Multiscale Fourier descriptors for defect image retrieval
Pattern Recognition Letters
A basis for efficient representation of the S-transform
Digital Signal Processing
Symbolic time series analysis via wavelet-based partitioning
Signal Processing - Special section: Distributed source coding
Wavelet-based algorithm for signal analysis
EURASIP Journal on Applied Signal Processing
Bio-inspired optimisation for economic load dispatch: a review
International Journal of Bio-Inspired Computation
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This unique resource examines the conceptual, computational, and practical aspects of applied signal processing using wavelets. With this book, readers will understand and be able to use the power and utility of new wavelet methods in science and engineering problems and analysis. The text is written in a clear, accessible style avoiding unnecessary abstractions and details. From a computational perspective, wavelet signal processing algorithms are presented and applied to signal compression, noise suppression, and signal identification. Numerical illustrations of these computational techniques are further provided with interactive software (MATLAB code) is available on the world wide web. Topics and Features: * Continuous wavelet and Gabor transforms * Frame-based theory of discretization and reconstruction of analog signals is developed * New and efficient "overcomplete" wavelet transform is introduced and applied * Numerical illustrations with an object-oriented computational perspective using the Wavelet Signal Processing Workstation (MATLAB code) available This book is an excellent resource for information and computational tools needed to use wavelets in many types of signal processing problems. Graduates, professionals, and practitioners in engineering, computer science, geophysics, and applied mathematics will benefit from using the book and software tools.