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- W2078366808 abstract "One of the primary reasons for using the PSDF is the inherent data dimension reduction that is achieved through theuse of the projection-slice theorem, (PST). The use of the PST allows for a powerful technique to segmentinformational content into lower dimensional spans while simultaneously providing a complete and naturally linkeddata set. Shannon provides a formula for maximum information capacity in a channel that utilizes as the mostefficient informational coding independent data samples, as this spreads the spectrum evenly across the channelband. This implies that independent information that represent a correlated set contains maximal information if thekey that represents the correlated-ness of the data is known, otherwise the independent data are purely random.By using a novel Adaptive Grahm-Schmidt (AGS) procedure we form a method that identifies patterns in correlateddata for the removal of the inter-dependence and thereby maximization of information content per data sample. Inthis work we subject the lower-dimensional data sets in the PSDF to the AGS to maximize the information contentof the PSDF and share some of our findings, results, and deductions." @default.
- W2078366808 created "2016-06-24" @default.
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- W2078366808 date "2007-04-09" @default.
- W2078366808 modified "2023-09-23" @default.
- W2078366808 title "Adaptive Grahm-Schmidt orthogonalization for the projection-slice synthetic discriminant function filter" @default.
- W2078366808 doi "https://doi.org/10.1117/12.720891" @default.
- W2078366808 hasPublicationYear "2007" @default.
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