Center for Discrete Mathematics and Theoretical Computer Science

About: Center for Discrete Mathematics and Theoretical Computer Science is a facility organization based out in Piscataway, New Jersey, United States. It is known for research contribution in the topics: Local search (optimization) & Optimization problem. The organization has 140 authors who have published 175 publications receiving 2345 citations.

Poissonian Hyperspectral Image Superresolution Using Alternating Direction Optimization

Abstract: The reconstruction of Poissonian image is an active research area in recent years. This paper proposes a novel method for Poissonian hyperspectral image superresolution by fusing a low-spatial-resolution hyperspectral image and a low-spectral-resolution multispectral image. The fusion scheme is designed as an optimization problem, whose cost function consists of the two data-fidelity terms about Poisson distribution, the sparse representation term, and the nonlocal regularization term. The two data-fidelity terms can capture statistical information of Poisson noise. The sparse representation term is used for enhancing the quality of sparsity-based signal reconstruction, and the nonlocal regularization term exploits the spatial similarity of hyperspectral image. As a result, the hyperspectral image and multispectral image are well fused. Finally, the designed optimization problem is effectively solved by an alternating direction optimization algorithm. Simulation results illustrate that the proposed method has a better performance than several well-known methods both in terms of quality indexes and reconstruction visual effect.

An Improved Simulated Annealing Algorithm With Excessive Length Penalty for Fixed-Outline Floorplanning

Abstract: In addition to wirelength and area, modern floorplans need to consider various constraints such as fixed-outline. To handle the fixed-outline floorplanning optimization problem efficiently, we propose an improved simulated annealing (SA) algorithm, which optimizes the area, the total wirelength, and the prescribed outline constraints at the same time. In order to enhance the effectiveness of SA algorithm, we propose a novel feasible solution strategy which ensures that viable solution would be found at all times. Moreover, we propose a new penalty function to better solve the prescribed outline constraint. It consists of a violation area function to prevent modules from moving to the prescribed outline, and an excessive violation function to enable the modules to move close to the optimal positions. Experimental results show that the proposed algorithm is effective and efficient to obtain a fixed-outline floorplan, and achieves a 100% success rate on each benchmark in different aspect ratios.

Spectral radius of r -uniform supertrees with perfect matchings

Abstract: supertree is a connected and acyclic hypergraph. The set of r-uniform supertrees with n vertices and the set of r-uniform supertrees with perfect matchings on rk vertices are denoted by Tn and Tr,k, respectively. H. Li, J. Shao, and L. Qi [J. Comb. Optim., 2016, 32(3): 741–764] proved that the hyperstar Sn,r attains uniquely the maximum spectral radius in Tn. Focusing on the spectral radius in Tr,k, this paper will give the maximum value in Tr,k and their corresponding supertree.