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The rapid growth of wavelet applications-speech compression and analysis, image compression and enhancement, and removing noise from audio and images-has created an explosion of activity in creating a theory of wavelet analysis and applying it to a wide variety of scientific and engineering problems. It becomes important, then, that engineers and scientists have a working understanding of wavelets. Until now, however, the study of wavelets has been beyond the mathematical grasp of many who need this understanding. Most treatments of the subject involve ideas from functional analysis, harmonic analysis, and other difficult mathematical techniques.
Wavelets and their Scientific Applications offers an introduction to wavelet analysis without mathematical rigor, requiring only algebra and some very basic calculus. The author stresses applications, and explains, using elementary algebra, how wavelet methods are typically applied in analyzing digital data.
Software is available for download through CRC's Website that will enable recording, playing, and modifying sound files, and includes a facility for displaying, printing and modifying IEEE gray field images. Unlike other software packages for wavelet analysis, the author developed this attractive, easy-to-use software without the need for a C++ compiler or MATLABä. Throughout the book the author provides numerous suggestions for computer experiments designed to challenge and enhance the reader's comprehension and provide practice in applying the concepts learned.
Wavelets and their Scientific Applications thus provides the perfect vehicle for understanding wavelets and their uses. It provides a fast-track learning opportunity for scientists and mathematicians unfamiliar with wavelet concepts and applications, and it is ideal for anyone without an extensive mathematical background.
"...offers an introduction to wavelet analysis without mathemataical rigor, requiring only algebra & some basic calculus. The author stresses applications & explains how wavelet methods are typically applied in analyzing data."
|1.1||The Haar transform||1|
|1.2||Conservation and compaction of energy||6|
|1.5||Compression of audio signals||18|
|1.6||Removing noise from audio signals||23|
|1.7||Notes and references||28|
|2.1||The Daub4 wavelets||29|
|2.2||Conservation and compaction of energy||38|
|2.3||Other Daubechies wavelets||42|
|2.4||Compression of audio signals||49|
|2.5||Quantization, entropy, and compression||53|
|2.6||Denoising audio signals||58|
|2.7||Two-dimensional wavelet transforms||65|
|2.8||Compression of images||72|
|2.11||Some topics in image processing||87|
|2.12||Notes and references||92|
|3.1||Discrete Fourier analysis||95|
|3.2||Definition of the DFT and its properties||98|
|3.3||Frequency description of wavelet analysis||103|
|3.4||Correlation and feature detection||108|
|3.5||Object detection in 2D images||114|
|3.6||Creating scaling signals and wavelets||118|
|3.7||Notes and references||122|
|4.1||Wavelet packet transforms||123|
|4.2||Applications of wavelet packet transforms||126|
|4.3||Continuous wavelet transforms||129|
|4.4||Gabor wavelets and speech analysis||134|
|4.5||Notes and references||138|
|A||Software for wavelet analysis||139|
Posted July 27, 2002
This lovely little book helps the novice to get an idea of the math behind wavelets, and at the same time to learn how one readily gets hold of software that is convinient, that will make it easy for anyone to start playing around with it. It also explains in plain English the wavelet aspects of audio denoising, signal compression, image recognition, speech recognition and more.Was this review helpful? Yes NoThank you for your feedback. Report this reviewThank you, this review has been flagged.