Version 4.7 (R2011a) Wavelet Toolbox Software

This table summarizes what is new in Version 4.7 (R2011a):

New Features and Changes	Version Compatibility Considerations	Fixed Bugs and Known Problems
Yes	No	Bug Reports Includes fixes

New features introduced in this version:

• Inverse Continuous Wavelet Transform

• FFT-based Continuous Wavelet Transform

• Pattern-adapted Wavelets for Signal Detection Demo

Inverse Continuous Wavelet Transform

In R2011a, you can compute the inverse continuous wavelet transform (CWT) using an FFT-based algorithm. The inverse CWT allows you to synthesize approximations to your 1D signal based on selected scales. The inverse CWT is only supported for coefficients obtained using the FFT-based CWT. See icwtft and cwtft for details.

FFT-based Continuous Wavelet Transform

In R2011a, you can compute the continuous wavelet transform (CWT) using an FFT-based algorithm with cwtft. The CWT computed using an FFT algorithm supports the computation of the inverse CWT. See cwtft and icwtft for details. Only select wavelets are valid for use with cwtft. See cwtftinfo for a list of supported wavelets.

Pattern-adapted Wavelets for Signal Detection Demo

In R2011a there is a new demo using pattern adapted wavelets for signal detection. You can view this demo here Pattern adapted wavelets for signal detection. The Wavelet Toolbox software enables you to design admissible wavelets based on the pattern you wish to detect. Designing a valid wavelet based on your desired pattern allows you to exploit the optimality of matched filtering in the framework of the CWT. The demo illustrates this process on simulated data and human EEG recordings.

Version 4.8 (R2011b) Wavelet Toolbox Software

Version 4.6 (R2010b) Wavelet Toolbox Software

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