Low storage space for compressive sensing: semi-tensor product approach
نویسندگان
چکیده
منابع مشابه
Low storage space for compressive sensing: semi-tensor product approach
Random measurement matrices play a critical role in successful recovery with the compressive sensing (CS) framework. However, due to its randomly generated elements, these matrices require massive amounts of storage space to implement a random matrix in CS applications. To effectively reduce the storage space of the random measurement matrix for CS, we propose a random sampling approach for the...
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ژورنال
عنوان ژورنال: EURASIP Journal on Image and Video Processing
سال: 2017
ISSN: 1687-5281
DOI: 10.1186/s13640-017-0199-9