The CRP method can be effective in balancing the sparsity of sampled vectors in DCT domain of image, and then in improving the CS sampling efficiency.
For example, the recently proposed framework of Compressed Sensing (CS), a state-of-the-art signal sampling and compression scheme, was investigated for WSN data acquisition and aggregation [13, 14] exploiting the sparsity of the sampled data when expressed in an appropriate basis [15].
In this paper, we have analyzed the signal characteristics in multi-static passive radar SAR and depicted the block sparsity of the sampling support in the wavenumber domain.
55 The relative sparsity of blood sampling for pharmacokinetic assessment during telemetry experiments can prove difficult when trying to build a robust pharmacokinetic model.
It must be noted that this situation (sample clustering and relevant gene extraction) is difficult mainly due to three reasons [ 1]: the sparsity of the data (samples), the high dimensionality of the feature (gene) space, and the fact that many features are irrelevant or redundant (low signal-to-noise ratio).
However, due to the sparsity of labeled font samples and the structural complexity of Chinese characters, CFR is still a challenging task.
We first demonstrate the block sparsity of the Fourier domain samples in a multi-static passive SAR.
ωAPD p) estimates the local sampling sparsity of the scanned surface at p. High values of ωAPD characterize those points having a neighbourhood sparsely sampled, typical of corner and edge points and regions scanned with low incident angle, which are likely located in the overlapping area of the models.
We prove a quantitative-bound of errors in known part that relates with the number of samples and the sparsity of original vector.
When the location of sparsity is not known, by the law of algebra, the number of samples needed to specify the sparsity is at least twice the number of sparse coefficients.
