Elliptical basis function network for classification of remote-sensing images
文献类型：EI期刊论文
| 作者 | Luo Jian-Cheng ; Ming Dong-Ping ; Shen Zhan-Feng ; Chen Qiu-Xiao ; Zheng Jiang |
| 发表日期 | 2005 |
| 英文摘要 | An elliptical basis function (EBF) network is proposed for the classification of remote-sensing images. Though they are similar in structure, the EBF network differs from the well-known radial basis function (RBF) network by incorporating full covariance matrices and uses the expectation-maximization (EM) algorithm to estimate the basis functions. Since remotely sensed data often take on mixture-density distributions in the feature space, the proposed network possesses the advantage of the RBF mechanism and utilizes the EM algorithm to compute the maximum likelihood estimates of the mean vectors and covariance matrices of a Gaussian mixture distribution in the training phase. Experimental results show that the EM-based EBF network is faster in training, more accurate, and simpler in structure. |
| 出处 | Shuju Caiji Yu Chuli/Journal of Data Acquisition and Processing
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| 卷 | 20期:1页:8-12 |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/24711]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Luo Jian-Cheng,Ming Dong-Ping,Shen Zhan-Feng,et al. Elliptical basis function network for classification of remote-sensing images. 2005. |
入库方式： OAI收割
来源：地理科学与资源研究所
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