In Symmetry order, you can specify the number of fractal segments that are copied and rotated. This is set to a standard value of 8, but you can also select a lower value. You see the effects of lower values in figure 5.9:
For a given window size, the STFT has fixed frequency resolution but its temporal precision relative to period decreases with increasing frequency (Fig. 1a, right), i.e., as frequency increases, the size of an oscillation packet spanning a finite number of cycles is decreasing relative to the fixed analysis window size. This is especially problematic in the analysis of scale-free, fractal-like signals that contain oscillation bursts which are self-similar across frequencies. To overcome this limitation multiscale, also called multiresolution15,16 techniques have been introduced, like the continuous-wavelet transform (CWT). The CWT provides good relative temporal localization by compression/dilation of a mother wavelet as a function of frequency11,14. A popular wavelet for TF analysis is the Morlet17,18, defined as a plane wave multiplied by a Gaussian envelope (see Supplementary Fig. 1). The original Morlet wavelet contains two terms, the second being a normalization constant to render the wavelet admissible (i.e., to remove its mean)18. In practice, when the wavelet is wide enough, this constant becomes negligible, and one can define the modified Morlet (also called Gabor) wavelet, as:
Ultra Fractal 5 Serial Number
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A 3D reconstruction of a dendrite from a 15,625 μm (25 x 25 x 25 μm) volumetric data set containing 500 serial images of mouse cerebellum generated by the 3View system. Dendrite structure (green), buttons (yellow), and vesicles (red). Inset images, clockwise from top left: Confocal image of a dendrite; wire frame traces rendered into a volumetric model; ultra-resolution dendritic spine model with synapses; and image showing wire frame traces. 2ff7e9595c
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