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N-sparse

于 2013-10-21 发布 文件大小:23KB
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  创建一个n维的稀疏数组对象,n是任意值。 定义N可能是大于2的一类n维稀疏阵列。然而,它应该被认为是一种起动方式与普通的MATLAB稀疏矩阵和重塑它有N维度。换句话说,稀疏的数据,首先必须能够作为一个普通的2D MATLAB稀疏矩阵被前n维。事实上,如果目标数组的尺寸mxnxp……yxz,然后将它存储在内部类是一个普通的二维稀疏阵列的尺寸(M×N×P×……×Y)XZ。这导致了某些内存株时使用大量的尺寸。我发现有用的类主要用于中等尺寸像三维图像边缘检测,你经常要举行一个稀疏的3D的边缘地图。(Creates an N-dimensional sparse array object, for arbitrary N.This submission defines a class of N-dimensional sparse arrays for N possibly greater than 2. However, it should really be thought of as a way of starting with an ordinary MATLAB sparse matrix and reshaping it to have N dimensions. In other words, the sparse data must first be able to exist as an ordinary 2D MATLAB sparse matrix before being made N-dimensional. In fact, if the intended array has dimensions MxNxP...YxZ, then the class will store it internally as an ordinary 2D sparse array of dimensions (M*N*P*...*Y)xZ. This leads to certain memory strains when using large numbers of dimensions. I find the class useful mainly for moderate dimensional things like edge detection in 3D imaging, where you often want to hold a sparse 3D edge map. )

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