0
For the triangle shown and the rotation matrix R, which of the following shows the product of the matrices?
What else can I help you with?
What does the mean of product of two orthogonal matrix is orthogonal in terms of rotation?
The mean of the product of two orthogonal matrices, which represent rotations, is itself an orthogonal matrix. This is because the product of two orthogonal matrices is orthogonal, preserving the property that the rows (or columns) remain orthonormal. When averaging these rotations, the resulting matrix maintains orthogonality, indicating that the averaged transformation still represents a valid rotation in the same vector space. Thus, the mean of the rotations captures a new rotation that is also orthogonal.
These matrices represent the coordinates of two figures in the plane. Is the product of these matrices defined Answer yes or no?
no
Is the product of two elementry matrices is an elementry matrix?
No, it is not.
What are the differences between the Kronecker product and the tensor product?
The Kronecker product is a specific type of tensor product that is used for matrices, while the tensor product is a more general concept that can be applied to vectors, matrices, and other mathematical objects. The Kronecker product combines two matrices to create a larger matrix, while the tensor product combines two mathematical objects to create a new object with specific properties.
Is every square matrix is a product of elementary matrices explain?
Yes, every square matrix can be expressed as a product of elementary matrices. This is because elementary matrices, which perform row operations, can be used to transform any square matrix into its row echelon form or reduced row echelon form through a series of row operations. Since any square matrix can be transformed into the identity matrix using these operations, it can be represented as a product of the corresponding elementary matrices that perform these transformations. Thus, every square matrix is indeed a product of elementary matrices.
The product of two upper triangular matrices is upper triangular?
yes it is
How do you describe a product matrix without multiplying?
You can indicate the multiplication with a multiplication sign. If your matrices are "A" and "B", the product is: A x B In other words, you are indicating the product, but not actually carrying out any multiplication. Anybody who understands about matrices should know what this refers to.
How do you find the rank of product of two matrices?
just make the matrices upper triangular by making the values below the digonal zero,and then find how many minors can be calcuted.......
What is the proof of the anticommutator relationship for gamma matrices?
The proof of the anticommutator relationship for gamma matrices shows that when you multiply two gamma matrices and switch their order, the result is the negative of the original product. This relationship is important in quantum field theory and helps describe the behavior of particles.
Prove that the product of two orthogonal matrices is orthogonal and so is the inverse of an orthogonal matrix What does this mean in terms of rotations?
To prove that the product of two orthogonal matrices ( A ) and ( B ) is orthogonal, we can show that ( (AB)^T(AB) = B^TA^TA = B^T I B = I ), which confirms that ( AB ) is orthogonal. Similarly, the inverse of an orthogonal matrix ( A ) is ( A^{-1} = A^T ), and thus ( (A^{-1})^T A^{-1} = AA^T = I ), proving that ( A^{-1} ) is also orthogonal. In terms of rotations, this means that the combination of two rotations (represented by orthogonal matrices) results in another rotation, and that rotating back (inverting) maintains orthogonality, preserving the geometric properties of rotations in space.
What does product mean in a mathimatical way?
In short, the answer to a multiplication problem. The product of 3 and 5 is 15. There can be other kinds of products, like the product of matrices or vectors, but they're all about multiplication.
What is the used of dot product and cross product in real life?
The dot-product and cross-product are used in high order physics and math when dealing with matrices or, for example, the properties of an electron (spin, orbit, etc.).
