“Wavelets are mathematical functions that cut up data into different frequency components, and then study each component with a resolution matched to its scale. They have advantages over traditional Fourier methods in analyzing physical situations where the signal contains discontinuities and sharp spikes.”
An excellent tutorial on Wavelet Analysis covering also the basic concepts of mathematical transformations, time-frequency representations and non-stationary signal properties.
By Robi Polikar
Dept. of Electrical and Computer Engineering
Rowan University
Wave_clus is a fast and unsupervised algorithm for spike detection and sorting. Although it gives a first unsupervised solution, this can be further modified according to the experimenter’s preference (semi-automatic sorting).
By Rodrigo Quian Quiroga,
Reader in Bioengineering,
Dept. Engineering. University of Leicester, UK.
BrainML is a developing initiative to provide a standard XML metaformat for exchanging neuroscience data. It focuses on layered definitions built over a common core in order to support community-driven extension.
One such extension is provided by the new NIH-supported neuroinformatics initiative of the Society for Neuroscience, which supports the development of expert-derived terminology sets for several areas of neuroscience.
The BrainML project is funded by the Human Brain Project-Informatics initiative via MH/NS57153 from the NIMH and NINDS and is directed by:
Daniel Gardner
Weill Medical College of Cornell University
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