Distributed Crossproduct of a Rectangular Matrix and a VectormatName
The product of a Wishart matrix and a normal vector appears in the variety of statistics under the multivariate normality. For example, the coefficients of the linear discriminant function and the weights of the tangency portfolio are expressed as the product of a Wishart matrix and a normal ...
vector product n. A vectorc, depending on two other vectorsaandb, whose magnitude is the product of the magnitude ofa, the magnitude ofb, and the sine of the angle betweenaandb. Its direction is perpendicular to the plane throughaandband oriented so that a right-handed rotation about it ...
4) tensor product of matrix and vector 矩阵和向量的张量积5) Kronecker product 矩阵直积 1. By Kronecker product and the eigenvector of the coefficient matrix, the linear equations set for the hand-eye transformation matrix is derived and the error induced by discarding a block line equation ...
网络矩阵和向量乘法 网络释义 1. 矩阵和向量乘法 让我们再看一个矩阵和向量乘法(matrix-vector product)的systolic计算方法来加深印象:对任意一个矩阵 163.27.3.193|基于 1 个网页
Note that it should not be confused with the more common matrix product. Tensor product. Given two vectors, this product takes each element of a vector and multiplies it by all of the elements in the other vector creating a new row in the resultant matrix. Let N and M are two vectors ...
Learn the definition of Vector cross product and browse a collection of 39 enlightening community discussions around the topic.
So, a matrix object is used to encode all the information on how they interact.// Forming the tensor product v\otimes w of two vectors is a lot like forming the Cartesian product of two sets X \times Y . In fact, that's exactly what we are doing if we think of X as the set ...
Large randomly sparse matrix vector products are important in a number of applications in computational chemistry, such as matrix diagonalization and the solution of simultaneous equations. Vectorization of this process is considered for the CRAY XMP, CRAY 2, and CYBER 205, using a matrix of dimensi...
The matrix–vector product kernel can represent most of the computation in a gradient iterative solver. Thus, an efficient solver requires that the matrix–vector product kernel be fast. We show that standard approaches with Fortran or C may not deliver good performance and present a strategy invo...