Inner product generated by matrix

In summary, for the given inner product defined by the matrix [1 2; -1 3], the distance between u = (-1, 2) and v = (2, 5) is found by first calculating the inner product as 2u1v1 + 13u2v2. Then, finding u - v, which is (-3, -3). Finally, using the equation d(u, v) = abs(u - v) to get the distance as 3√13. It is important to check the inner product calculation for any potential errors.
  • #1
derryck1234
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0

Homework Statement



Find d(u, v), where the inner product is defined by the matrix

[1 2]
[-1 3]

and u = (-1, 2), v = (2, 5)

Homework Equations



<u, v> = Au . Av
d(u, v) = abs(u - v)

The Attempt at a Solution



I first tried to find the resulting inner product from the matrix in terms of an equation:

I got it to be:

2u1v1 + 13u2v2

Then I simply found u - v, which came to be (-3, -3)

And thus d(u, v) = <-3, -3>0.5

This, in terms of the relevant inner product, is:

[2(9) + 13(9)]0.5

Unfortunately, the books answer does not agree? It says it is 3 times root 13. I get root 135?
 
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  • #2
Check your inner product calculation. There should be some u1v2 and u2v1 terms
 
  • #3
Thanks.
 

FAQ: Inner product generated by matrix

What is an inner product generated by a matrix?

An inner product generated by a matrix is a mathematical operation that takes two vectors as inputs and produces a scalar value as an output. It is defined as the sum of the products of the corresponding elements of the two vectors. This operation is commonly used in linear algebra and plays a crucial role in many fields of science, including physics, computer science, and engineering.

How is an inner product generated by a matrix calculated?

To calculate an inner product generated by a matrix, the two vectors are first multiplied element-wise. The resulting vector is then summed, giving a single scalar value as the output. This process can be visualized as projecting one vector onto the other and measuring the length of the projection. It can also be represented by matrix multiplication, where the first vector is transposed and multiplied by the second vector.

In what applications is an inner product generated by a matrix used?

An inner product generated by a matrix is used in various applications, such as signal processing, image and video compression, data analysis, and machine learning. It is also an essential tool in quantum mechanics, where it represents the probability of finding a quantum state in a particular state.

What are the properties of an inner product generated by a matrix?

An inner product generated by a matrix has several properties that make it a powerful mathematical tool. These include linearity, symmetry, and positive definiteness. Linearity means that the inner product is distributive and follows the rules of scalar multiplication. Symmetry states that the inner product of two vectors is the same regardless of the order in which they are multiplied. Positive definiteness ensures that the inner product is always positive, except when the input vectors are zero.

How does an inner product generated by a matrix relate to other mathematical concepts?

An inner product generated by a matrix is closely related to other mathematical concepts, such as norms, orthogonality, and projections. The norm of a vector can be calculated using the inner product, while orthogonality is defined as the inner product of two vectors being zero. Projections can also be expressed using inner products, as they represent the length of the projection of one vector onto another.

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