Download Wavelet Analysis Tools User Manual

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Introduction to
Wavelet Signal Processing
Wavelets are functions that you can use to decompose signals, similar to
how you use complex sinusoids in the Fourier transform to decompose
signals. The wavelet transform computes the inner products of the analyzed
signal and a family of wavelets.
In contrast with sinusoids, wavelets are localized in both the time and
frequency domains, so wavelet signal processing is suitable for
nonstationary signals, whose spectral content changes over time. The
adaptive time-frequency resolution of wavelet signal processing enables
you to perform multiresolution analysis on nonstationary signals. The
properties of wavelets and the flexibility to select wavelets make wavelet
signal processing a beneficial tool for feature extraction applications.
Refer to the Benefits of Wavelet Signal Processing section of Chapter 2,
Understanding Wavelet Signal Processing, for information about the
benefits of wavelet signal processing.
This chapter describes the application areas of wavelet signal processing
and provides an overview of the LabVIEW Wavelet Analysis Tools.
Wavelet Signal Processing Application Areas
You can use wavelets in a variety of signal processing applications, such as
analyzing signals at different scales, reducing noise, compressing data, and
extracting features of signals. This section discusses these application areas
by analyzing signals and images with the Wavelet Analysis Tools.
The Wavelet Analysis Tools provide example VIs for each application area.
In the Browse tab of the NI Example Finder, you can view these example
VIs by selecting Toolkits and Modules»Wavelet Analysis»
Applications. Refer to the Finding Example VIs section of this chapter for
information about launching the NI Example Finder.
© National Instruments Corporation
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Wavelet Analysis Tools User Manual