Sentence examples for most compact representation from inspiring English sources
Friedman, Steven J. / Supowit, Kenneth J. some applications, such as Differential Cascode Voltage Switch (DCVS) trees, it becomes extremely important to find the ordering leading to the most compact representation.
In turn, perhaps the most compact representation of a given statistical distribution is via the mean-variance approach: the mean manifesting the distribution's 'typical' value, and the variance manifesting the magnitude of the distribution's fluctuations about its mean.
The second part of the system is a JPEG encoder, which adapts the JPEG encoding process to the original photos, creating the most compact representation of the photos that is possible under the JPEG standard.
The main idea behind sparse signal representation is, to find the most compact representation of a signal as a linear combination of a few elements (or atoms), in an over-complete dictionary [15 18].
In 1999, Kolpakov and Kucherov presented an O (n ) -time algorithm to compute the most compact representation of all repetitions known as runs[ 2].
For future work, we intend on devising an algorithm to compute a most compact representation of all maximal repetitions in weighted strings similar to the one for regular strings [ 2].
Mathematical models provide the most compact and informative representation of a hypothesis of how a cell works.
To effectively incorporate the DSRF descriptors in the skeletal representation, a skeleton is decomposed into five parts and the most informative part method is raised for offering compact representation.
1-sequence numerical representation (with R = 1) is the most compact form of mapping in which one nucleotide is mapped to one fixed numerical value to form a single sequence.
An audio fingerprint is a compact representation of an audio signal that extracts the most meaningful information of an audio excerpt.
Such compact representation not only provides better signal compression for bandwidth/storage efficiency, but since it focuses on the most intrinsic property of the data, it also leads to faster processing algorithms and more effective signal separation for detection, classification, and recognition.
