Adaptive prediction using a dimensionality reduction process
View Patent ↗Multi-field taps are defined based on a decimated field. The multi-field taps are used to generate correlation matrices, the elements of which are used to generate covariance matrices. A principal component space is obtained by projecting the correlation matrix elements on to eigenvectors. The principal component space is partitioned into classes and a least square filter set is generated for each class.
1. A computerized method comprising:
defining multi-field taps based on a decimated field;
generating correlation matrixes and correlation matrix elements using the multi-field taps;
generating covariance matrixes based on the correlation matrix elements;
projecting the correlation matrix elements onto eigenvectors to obtain a principal component space;
partitioning the principal component space into classes; and
generating a least square filter set for each of the classes.
2. The computerized method of claim 1 , further comprising:
decimating an original high resolution field to produce a decimated field.
3. The computerized method of claim 2 , further comprising:
reconstructing the original high resolution field for display on a display device.
4. A non-transitory computer-readable storage medium storing instructions which when executed by a data processing system cause the data processing system to perform operations that process data, the operations comprising:
defining multi-field taps based on a decimated field;
generating correlation matrixes and correlation matrix elements using the multi-field taps;
generating covariance matrixes based on the correlation matrix elements;
projecting the correlation matrix elements onto eigenvectors to obtain a principal component space;
partitioning the principal component space into classes; and
generating a least square filter for each of the classes.
5. The computer-readable storage medium of claim 4 , the method further comprising:
decimating an original high resolution field to produce a decimated field.
6. The computer-readable storage medium of claim 5 , the method further comprising:
reconstructing the original high resolution field for display on a display device.
7. A system comprising:
a processor coupled to a bus;
a memory coupled to the processor through the bus; and
instructions executed by the processor from the memory to cause the processor to
define multi-field taps based on a decimated field;
generating correlation matrixes and correlation matrix elements using the multi-field taps;
generate covariance matrixes based on the correlation matrix elements;
project the correlation matrix elements onto eigenvectors to obtain a principal component space;
partition the principal component space into classes; and
generate a least square filter for each of the classes.
8. The system of claim 7 , the instructions further comprising:
decimate an original high resolution field to produce a decimated field.
9. The system of claim 8 , the instructions further comprising:
reconstruct the original high resolution field for display on a display device.
10. A data processing system comprising:
means for defining multi-field taps based on a decimated field;
means for generating correlation matrixes and correlation matrix elements using the multi-field taps;
means for generating covariance matrixes based on the correlation matrix elements;
means for projecting the correlation matrix elements onto eigenvectors to obtain a principal component space;
means for partitioning the principal component space into classes; and
means for generating a least square filter for each of the classes.