Sentence examples for sparsity-based method from inspiring English sources

On the other hand, the two-step sequential method based on group sparsity is robust against such phase discrepancies because the performance of the group sparsity-based method does not directly depend on the coherent combination of the multiple Doppler signatures.

This is a local sparsity-based method that divides the whole image into blocks and represents each block sparsely using some trained dictionary Among other advantages, one major advantage of such a method is the ease to train a small dictionary as compared to one large global dictionary This is achieved with the help of (2) which is equivalent to (4).

Performance evaluation of the proposed sparsity-based methods is conducted using numerical simulations.

Simulation results indicate that we can get close to this bound by using proper sparsity-based methods.

Generally, there are two main categories of sparsity-based methods to solve the set of equations presented in (3).

In this section, we will study the sub-optimum pilot locations when greedy sparsity-based methods such as OMP and the introduced IMAT are employed.

Thus, if the sparsity-based methods succeed in estimating the support of the channel impulse response, the MSE will be improved by prevention of the leakage effect.

Therefore, such motion parameters act as a common sparse support to enable the exploitation of group sparsity-based methods for robust motion parameter estimation.

One of the well-known results demonstrates that the sparsity-based methods such as ℓ1 minimization and greedy methods, are guaranteed to perfectly recover the s-sparse vectors when μ Φ < 1 2 s [6].

Alternative methods include adaptive beamforming, which is closely related to independent component analysis when information-theoretic cost functions are applied [13], sparsity-based methods that utilize amplitude-delay histograms [6, 8, 14], or grouping cues typical of human stream segregation [15].

The main goal of sparsity-based methods for MIMO radar systems ([21 24]) is to achieve accurate estimates for target parameters, whereas in this paper, we mainly focus on the CS MIMO radar problem to reduce the sampling rate lower than the Nyquist criterion by designing a suitable measurement matrix.