ZHU Hongyan, ZHAI Qiaozhu. A Global Optimal Gaussian Mixture Reduction Approach Based on Integer Linear Programming[J]. Chinese Journal of Electronics, 2013, 22(4): 763-768.
Citation: ZHU Hongyan, ZHAI Qiaozhu. A Global Optimal Gaussian Mixture Reduction Approach Based on Integer Linear Programming[J]. Chinese Journal of Electronics, 2013, 22(4): 763-768.

A Global Optimal Gaussian Mixture Reduction Approach Based on Integer Linear Programming

Funds:  This work is supported by the National Natural Science Foundation of China (No.61203220, No.61174146), the Program for New Century Talents of Education Ministry (No.NCET-08-0432), and the Foundation for Authors of National Outstanding Doctoral Dissertation (No.201047).
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  • Corresponding author: ZHU Hongyan, ZHAI Qiaozhu
  • Received Date: 2012-09-01
  • Rev Recd Date: 2013-01-01
  • Publish Date: 2013-09-25
  • In many applications, the Gaussian mixture serves as an important probabilistic representation of the system state. A global optimal Gaussian mixture reduction (GMR) approach based on Integer linear programming (ILP) is developed in this paper. Firstly, a Gaussian base set is constructed with partial merging of components of the original mixture. Secondly, by introducing auxiliary variables reasonably, the original problem of selecting the best candidates from the given Gaussian base set is formulated as an ILP problem. Finally, a global optimal solution to GMR is obtained by solving the ILP problem. The global optimum property enables it as a basis for performance comparison with different GMR algorithms.
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