform have spread to diverse areas of signal analysis and compression, students and practitioners need a practical introduction and overview. This textbook provides that concise and practical introduction to the underlying foundations and important applications. Through numerous examples and case studies from industry, it demonstrates both the potential and the limits of wavelet techniques, expanding the usual treatment beyond the discrete wavelet transform to the continuous transform. Providing the basics of Fourier transforms and digital filters in the appendix, the text is supplemented with end-of-chapter exercises, MATLAB code, and a short introduction to the MATLAB wavelet toolbox. Students of electrical engineering and engineers in industry can benefit from the concentration on real applications. .