Adaptive prediction using a dimensionality reduction process
AssigneesSony Corporation, Sony Electronics Inc.
InventorsOguz Demirci, Marco Paniconi
Life of this patent
Estimating the term…
Abstract
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.
Claims10
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.
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.
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.
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.
Dependencies are inferred from the claim text.