New Data Compression Process:

For GRI (2011)

The team collaborated and developed the use of a new type of dimensionality reduction and data compression for principal component analysis. They have developed a process to shift the computational burden to a base-station decoder. This process is called compressive-projection Principal Component Analysis or CPPCA. CPPCA dramatically departs from traditional PCA because it allows its dimensionality-reduction and compression performance to be realized with a system that puts computational burden on the decoder. Continued development of the process could help the conservation, protection, utilization and enhancement of natural resources in the rural South.

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