Understanding the Linearity Test for Inner Products

In summary, the conversation discusses verifying if a given function is a valid inner product and determining if it satisfies the linearity test. The tutor explains that the function does not satisfy linearity due to the x1 and y1 terms in front of the x2 and y2 terms. The conversation then explores explicitly calculating the inner product of <x+y,z> and comparing it to the sum of <x,z> and <y,z> to further prove the function's lack of linearity. The conversation also briefly discusses the inner product of <x,0*y> and how it does satisfy the linearity test. However, this does not prove anything about the given function. Eventually, it is discovered that the given inner product was being
  • #1
JamesGoh
143
0
In one of my tutorial problems, I was asked to verify if the following function
is a valid inner product

<[itex]x,y[/itex]>= [itex]x1x2 + y1y2[/itex]

Note, x=(x1,x2)[itex]^{T}[/itex] and y=(y1,y2)[itex]^{T}[/itex]

where T means transpose of the matrix

The tutor said to us the answer is no because it fails the linearity test

Does it fail the linearity test because of the x1 and y1 terms in front of the x2 and y2 ?
 
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  • #2
Try explicitly calculating
[tex]
\langle x+y,z\rangle
[/tex]
and see if it really does equal
[tex]
\langle x,z\rangle +\langle y,z\rangle
[/tex]
If it doesn't then you know it does not satisfy linearity.
 
  • #3
Does <x,0*y>=0*<x,y>?
 
  • #4
Yes, it does. But that doesn't prove anything.
 
  • #5
HallsofIvy said:
Yes, it does.
No it doesn't. <x,0>=x1x2.
 
  • #6
Oh, Blast! I was interpreting the given inner product wrong!
 

FAQ: Understanding the Linearity Test for Inner Products

1. What is an inner product?

An inner product is a mathematical operation that takes two vectors and produces a scalar value. It is often used to measure the angle between vectors and calculate the length of a vector.

2. How is an inner product different from a dot product?

An inner product is a generalization of a dot product, which is a specific type of inner product that only works with real-valued vectors. An inner product can work with vectors of any type, such as complex numbers or functions.

3. What are some properties of an inner product?

Some properties of an inner product include linearity, symmetry, and positive definiteness. Linearity means that the inner product of two vectors multiplied by a scalar is equal to the scalar multiplied by the inner product of the two vectors. Symmetry means that the inner product of two vectors is the same regardless of the order in which they are multiplied. Positive definiteness means that the inner product of a vector with itself is always a positive value.

4. What are some applications of inner products?

Inner products have many applications in mathematics, physics, and engineering. They are used in vector calculus, signal processing, quantum mechanics, and machine learning, among others. In particular, the dot product is commonly used in physics to calculate work and energy.

5. How can inner products be extended to higher-dimensional spaces?

Inner products can be extended to higher-dimensional spaces by using more complex mathematical structures, such as tensors or matrices. These structures allow for the calculation of inner products between multiple vectors at once and can be used in applications such as image and audio processing.

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