Provides a textbook treatment that is 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.

As the applications of wavelets 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 students and engineers in industry can benefit from the concentration on real applications.

Compact and application-oriented introduction to the subject Matlab codes for the application of wavelets are available for download over the internet Brief introduction to the Wavelets Toolbox of Matlab Includes supplementary material: sn.pub/extras

Autorentext

Hans-Georg Stark

studied physics at Würzburg University and the State University of New York at Albany (USA). Degrees: Master of Science 1979, Diploma 1981, PhD 1984 (each in theoretical physics). After the PhD, he held scientific positions in academia (Technomathematics Group at Kaiserslautern University) and industry (VDO-Adolf-Schindling AG and TECMATH GmbH), where he worked in reliability analysis (VDO) and image- and signal processing (TECMATH) and coordinated the respective company's activities. Since 1996 he is Professor of Mathematics and Computer Science, first at Würzburg-Schweinfurt-Aschaffenburg University of Applied Sciences and, since 1999, at Aschaffenburg University of Applied Sciences. His current research and teaching are in the fields of applied mathematics and signal- and image analysis, and he also serves as an industrial consultant.

Inhalt
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