Method and apparatus for signal detection, classification and estimation from compressive measurements
US8483492B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 25, 2006 |
| Grant date | Jul 9, 2013 |
| Priority date | — |
| Expiry date | Oct 8, 2030 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/52
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
The recently introduced theory of Compressive Sensing (CS) enables a new method for signal recovery from incomplete information (a reduced set of “compressive” linear measurements), based on the assumption that the signal is sparse in some dictionary. Such compressive measurement schemes are desirable in practice for reducing the costs of signal acquisition, storage, and processing. However, the current CS framework considers only a certain task (signal recovery) and only in a certain model setting (sparsity).We show that compressive measurements are in fact information scalable, allowing one to answer a broad spectrum of questions about a signal when provided only with a reduced set of compressive measurements. These questions range from complete signal recovery at one extreme down to a simple binary detection decision at the other. (Questions in between include, for example, estimation and classification.) We provide techniques such as a “compressive matched filter” for answering several of these questions given the available measurements, often without needing to first reconstruct the signal. In many cases, these techniques can succeed with far fewer measurements than would be r…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.