Calculating Inner Products in an Inner Product Space

In summary, the conversation discusses the properties of inner product spaces and the given information about vectors \vec{u}, \vec{v}, and \vec{w}. The task is to compute the inner product of (\vec{2v-w},\vec{3u+2w}). The solution involves understanding the properties of inner product spaces and using the given information to compute the inner product.
  • #1
FeynmanIsCool
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0

Homework Statement



Suppose [itex]\vec{u}[/itex], [itex]\vec{v}[/itex] and [itex]\vec{w}[/itex] are vectors in an inner product space such that:

inner product: [itex]\vec{u},\vec{v}= 2[/itex]
inner product: [itex]\vec{v},\vec{w}= -6[/itex]
inner product: [itex]\vec{u},\vec{w}= -3[/itex]


norm[itex](\vec{u}) = 1[/itex]
norm[itex](\vec{v}) = 2[/itex]
norm[itex](\vec{w}) = 7[/itex]

Compute:

innerproduct: ([itex]\vec{2v-w},\vec{3u+2w}[/itex])




Homework Equations



[itex]\vec{u}[/itex], [itex]\vec{v}[/itex] and [itex]\vec{w}[/itex][itex]\in[/itex]Rn .The inner product type is not specified (ie. euclidean, weighted ect...)




The Attempt at a Solution



Im not sure where to start. This seems like a very simple problem, but I am confused on where to start. I can't expand inner products and solve for v,u or w since the inner product formula is not known. I also can't expand inner product([itex]\vec{2v-w},\vec{3u+2w}[/itex]) since I don't know the inner product formula. All I can think of doing right now is expanding norm[itex](\vec{u},\vec{v},\vec{w})[/itex] to equal [itex]\sqrt{innerproduct(\vec{u},\vec{u}})[/itex], [itex]\sqrt{innerproduct(\vec{v},\vec{v}})[/itex], [itex]\sqrt{innerproduct(\vec{w},\vec{w}})[/itex] but that gets me no where as well.
Can someone give a point in the right direction?
Thanks in advance!
 
Last edited:
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  • #2
You should look up what properties a function has to satisfy to be considered an inner product.
 
  • #3
ahh yes, the algebraic properties of inner product spaces. Of course!
Thanks

edit* its -101
 
Last edited:

1. What is an inner product space?

An inner product space is a mathematical structure that consists of a vector space and an inner product, which is a function that takes in two vectors and returns a scalar. This scalar represents the magnitude of the projection of one vector onto the other, and it also satisfies certain properties, such as symmetry and linearity, that make the inner product space useful for various calculations and proofs.

2. What is the difference between an inner product and a dot product?

An inner product is a more general concept than a dot product. While a dot product is defined as the sum of the products of the corresponding components of two vectors, an inner product can be defined on various types of vector spaces, including complex vector spaces. Additionally, an inner product can have properties that a dot product does not, such as being antilinear in one of its arguments.

3. How is an inner product space related to geometry?

An inner product space allows us to define geometric concepts such as length, angle, and orthogonality in a more abstract setting. This is useful because it allows us to apply geometric ideas to vector spaces that may not have a direct geometric interpretation, such as spaces of functions or matrices. Additionally, the inner product itself can be used to define a norm, which measures the length or magnitude of a vector.

4. What are some common applications of inner product spaces?

Inner product spaces have a wide range of applications in mathematics, physics, and engineering. They are used in quantum mechanics to represent the state of a physical system, in signal processing to analyze and manipulate data, and in optimization and control theory to solve various problems. They are also fundamental in areas such as functional analysis, which studies vector spaces of functions, and linear algebra, which deals with vector spaces of matrices.

5. How do you compute the inner product of two vectors?

The specific formula for computing the inner product of two vectors depends on the vector space and the definition of the inner product. In general, the inner product can be calculated by taking the sum of the products of the corresponding components of the two vectors, possibly multiplied by a complex conjugate or other coefficients. However, many vector spaces have a more abstract definition of the inner product, such as using integrals or other operations. It is important to understand the specific definition of the inner product in order to compute it correctly.

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