Sentence examples for decent algorithm from inspiring English sources

In Section 4, we propose a measurement matrix design for 1D and 2D CS model using gradient decent algorithm.

This approach, however, basically leads to first-order results as the LMS algorithm then behaves similarly to the steepest decent algorithm.

In this paper, we introduce a 2D signal model in CS for a collocated MIMO radar with point targets, and then we improve the efficiency of this 2D MIMO radar model by proposing a measurement matrix design using gradient decent algorithm (MMDGD) in which the MC of sensing matrix is minimized.

The simulation results show that our proposed 2D measurement matrix design using gradient decent algorithm (2D-MMDGD) has much lower computational complexity compared to one-dimensional (1D) methods while having better performance in comparison with conventional methods such as Gaussian random measurement matrix.

For this dataset, the initialized estimates give high accuracy until SNR decreases below −12 dB, which also leads to failure of the coordinate decent algorithm for fine translational motion correction subsequently as we mentioned before, because the relationship between focusing quality and image entropy is inconsistent when very strong noise is involved into the data.

Step 1 can be done by using the coordinate decent algorithm.

By this, coordinate decent algorithms have monotone convergence in the objective function and trend to have the ability of achieving the global optimization [19].

The systems were minimized with the steepest-decent algorithm followed by the adopted basis Newton−Raphson (ABNR) method, gradually decreasing the harmonic force restraints to zero.

After finding the derivative, we initialize A=(S+ λ I −1, and then use the standard decent gradient algorithm to update each row/column repeatedly until the algorithm converges.

In addition, GVQ and GSAVQ need a little longer CPU time than, the maximum decent (MD) algorithm, but they outperform MD by 0.2 0.5 dB in PSNR.

To take advantage of this implication, Fu and Zhou (2013) proposed a blockwise coordinate decent (BCD) algorithm where the p(p−1) parameters are partitioned in to p(p−1)/2 blocks.