Towards compressive information processing systems (CRISP)
Towards compressive information processing systems
Start date: Nov 1, 2011,
End date: Jun 30, 2017
This proposal targets the emerging frontier research field of compressive sampling (CS), and particularly its application in the framework of complex information processing systems, including several related innovative and unconventional aspects. Future systems will have to handle unprecedented amounts of information such as those generated in multiview video, medical and hyperspectral imaging applications, increasingly suffering from limited communication and computational resources. CS is a breakthrough technology that will have a profound impact on how these systems are conceived. It offers a viable and elegant solution, acquiring and representing an information signal through a small set of linear projections of it, allowing to dramatically reduce communication, storage and processing requirements, and is one of the topics that will dominate signal processing research in the next years. At the core of this research proposal is the concept of employing CS not only as a standalone tool, but inside an information processing system. The main challenge is to develop theory and algorithms that will allow to perform all signal manipulations typical of conventional systems directly on the linear measurements, as reconstructing the signal samples would be unfeasible due to excessive complexity. Such operations include compression, encryption, communication, reconstruction, signal analysis, information extraction and decision, and distributed signal processing, leading to a very multidisciplinary and technically challenging research agenda. Ultimately, our research aims at developing and demonstrating the fundamental tools that will fuel next-generation information processing systems with an order-of-magnitude better performance at a lower cost than today. Europe has several successful industries active in communications and signal processing. The future success of these sectors critically depends on the ability to innovate and integrate new technology.
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