Galton-nail-plate-problem

recurrent neural network

LiScNLS is a Matlab application for the numerical study of some nonlinear differential equations of the form Lu=Nu, using the Lyapunov-Schmidt method. Downloading the LiScNLS package creates a new LiScNLS folder on the computer.(LiScNLS is a Matlab application for the numerical study of some nonlinear differential equations of the form Lu = Nu, using the Lyapunov-Schmidt method.Downloading the LiScNLS package creates a new LiScNLS folder on the computer.)

k个位子，n个元素填充，每个位置上数字可重复。例程为一简洁的递归算法，显示所有可能的组合(n to K problem)

说明：  Matlab中的画圆函数。Matlab本身没有画圆的函数。本附件实现了画圆函数。(Drawcircle function in Matlab. Matlab does not have drawcircle function. Of this Annex drawcircle realize the function.)

对nii文件进行Z变换，并保存成nii文件(Z transform to the NII file and save it as a NII file)

若干种r/s估值法源代码，试试看很好用，有没有朋友有其他估值法下的源代码？麻烦上传分享一下，(Number of r/s valuation method source code, give it a try very good, and have no friends there are other valuation method under the source code? From trouble to share,)

几种集体联合对角化的盲源分离算法，包括ACDC，SOBI,WEDGE,UWEDGE.(Several collective joint diagonalization for blind source separation algorithm, including ACDC, SOBI, WEDGE, UWEDGE.)

基于SVD分解的总体最小二乘算法,在工程领域有很大的应用(Based on the SVD decomposition of the overall least-squares algorithm, in the engineering field has a lot of applications)

单基地多普勒补偿,可实现单基地的多普勒补偿(Doppler compensation of monostatic)

流形学习，局部线性嵌入式算法(LLE)，一种智能的算法去推测捕捉高维空间中所包含的低维特征。与适合于局部维数约减的聚类算法不同，LLE算法在单一的低维的全域坐标系统中表征采样空间，然而它并没有优化最小局域。通过对线性重构的局域对称的研究应用，LLE能够描述非线性流形的全局结构，例如那些人脸的数据集或者文本文档集(Manifold learning, embedded local linear algorithm (LLE), an intelligent algorithm to predict capture high-dimensional space contained in the low-dimensional features. And for local dimensionality reduction of the different clustering algorithms, LLE algorithm in a single low-dimensional characterization of the global coordinate system, the sampling space, but it does not optimize the local minimum. Reconstructed by the local symmetry of the linear study of the application, LLE can describe the global structure of nonlinear manifolds, such as those who face data sets or text document collection)