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Wavelet Based Representations for a Class of Self Similar Signals with Application to Fractal Modula Information Theory, IEEE Tr

Wavelet Based Representations for a Class of Self Similar Signals with Application to Fractal Modula Information Theory, IEEE Tr

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[Music] welcome back so today I'm really excited to tell you about wavelets which you can think of as kind of a supercharged Fourier transform okay so we've already seen how you can take the Fourier transform and decompose a signal into a sum of sines and cosines into its frequency content and we've shown that those sines and cosines form an orthogonal basis for the space of functions that you want to represent and here in this wavelets lecture we're gonna see that you can generalize that idea of sines and cosines providing an orthogonal basis to other functions orthogonal functions that might provide better representation of certain types of functions so we're going to use wavelets a lot for things like image and audio compression and really wavelets has changed how we how we compress and represent signals in the digital era okay so I'm gonna start off by talking about kind of how we think of time series Fourier transforms and the spectr

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