photonic_crystal_method_of_characteristic_matrix_1

用fortran编写的计算水凝胶变形的UEL(Written using fortran calculated deformation of the hydrogel UEL)

说明：  局部线性回归方法及其稳健形式已经被看作一种有效的非参数光滑方法.与流行的核回归方法相比,它有诸多优点,诸如:较高的渐近效率和较强的适应设计能力.另外,局部线性回归能适应几乎所有的回归设计情形却不需要任何边界修正。(Local linear regression methods and their solid form has been seen as an effective non-parametric smoothing method. Contrary to popular kernel regression methods, it has many advantages, such as: higher efficiency and stronger asymptotic adaptation design capacity. In addition, the local linear regression to adjust to the return of the design of almost all cases does not require any boundary amendment.)

计算方法：主要是高斯消去法的C语言算法实现(Calculation method: Gaussian elimination)

用matlab来模拟温度场，准确度高，具有参考价值。(yong matlab lai moni wenduchang ,zhuquedugao ,juou cankaojiazhi .)

sar图像去噪的几种新的方法，数学方法是部分子空间法，实现典型相关分析。( Several new methods sar image denoising, Mathematics is part of the subspace, Achieve canonical correlation analysis.)

提供两种非线性动态方程线性化的方法实例，精确线性化方法和反馈线性化方法(Provides two linear equations of nonlinear dynamic methods examples of exact linearization and feedback linearization method)

利用贝叶斯分类原理实现多义词的消歧。首先利用训练语料进行训练，然后基于机器已经获取的知识的基础上对生语料进行词义标注。(Realize the principle of the use of Bayesian classification polysemous word sense disambiguation. First of all, the use of training corpus for training, and then the machine has been based on knowledge gained on the basis of corpus for semantic tagging of Health.)

stiff differential equations examples

说明：  ADAM （Adaptive Moment Estimation）是另外一种自适应学习率算法，它结合动量梯度 下降法，在不同参数方向上采用不同学习率，保留前几次迭代的梯度，能够很好 的适应于稀疏数据。(ADAM (Adaptive Moment Estimation) is another adaptive learning rate algorithm, which combines momentum gradient. The descent method, which uses different learning rates in different parameter directions and retains the gradients of previous iterations, is very good. It is suitable for sparse data.)

说明：  相场法材料计算的modelc-alloy 对应的基础代码，自取基础有用(The basic code corresponding to modelc-alloy for phase field method material calculation, useful for self-extraction)