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The innovative concept of Compressed Sensing (CS) presents a breakthrough that enables the acquisition of sparse signals at much lower sampling rates compared to the conventional Nyquist rate. The scope of CS is not limited only to sparse signal but it is also applicable to compressible signals, such as multimedia signals including audio signals. Representing the random samples from CS process using...
Compressed Sensing (CS) has been widely used for multimedia processing to reduce the number of the measurements required to acquire signals that are spare or compressible sparse in some basis. CS provides good quality of the restored signal even when the signal is not completely sparse and even also at high compression ratio. However, classical CS assumes that the measurements are real-valued and...
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