Conceptual wavelets in digital signal processing: an by D. Lee Fugal

By D. Lee Fugal

I'm a practising sign processing engineer and feature been operating with wavelets on the grounds that they have been first invented. My purposes were in modulation (US Robotics), audio/image/video processing/compression/recognition, hybrid algorithms, predictive algorithms, move prediction for a magnetically levitated synthetic middle (spin-off from the college of Utah), x-ray florescence spectroscopy (XRF) detectors, and wavelet/neural community algorithms for fuel chromatography.

The technology of wavelets used to be invented by way of mathematicians -- so, all the early books have been written by way of mathematicians and intensely tricky to navigate. the facility of those new wavelet equipment past Fourier Transforms used to be visible, yet relatively obscure and use.

I have an important number of books on wavelets from many of the mathematicians. while I got Lee Fugal's booklet, i used to be more than happy to work out whatever that used to be written from a pragmatic standpoint. i discovered the e-book effortless to learn and comprehend, or even with a beautiful heavy historical past in wavelets, I discovered alot. additionally as a MatLAB consumer, it was once really nice to discover helpful code examples in addition to wavelet toolbox features defined in detail.

Thank you Lee Fugal for taking for all time to jot down this ebook. every thing else on my bookshelf is amassing dirt -- Lee's ebook, 'Conceptual Wavelets' is what i take advantage of on a daily basis in my work.

Best regards,

W. Kurt Dobson, CEO
Sigma know-how Holdings
Salt Lake urban, UT

Show description

By D. Lee Fugal

I'm a practising sign processing engineer and feature been operating with wavelets on the grounds that they have been first invented. My purposes were in modulation (US Robotics), audio/image/video processing/compression/recognition, hybrid algorithms, predictive algorithms, move prediction for a magnetically levitated synthetic middle (spin-off from the college of Utah), x-ray florescence spectroscopy (XRF) detectors, and wavelet/neural community algorithms for fuel chromatography.

The technology of wavelets used to be invented by way of mathematicians -- so, all the early books have been written by way of mathematicians and intensely tricky to navigate. the facility of those new wavelet equipment past Fourier Transforms used to be visible, yet relatively obscure and use.

I have an important number of books on wavelets from many of the mathematicians. while I got Lee Fugal's booklet, i used to be more than happy to work out whatever that used to be written from a pragmatic standpoint. i discovered the e-book effortless to learn and comprehend, or even with a beautiful heavy historical past in wavelets, I discovered alot. additionally as a MatLAB consumer, it was once really nice to discover helpful code examples in addition to wavelet toolbox features defined in detail.

Thank you Lee Fugal for taking for all time to jot down this ebook. every thing else on my bookshelf is amassing dirt -- Lee's ebook, 'Conceptual Wavelets' is what i take advantage of on a daily basis in my work.

Best regards,

W. Kurt Dobson, CEO
Sigma know-how Holdings
Salt Lake urban, UT

Show description

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Extra resources for Conceptual wavelets in digital signal processing: an in-depth, practical approach for the non-mathematician

Example text

We will use a seven-level DWT for this next example. 8–1, we would have further decomposition of A1 into A2 and D2, then A2 into A3 and D3, and so on until A6 is decomposed into A7 and D7. The frequency allocation for a conventional DWT (assuming no aliasing problems) is the same as that for the UDWT. 7–5 for the allocation by a 4-level DWT (or 4-level UDWT). Suppose we had a binary signal that had a great deal of noise added which changed frequency as time progressed (e. g. “chirp” noise). Using a 7-level DWT the noise would appear at different times in the different frequency sub-bands (D1, D2, D3, D4, D5, D6, D7 and A7).

Jargon Alert: Stretching or shifting by powers of 2 is often referred to as “dyadic”. g. 2, 4, 8, 16 etc). * As is the discrete Fourier transform (implemented by the FFT algorithm). © 2006 Space & Signals Technologies LLC, All Rights Reserved. com 20 Conceptual Wavelets in Digital Signal Processing The undecimated discrete wavelet transform (we’ll explain why it’s called “undecimated” in a moment) is not as well known as the conventional discrete wavelet transform. However it is simpler to understand than the conventional DWT, compares better with the continuous wavelet transform we have just studied and is similar enough to the DWT to provide a clear learning “bridge”.

As will be explained further in later chapters, the Biorthogonal 7/9 filters have 7 points in H and L’ and 9 points in H’ and L. 4” © 2006 Space & Signals Technologies LLC, All Rights Reserved. 9–4 JPEG image compression of 91:1 achieved with a conventional DWT using a Biorthogonal 9/7 set of symmetrical wavelets. 10 Summary In this preview chapter we introduced wavelets by drawing them as continuous functions, but told how they are actually implemented in a digital computer as discrete, short wavelet filters.

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