A nonlinear partial differential equation model based on nonlocal information was proposed to remove noise and preserve the edges.
针对传统扩散模型中的边界模糊问题，提出一种基于非局部信息的非线性偏微分方程去噪模型。
To avoid multicollinearity's disturbance, partial least-squares regression which can identify system information and noise is introduced to model, and a program is compiled.
为了克服多重相关性对模型的干扰，引入了能辨别系统信息与噪声的偏最小二乘回归，并编制了程序。
Second, we add fringe restraint in the model of partial grey level, so that the points with stronger fringe information could have more possibility to become the perfect candidate points.
第二，我们在局部灰度模型中加入了边缘约束，使边缘信息较强的点有更大的可能成为最佳候选点。
To avoid multicollinearity's disturbance, partial least-squares regression which can identify system information and noise is introduced to model, and a novel seepage monitoring model is introduced.
为了克服多重相关性对模型的干扰，本文引入了能辨别系统信息与噪声的偏最小二乘回归，并提出了一种基于偏最小二乘回归原理的土石坝渗流监控模型。
The algorithm took transmission time vector between nodes as input, and a model was established by KLPP, which can reflect partial information network topology structure.
该算法以节点间的传输时间向量为输入，借助能够体现网络拓扑结构局部信息的核局部保持映射进行建模。
The algorithm took transmission time vector between nodes as input, and a model was established by KLPP, which can reflect partial information network topology structure.
该算法以节点间的传输时间向量为输入，借助能够体现网络拓扑结构局部信息的核局部保持映射进行建模。
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