A scalar, which is a tensor of rank 0, is just a number, e.g. 6
A vector, which is a tensor of rank 1, is a group of scalars, e.g. [1, 6, 3]
A matrix, which is a tensor of rank 2, is a group of vectors, e.g.
1 6 3
9 4 2
0 1 3
A tensor of rank 3 would be a group of matrix and would look like a 3d matrix.
A tensor is the general term for all of these, and the generalization into high dimensions.
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actually MATRICES is the plural of matrix which means the array of numbers in groups and columns in a rectangular table... and determinant is used to calculate the magnitude of a matrix....
The matrices must have the same dimensions.
Only square matrices have a determinant
There are no matrices in the question!
I do not. I f*cking hate matrices. I multiply sheep.
A tensor is a mathematical object that generalizes the concepts of scalars, vectors, and matrices. It can represent relationships between geometric vectors, scalars, and other tensors. In physics and engineering, tensors are used to describe various physical properties and phenomena in a mathematical framework.
Tensors are simply arrays of numbers, or functions, that transform according to certain rules under a change of coordinates. Scalars and vectors are tensors of order 0 and 1 respectively. So a vector is a type of tensor. An example of a tensor of order 2 is an inertia matrix. And just for fun, the Riemann curvature tensor is a tensor of order 4.
To multiply two tensors tf_x and tf_y, you can use tf.matmul(tf_x, tf_y) in TensorFlow. This function computes the matrix product of the two tensors. Make sure the dimensions of the tensors are compatible for matrix multiplication, such as the inner dimensions of the tensors being the same.
The dyadic product of two tensors is significant in mathematics and physics because it allows for the combination of two tensors to create a new tensor that represents a specific physical quantity or transformation. This operation is commonly used in fields such as mechanics, electromagnetism, and quantum mechanics to describe complex relationships between different physical quantities or properties.
Only square matrices have inverses.
actually MATRICES is the plural of matrix which means the array of numbers in groups and columns in a rectangular table... and determinant is used to calculate the magnitude of a matrix....
how is matrices is applicable in our life?
The singular form of matrices is matrix.
The matrices must have the same dimensions.
Only square matrices have a determinant
William John Gibbs has written: 'Tensors in electrical machine theory' -- subject(s): Electrodynamics, Calculus of tensors, Electric machinery
Frank Hadsell has written: 'Tensors of geophysics for mavericks and mongrels' -- subject(s): Algebras, Linear, Calculus of tensors, Geophysics, Linear Algebras, Mathematics