Difference between revisions of "What is Tensor?"
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In simplifying terms, we can think of tensors as multidimensional arrays of numbers, as a generalization of scalars, vectors, and matrices. | In simplifying terms, we can think of tensors as multidimensional arrays of numbers, as a generalization of scalars, vectors, and matrices. | ||
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| + | # Scalar | ||
| + | # Vector | ||
| + | # Matrix | ||
| + | # 3-Tensor | ||
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| + | When we describe tensors, we refer to its “dimensions” as the rank (or order) of a tensor, which is not to be confused with the dimensions of a matrix. For instance, an m × n matrix, where m is the number of rows and n is the number of columns, would be a special case of a rank-2 tensor. A visual explanation of tensors and their ranks is given is the figure below. | ||
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| + | [[File:Tensors.png]] | ||
[[Category:Blog]] | [[Category:Blog]] | ||
Revision as of 11:05, 15 November 2020
2020
In simplifying terms, we can think of tensors as multidimensional arrays of numbers, as a generalization of scalars, vectors, and matrices.
- Scalar
- Vector
- Matrix
- 3-Tensor
When we describe tensors, we refer to its “dimensions” as the rank (or order) of a tensor, which is not to be confused with the dimensions of a matrix. For instance, an m × n matrix, where m is the number of rows and n is the number of columns, would be a special case of a rank-2 tensor. A visual explanation of tensors and their ranks is given is the figure below.
