Seafloor CO2 sequestration in the form of gas hydrates offers expansive geological opportunities for carbon neutrality strategies. Guided by phase equilibrium conditions, this study employs a self-developed multi-phys...
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Computational experiments have emerged as a valuable method for studying complex systems, involving the algorithmization of counterfactuals. However, accurately representing real social systems in Agent-based Modeling...
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In order to obtain high resolution inverse synthetic aperture radar (ISAR) sparse images, a block sparse signal recovery ISAR imaging algorithm is proposed by considering the cluster characteristics of target in this ...
In order to obtain high resolution inverse synthetic aperture radar (ISAR) sparse images, a block sparse signal recovery ISAR imaging algorithm is proposed by considering the cluster characteristics of target in this paper. Firstly, the ISAR sparse imaging model is established, the imaging is converted to L0 norm optimization problem. Secondly, one negative exponential function sequence is used as smoothed function to approach the block L0 norm. Finally, the revised step is added to ensure solving the optimization problem along the steepest descent gradient direction and the cost function is updated for the next loop. Simulation results verify the proposed algorithm is effective.
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