aim to study how to identify determinant dy-namics in neurons spiking series. methods determinant dynamics in neurons spiking series was researched by using unstable periodic orbits, correlation dimension and nonlinear prediction. results when the determinant statistics is in-effetive, the orbital structures of periodⅰ, periodⅱand pe-riodⅲcould be recognized by using unstable periodic orbits. conclusion compared with determinant statistics, unstable periodic orbits is more suitable for the analysis of chaotic time series with high dimension.
目的 研究如何识别神经元阵发放电序列中的确定性动力学。方法运用不稳定周期轨道及关联分维、非线性预报对神经元阵发放电序列中的确定性动力学进行了研究。结果在确定性统计方法失效的情况下，不稳定周期轨道方法依然能可靠的辨别出放电序列的周期ⅰ，周期ⅱ，周期ⅲ轨道结构。结论与确定性统计方法比较，不稳定周期轨道更适合于对高维动力系统的混沌时间序列进行分析。
A correlation between early embryonic waste and higher CD80 proportion at the fetomaternal interface suggests that CD80 + cells may be an important determinant in recurrent peri-implantation abortion.
早期A丕胎吸收与较高的CD80~+细胞检出率相关，提示CD80~+细胞可能是围着床期反复流产的重？
When classifying the hyper-spectral remote sensing images using the max-likelihood classifier, the determinant of spectra's cov-matrix is singular approximately and an unreasonable result comes out because of the big number of the bands and the close correlation between them.
利用最大似然分类器对高光谱遥感图像分类时，由于波段数目多、波段间的相关度大，使协方差矩阵的行列式近似于奇异，因而导致了不合理的分类结果。