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In this approach, the discrete time signals representing the gestural parameters extracted from dance movements are organized into a fixed-size multidimensional feature array forming the spatiotemporal template.
As will be explained in depth, the discrete time signals representing the gestural parameters extracted from dance movements are organized into a fixed-size multidimensional feature array forming the spatiotemporal template.
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Thus, UWB data detection is formulated as a pattern classification problem in a multidimensional feature space.
The training samples are audio feature vectors which are distributed in a multidimensional feature space.
There exist a myriad methods to partition our multidimensional feature space into several classification regions.
Instead, multiple variances are determined for different frequency ranges resulting in a multidimensional feature vector.
To detect speech based on the spectral shape, the multidimensional feature vectors are typically modeled using codebooks.
Array CGH was carried out as previously described [61] using a 385,000 feature array from NimbleGen.
Array CGH was carried out as previously described [24] using a 72,000 feature array (NimbleGen).
This feature array is called candidate feature array.
Frailty is a multidimensional feature that has been defined and described in many different ways.
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