Subspace-constrained partial update method for high-dimensional adaptive processing systems
US9928212B2 · kind B2 · utility
Inventor
Key dates
| Filing date | Nov 1, 2014 |
| Grant date | Mar 27, 2018 |
| Priority date | — |
| Expiry date | Oct 8, 2035 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH03H2021/0072
- WIPO fieldBasic communication processes
- WIPO sectorElectrical engineering
Abstract
A method is explained for any adaptive processor processing digital signals by adjusting signal weights on digital signal(s) it handles, to optimize adaptation criteria responsive to a functional purpose or externalities (transient, temporary, situational, and even permanent) of that processor. Adaptation criteria for the adaptive algorithm may be any combination of a signal or parameter estimation, and measured quality(ies). This method performs a linear transformation adapting parameters from M to (M1+L) dimensions in each adaptation event, such that M1 weights are updated without constraints and M0=M−M1 weights are forced by soft constraints into an L-dimensional subspace they spanned at the beginning of the adaptation period. The same dimensionality reduction, using the same linear transformation, is applied to the input data. The reduced-dimensionality weights are then adapted using the identical optimization strategy employed by the processor, except with input data that has also been reduced in dimensionality.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.