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Edition Date:
June 2001
Part Number:
322142B-01
The Signal Processing Toolset User Manual is divided into six sections and
is organized as follows:
Part I—Introduction
• Chapter 1, Signal Processing Toolset Overview, provides an overview
of the Signal Processing Toolset, its components, and installation
instructions.
• Chapter 2, Analysis Beyond FFT, provides basic information about
signal processing, Fourier transform, Gabor expansion, Wigner-Ville
Distribution, wavelet transform, time-frequency transform, and the
role of the Signal Processing Toolset in signal analysis.
Part II—Joint Time-Frequency Analysis
• Chapter 3, Joint Time-Frequency Analysis, explains the need for and
approaches to joint time-frequency analysis (JTFA).
• Chapter 4, Joint Time-Frequency Analysis Algorithms, describes the
algorithms the JTFA virtual instruments (VIs) use. The JTFA
algorithms implemented in this toolset fall into the following two
categories: linear and quadratic.
• Chapter 5, Joint Time-Frequency Analysis Applications, describes the
Online and Off-line JTFA examples included with the Signal
Processing Toolset. These examples are designed to help you learn
more about JTFA.
Part III—Super-Resolution Spectral Analysis
• Chapter 6, Introduction to Model-Based Frequency Analysis,
introduces the basic concepts of model-based frequency analysis.
• Chapter 7, Model-Based Frequency Analysis Algorithms, outlines
the theoretical background of model-based frequency analysis and
describes the relationship among the model coefficients, power
spectra, and parameters of damped sinusoids.
• Chapter 8, Applying Super-Resolution Spectral Analysis and
Parameter Estimation, describes a super-resolution spectral analysis
example application included with the Signal Processing Toolset. This
example is designed to help you learn about model-based analysis.
Part IV—Wavelet Analysis
• Chapter 9, The Fundamentals of Wavelet Analysis, describes the
history of wavelet analysis, compares Fourier transform and wavelet
analysis, and describes some applications of wavelet analysis.
• Chapter 10, Wavelet Analysis by Discrete Filter Banks, describes the
design of two-channel perfect reconstruction filter banks and defines
the types of filter banks used with wavelet analysis.
• Chapter 11, Wavelet Analysis Applications, describes the 1D and 2D
Wavelet Transform examples included with the Signal Processing
Toolset. These examples are designed to help you learn about wavelet
analysis.
Part V—Digital Filter Design Application
• Chapter 12, Digital Filter Design Application, describes the digital
filter design (DFD) application used to design infinite impulse
response (IIR) and finite impulse response (FIR) digital filters.
• Chapter 13, IIR and FIR Implementation, describes the filter
implementation equations for IIR and FIR filtering and the format of
the IIR and FIR filter coefficient files.
Part VI—Signal Processing for LabWindows/CVI
• Chapter 14, Joint Time-Frequency Analysis for LabWindows/CVI,
describes functions used to perform JTFA analysis in
LabWindows/CVI.
• Chapter 15, Super-Resolution Spectral Analysis for LabWindows/CVI,
describes functions used to perform super-resolution spectral analysis
and parameter estimation in LabWindows/CVI.
• Chapter 16, Wavelet Analysis for LabWindows/CVI, describes
functions used to perform wavelet analysis in LabWindows/CVI.
• Chapter 17, Using Your Coefficient Designs with DFD Utilities,
describes the DFD utilities used for filtering applications in
LabWindows/CVI.
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