This paper also develops a fuzzy competitive learning scheme for these new reference vector parameters, and applies the algorithm to the difficult task of clustering documents.
针对新的参考向量开发了模糊竞争学习模式，并用该算法成功地解决了文献聚类的难题。
Gauss-Newton error minimization is used to transform six-dimentional reference vector to quaternion as a part of observations for EKF, which significantly reduces the computational requirement.
用高斯-牛顿误差最小法将六维观测量转化为四元数，作为观测量的一部分，显著减少了直接使用EKF的计算量。
Gauss-Newton error minimization is used to transform six-dimentional reference vector to quaternion as a part of observations for EKF, which significantly reduces the computational requirement.
用高斯-牛顿误差最小法将六维观测量转化为四元数，作为观测量的一部分，显著减少了直接使用EKF的计算量。
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