Exact(1)
Simulation results show that LMBP has more fast convergence and it is suitable for system identification and controller design.
Similar(59)
KT has gained more popularity for its fast convergence speed and low computation requirement, and thus can achieve real-time tracking.
These drawbacks make maximum likelihood (ML -based approaches, e.g., [15, 16] ML -basedapproaches to the.g.fast convergence despite having the higher computational cost.
A structured loss function defined over positive pairs and hard negatives is proposed to formulate a novel optimization problem so that fast convergence and more stable optimized solution can be attained.
As we will see in Section 3 this discretization scheme leads to the fast convergence with more accurate results in solving the original system (1.2) with integer-order derivative one.
These results show that ALC-PSODE is more robust and efficient while keeping fast convergence.
This guess enables the algorithm to reach more refined solution iteratively by ensuring fast convergence.
Compared with DD, the ADMM-based method is known for its fast convergence rate and more robustness against network dynamic and system parameters[22].
The simulation results show that the most efficient bandwidth saving and optical resource allocation can be achieved with INLP, while the proposed adaptive GA nearly has the same performance with low computational complexity and fast convergence, which is more applicable for the large-scale fronthaul network.
Given the choice of two infinite series for, mathematicians will generally use the one that converges more rapidly because faster convergence reduces the amount of computation needed to calculate to any given accuracy.
It may be due to the fast convergence of K-cluster-valued CoSaMP caused by more accurate recovery result at each iteration.
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