A different approach to decentralized compression, compressed sensing for networked data, has been considered and revolves around large-scale distributed sources of data and their storage, transmission and retrieval. The new approach does not require any specific prior signal knowledge and is an effective strategy in each of the situations described above. It can be used to reconstruct compressible or sparse networked data in a variety of practical settings, including general multihop networks and wireless sensor networks. The reason that it is promising is that CS provides universal sampling and decentralized encoding.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Electrical and Electronic Engineering
- Applied Mathematics