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The matrix components are these dot products.LSMOG said:I understand the dot product of ei.ej, but I can't find the matrix components.
Thank you. But you you gave x, y and z in spherical coordinates, according to your last expression, I need dx, dy and dx in spherical coordinates.sweet springs said:You can get it by inserting
[tex]x=r\ sin\theta\ cos\phi[/tex]
[tex]y=r\ sin\theta\ sin\phi[/tex]
[tex]z=r\ cos\ \theta[/tex]
into
[tex]dx^2+dy^2+dz^2[/tex]
do the derivativesLSMOG said:Thank you. But you you gave x, y and z in spherical coordinates, according to your last expression, I need dx, dy and dx in spherical coordinates.
The matrix in the attachment was found using a process called matrix factorization. This involves breaking down a larger matrix into smaller, more manageable matrices in order to extract useful information.
Matrix factorization is a mathematical process used to break down a larger matrix into smaller matrices in order to better understand or analyze the data contained within the larger matrix. It is commonly used in various fields such as data analysis, machine learning, and signal processing.
The purpose of using matrix factorization to find the matrix in the attachment is to simplify the data and make it easier to analyze. By breaking down the larger matrix into smaller matrices, we can extract useful information and patterns that may not have been easily noticeable in the original matrix.
The accuracy of the matrix found through factorization depends on various factors such as the quality of the original data, the method of factorization used, and the desired level of accuracy. In general, matrix factorization is a reliable method for extracting useful information from large datasets.
Yes, matrix factorization can be applied to various types of data such as numerical data, text data, and even images. However, the specific method of factorization used may vary depending on the type of data being analyzed.