Manifold learning attempts to obtain the intrinsic structure of non-linearly distributed data, which can be used in non-linear dimensionality reduction(NLDR).
流形学习旨在获得非线性分布数据的内在结构，可以用于非线性降维。
2
Among them, the most complex one is the signal transduction. These paths are organized non-linearly, and they can form a network through a series of protein interactions.
信号转导通路是非线性排列的，许多信号转导通路可以通过一系列的蛋白质与蛋白质相互作用形成一个网络。
3
At last an initial-boundary value problem was considered and the numerical experiment demonstrated that the linear sinusoidal wave would successively evolve non-linearly into conoidal wave.