Eigen-based method for covariance data compression
US7574057B1 · kind B1 · utility
Assignee
Inventor
Key dates
| Filing date | Mar 23, 2005 |
| Grant date | Aug 11, 2009 |
| Priority date | — |
| Expiry date | Aug 24, 2027 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/2135
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An improved covariance matrix encoding scheme wherein a covariance matrix is described in terms of Euler angles and eigenvalues. A covariance matrix, P, is decomposed into its eigenvalues and eigenvectors. The eigenvalues and their corresponding eigenvectors are arranged starting with the smallest value, and the next two ordered such that, the eigenvector set comprises a right-handed coordinate system. Each eigenvalue is then encoded with a logarithmic or other compression scheme. Euler angles are calculated and angle is compressed and an offset is added to each angle. The covariance matrix is then reconstructed from the encoded values to test if the encoded matrix completely covers the original matrix. If necessary, a scale factor is applied to all reconstructed eigenvalues and the scaled versions are then re-encoded as described above. The scaling and re-encoding process ensures that the encoded matrix covers the original matrix.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.