| 21. | The discrete wavelet transform has become a very useful tool for fusion.
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| 22. | Figure 3 : FIR-based approximation of Mathieu wavelets.
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| 23. | Waves and wavelets are hosted by the wave provider of the creator.
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| 24. | Wavelets in the same wave can be hosted by different wave providers.
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| 25. | It also validates the operations before applying them to a local wavelet.
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| 26. | Choice of wavelet may depend on characteristics of the signal being investigated.
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| 27. | To get smooth value approximation, diffusion wavelets are used.
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| 28. | A wavelet tree contains a bitmap representation of a string.
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| 29. | Wavelet analysis is extended for multidimensional signal processing as well.
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| 30. | In the wavelet transformation, the probabilities are also passed through the hierarchy.
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