Abstract
This brief chapter serves as a bridge between the iterated function systems (IFS) in Chapter 4 and the more detailed wavelet analysis in Chapters 7 and 8. We wish to examine a variation of scale, i.e., examine the effect on the Perron-Frobenius-Ruelle theory induced by a change of scale in a wavelet basis. After stating a general result (Theorem 6.1.1), we take a closer look at a single example: Recall that Haar’s wavelet is dyadic, i.e., it is a wavelet basis for L2 (ℝ) which arises from the operations of translation by the integers ℤ, and by scaling with all powers of two, i.e., scaling by 2j, as j ranges over ℤ. But the process begins with the unit box function, say supported in the interval from x=0 to x=1. The scaling by 3, i.e., f→f(x/3), stretches the support to the interval [0, 3]. It is natural to ask what happens to an ONB dyadic wavelet under scaling by 3, i.e., f→f(x/3). This is related to over-sampling: The simplest instance of this is the following scaling of the low-pass filter m0(x), i.e., m0(x)→m0(3x).
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© 2006 Springer Science+Business Media, LLC
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(2006). The minimal eigenfunction. In: Analysis and Probability Wavelets, Signals, Fractals. Graduate Texts in Mathematics, vol 234. Springer, New York, NY. https://doi.org/10.1007/978-0-387-33082-2_6
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DOI: https://doi.org/10.1007/978-0-387-33082-2_6
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-29519-0
Online ISBN: 978-0-387-33082-2
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