Inner Product Proof on Square Integrable Functions

In summary, an inner product in the context of square integrable functions is a mathematical operation that takes in two functions and produces a scalar value. It is important to prove this inner product in order to rigorously analyze these functions and define concepts such as orthogonality and distance. The key properties of the inner product include linearity, symmetry, and positive definiteness. The Cauchy-Schwarz inequality is related to this inner product and can be used to prove the existence of the norm and establish the triangle inequality. This inner product can also be extended to other spaces, but the specific properties and definitions may vary. Careful definition of the space and inner product is necessary for proper generalization.
  • #1
SunnyBoyNY
63
0

Homework Statement



Consider the linear space S, which consists of square integrable continuous
functions in [0,1]. These are continuous functions x : [0,1] -> R such that the integral is less than infinity.

Homework Equations



Show that the operation

∫x(t)y(y)dt at [0,1] is an inner product in this space.

The Attempt at a Solution



Apparently there are three axioms:

1] <x,x> is >= 0 (<x,x> = 0 only if x is a trivial function). I think that know how to prove this one. Simply, if the integrand is positive at any point then the function must be positive in the neighborhood of that point. Therefore, the integral cannot be <= 0. It can be zero only if the function is trivial such that x(t) = 0.

2] Linearity - how would I prove the linearity argument for general continuous functions? Could I replace such function with its Taylor series and show the linearity on the resulting polynomials?

3] Symmetry - no clue so far.

Could you guys give me some pointers?

Thanks a lot,

SunnyBoy
 
Last edited:
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  • #2
Should that be [itex] \int x(t) y(t) dt [/itex]?

I think you may be over complicating things. First off, linearity and symmetry are actually the two easier parts. What does linearity of the inner product mean? Write it out and you'll see it follows immediately. Same thing with symmetry.

Edit: Forgot to address the first part. This is actually the harder part. You've shown that if the inner-product is non-negative then x cannot be trivial. This is the contrapositive of the statement [itex] \langle x ,x \rangle = 0 \Rightarrow x \equiv 0 [/itex]. However, this you still need to show the first part: You want to show that [itex] \langle x, x \rangle \geq 0 [/itex]. Again, write this out and you'll see why it's true.
 
  • #3
Hello Kreizhn,

you are right- the integrands are both functions of one variable (time).

I have done what you suggested - the algebra is not really that difficult. However, how do I incorporate the "square-integrable" statement into the problem? Or is that just a generic statement which limits our function selection so that the inner product can be evaluated?

Linearity: [itex] <ax,y> = a<x,y>[/itex]
And:
[itex] <x+y,z> = <x,z> + <y,z>[/itex]

So:

[tex] <af(t),g(t)> = \int_{0}^{1}af(t)g(t)dt = a\int_{0}^{1}f(t)g(t)dt = a<f(t),g(t)>[/tex]
And:
[tex] <f(t)+g(t),h(t)> = \int_{0}^{1}(f(t)+g(t))h(t)dt = \int_{0}^{1}f(t)h(t)+g(t)h(t)dt = <f(t),h(t)>+<g(t),h(t)>[/tex]

Symmetry:

[tex] <f(t),g(t)> = \int_{0}^{1}f(t)g(t)dt = \int_{0}^{1}g(t)h(t)dt = <g(t),f(t)>[/tex]

First axiom:

The integrand must be non-negative at all times since it is a square of a function. Therefore, if the function is continuous then no point can be negative. Therefore, the integral value must be nonnegative.

[tex] <f(t),f(t)> = \int_{0}^{1}f(t)f(t)dt= \int_{0}^{1}f^2(t)dt >= 0 [/tex]

Thanks!

SunnyBoy
 
  • #4
SunnyBoyNY said:
However, how do I incorporate the "square-integrable" statement into the problem? Or is that just a generic statement which limits our function selection so that the inner product can be evaluated?

...

[tex] <f(t),f(t)> = \int_{0}^{1}f(t)f(t)dt= \int_{0}^{1}f^2(t)dt >= 0 [/tex]

I'm not sure if you didn't just answer this question yourself, but in case it's not clear, let me just explain it quickly. Look at your last line of math. How do you know [itex] \langle f(t), f(t) \rangle [/itex] is finite? Well, it is, and the reason it is finite is precisely because f is square integrable on [0,1].
 
  • #5
Seems pretty straightforward then. Thank you very much, Kreizhn!

Should I edit my second post so that folks who are solving the same problem will have the same pointer as I had? I am not sure what the policy is but i have gotten the impression that pple are encouraged to do the thinking themselves (no direct answers provided).

SunnyBoy
 
  • #6
I think it's fine. It's more important that I don't give you the answer. You are allowed to demonstrate that you have successfully solved the problem.
 

Related to Inner Product Proof on Square Integrable Functions

1. What is an inner product in the context of square integrable functions?

An inner product in the context of square integrable functions is a mathematical operation that takes in two functions and produces a scalar value. It is defined as the integral of the product of the two functions over a given interval. The resulting scalar value represents the similarity or "closeness" of the two functions.

2. Why is it important to prove the inner product on square integrable functions?

Proving the inner product on square integrable functions is important because it provides a rigorous mathematical framework for analyzing these functions. It allows us to define important concepts such as orthogonality and distance between functions, which are crucial in many areas of mathematics and physics.

3. What are the key properties of the inner product on square integrable functions?

There are several key properties of the inner product on square integrable functions, including linearity, symmetry, and positive definiteness. Linearity means that the inner product of a linear combination of functions is equal to the same linear combination of their individual inner products. Symmetry means that the inner product of two functions is the same regardless of the order in which they are multiplied. Positive definiteness means that the inner product of a function with itself is always greater than or equal to zero, with equality only when the function is equal to zero.

4. How is the Cauchy-Schwarz inequality related to inner product on square integrable functions?

The Cauchy-Schwarz inequality is a fundamental result in mathematics that states that the absolute value of the inner product of two vectors is less than or equal to the product of their magnitudes. In the context of square integrable functions, this inequality can be used to prove the existence of the norm (or length) of a function, as well as to establish the triangle inequality, which is crucial in defining a metric space for these functions.

5. Can the inner product on square integrable functions be extended to other spaces?

Yes, the inner product on square integrable functions can be extended to other spaces, such as the space of continuous functions or the space of complex-valued functions. However, the specific properties and definitions may differ slightly in these different spaces. It is important to carefully define the space and inner product being used in order to properly generalize the concept.

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