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| R2012a Documentation → Wavelet Toolbox | |
Learn more about Wavelet Toolbox |
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| Contents | Index |
New Features and Changes | Version Compatibility Considerations | Fixed Bugs and Known Problems |
|---|---|---|
Yes | Yes — Details labeled as Compatibility
Considerations below. See also | Bug
Reports |
New features introduced in this version:
MATLAB Code Generation Support for Denoising and Compression GUIs
Signal Reconstruction from Continuous Wavelet Transform Coefficients Demo
In R2011b, you can compute the Fourier transform based continuous wavelet transform (CWT) and inverse CWT using the Wavelet Toolbox graphical user interface wavemenu. To access these graphical tools, enter wavemenu at the command line, and select Continuous Wavelet 1-D (using FFT).
In R2011b, you can compute the inverse continuous wavelet transform (CWT) for a wider class of analyzing wavelets using icwtlin. icwtlin returns the inverse for CWT coefficients obtained at linearly spaced scales. icwtlin supports the output of cwtft and the output of cwt for a select number of wavelets. See icwtlin for detailed information.
In R2011b, you can generate MATLAB code for 1-D and 2-D discrete wavelet transforms (DWT), stationary wavelet transforms (SWT), and wavelet packet transforms. You can denoise or compress a signal or image in the GUI and export the MATLAB code to implement that operation at the command line. This approach allows you to set denoising thresholds or compression ratios aided by visualization tools and save the commands to reproduce those operations at the command line. See Generating MATLAB Code from Wavelet Toolbox GUI for examples.
R2011b includes a new demo illustrating signal reconstruction using the continuous wavelet transform (CWT). The demo emphasizes the use of the CWT to analyze a signal and reconstruct a time- and scale-based approximation with select coefficients using the inverse CWT. See Signal Reconstruction from Continuous Wavelet Transform Coefficients for details.
In R2011b, the default values for the smallest scale, scale increment, and number of scales have changed in cwtft for the derivative of Gaussian (DOG) and Paul wavelets. The change in the defaults also affects the Mexican hat wavelet, which is a special case of the DOG wavelet. In R2011b, the default value of the smallest scale for the Paul and DOG wavelets is 2*dt, where dt is the sampling period. The default scale increment, ds, is 0.4875. The default number of scales is fix(log2(length(sig))/ds)+1 for the Paul wavelet and max([fix(log2(length(sig))/ds),1]) for the DOG wavelets, where sig is the input signal.
cwtft was introduced in R2011a. In that release, the default smallest scales for the DOG and Paul wavelets are dt/8 and dt respectively, where dt is the sampling interval. The default scale increment is 0.5. The default number of scales is fix(1.5*log2(length(sig))/ds)+1 for the Paul wavelet. For DOG wavelets, the default number of scales is fix(1.25*log2(length(sig))/ds)+1, where sig is the input signal. You can obtain results in R2011b using cwtft with the DOG and Paul wavelets identical to results in R2011a with the default values. To do so, specify the smallest scale, scale increment, and number of scales in a structure or cell array. See cwtft for details.
 | Version 4.9 (R2012a) Wavelet Toolbox Software | Version 4.7 (R2011a) Wavelet Toolbox Software |  |
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