This menu allows you to compute the continuous wavelet transform of 1D signals. As said above, the Continuous Wavelet Transform sub-menu is almost exactly the same as the one that appears in the 1D Exponents Estimation and 1D Multifractal Spectra estimation menus. For convenience, we recall here its main features. Check your input signal and Refresh it if needed. You need then to tune the fmin and fmax values, which are the minimum and maximum frequencies of analysis. The default values are the ones yielding maximal span compatible with the size of the signal. You may change the extreme frequencies either by typing values under fmin and fmax, or by using the predefined values on the menus to the right. The Voices parameters governs the number of intermediate frequencies at which the continuous wavelet coefficients will be computed. Be warned that giving an excessive number of voices may result in large computing times for long signals. You may then decide if you want to use an L2 (the default) or an L1 normalization for your wavelet. This feature is the only one that is present in this menu and not in the continuous wavelet computations of other parts of Fraclab. Checking the Mirror item will deal the border effects by mirroring the signal at its extremities. Otherwise, zero-padding is used. Finally, you may choose the Size and Type of your analyzing wavelet: available wavelets are the Mexican Hat, and the real and analytic Morlet wavelets. The size may be any positive number (this parameter is not available for the Mexican hat). Once all the parameters that define the wavelet transform are chosen, hit Compute WT. The output signal is a matrix of size "number of voices" x "size of the original signal". It is called cwt_signal#, if "signal" is the name of your data, and where # is as usual an incremental parameter. You may visualize the continuous wavelet transform using the View menu. Note that Fraclab recognizes wavelet transforms, and display them differently form regular images. In particular, it uses a fixed aspect ratio (this is useful for instance if the number of voices is much smaller than the size of the signal), and the "jet" color-map, which often allows to highlight the important structures. If you want to view the transform as a normal image, or make other changes in the appearance, use the functionalities of the View menu described in the Overview help file.