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Learn how to visualize a TQWT decomposition using Signal Multiresolution Analyzer.

Use wavelets to analyze financial data.

Signals with very rapid evolutions such as transient signals in dynamic systems may undergo abrupt changes such as a jump, or a sharp change in the first or second derivative. Fourier analysis is usually not able to detect those events. The purpose of this example is to show how analysis by wavelets can detect the exact instant when a signal changes and also the type (a rupture of the signal, or an abrupt change in its first or second derivative) and amplitude of the change. In image processing, one of the major applications is edge detection, which also involves detecting abrupt changes.

Use wavelets to analyze physiologic signals.

Learn the advantages the dual-tree complex wavelet transform provides over the critically sampled discrete wavelet transform.