Abstract
To recognize circular boundaries, a mixed probability density function that can generate the circular spatial point pattern is built up. In terms of the above, the probability density function, a circular boundaries recognition method is constructed, It consists of three parts:viz.:denoising; estimating the parameters of mixed probability density function, and identifying the number of clusters via BIC. The new method overcomes the limitation of fuzzy C-shell clustering. simulation study provided some promising results.
| Original language | English |
|---|---|
| Pages (from-to) | 843-846 |
| Number of pages | 4 |
| Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
| Volume | 28 |
| Issue number | 9 |
| Publication status | Published - Sept 2008 |
Keywords
- Circular boundaries
- Classification expectation maximization method
- Mixed probability model
- Pattern recognition
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Zhao, X., & Cui, L. R. (2008). Model-based recognition method for circular boundaries. Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology, 28(9), 843-846.