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Sparsity is known to be very beneficial in blind source separation (BSS). Even if data is not sparse in its current domain, it can be modelled as sparse linear combinations of atoms of a chosen dictionary. The choice of dictionary that sparsifies the data is very important. In this paper the dictionary is partly pre-specified based on chirplet modelling of various kinds of real epileptic discharges,...
In blind source separation (BSS), sparsity is proved to be very advantageous. If data is not sparse in its current domain, it can be modelled as sparse linear combinations of elements of a chosen dictionary. The choice of dictionary that sparsifies the data is very important. In this paper the dictionary is pre-specified based on chirplet modelling of various kinds of real epileptic spikes. Dictionary...
A constrained blind source separation (BSS) approach for separation of intracranial spikes from scalp electroencephalogram (EEG) has been proposed in this paper. This method is based on creating a template from intracranial data, which is then used in the form of a constraint in a BSS algorithm. To generate a suitable template, the segments during which the brain discharges are labelled are used to...
Latent finger print matching is one of the freshest areas in science. The current methods of latent finger print matching are manual and reliable on human experience. Unfortunately, a system, which can perform the latent fingerprint matching automatically, does not exist. The eye tracking technology is able to record the eye movement and could provide useful information about the user search strategy...
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