Lim Teck Por, Puthusserypady Sadasivan
Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117576 Singapore.
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Aug;72(2 Pt 2):027204. doi: 10.1103/PhysRevE.72.027204. Epub 2005 Aug 24.
One problem when using the global false nearest-neighbors (GFNN) method and Cao's method to estimate embedding dimension is that their effectiveness is affected by the ratio of signal power to noise power (SNR). Simple models are proposed to explain the curves commonly obtained when using the GFNN method and Cao's method. Methods are proposed for systematically estimating the embedding dimension. Prior information is incorporated to improve the estimates.
使用全局伪近邻（GFNN）方法和曹的方法来估计嵌入维数时存在的一个问题是，它们的有效性会受到信号功率与噪声功率之比（SNR）的影响。提出了简单模型来解释使用GFNN方法和曹的方法时通常得到的曲线。提出了系统估计嵌入维数的方法。纳入先验信息以改进估计。
