Subspace, Linear Algebra, C^n[a,b]

In summary: The derivative of a power is: \left(f^{n}\left(x\right)\right)^{\left(n\right)}=n\left(f^{n-1}\left(x\right)\right)f'(x)In summary, C^n[a,b] is a subspace of C[a,b] because it satisfies the addition and multiplication properties of subspaces, as shown through the generalization of all nth derivatives. Using Maple or Latex can help with understanding and properly expressing these concepts.
  • #1
Dustinsfl
2,281
5
Show that C^n[a,b] is a subspace of C[a,b] where C^n is the nth derivative.

I know the set is non empty since f(x)=x exist; however, I don't know how to start either the multiplication or addition property of subspaces to confirm that C^n is a subspace.

Thanks ahead of time for any help any of you may have.
 
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  • #2
What's the derivative of the sum of two functions? What's the derivative of a function multiplied by a constant?
 
  • #3
alpha*n*f^(n-1)(x)
n*(f+g)^(n-1)(x)=n*[f^(n-1)(x)+g^(n-1)(x)]=n*f^(n-1)(x)+n*g^(n-1)(x)

That works for generalization all nth derivative functions?
 
  • #4
Your expressions don't make much sense. If I'm reading them right (and please, try to use Latex), you're saying that:

[tex]\left(\alpha f\left(x\right)\right)^{n}=n\alpha\left(\alpha f\left(x\right)\right)^{n-1}[/tex]

That doesn't make much sense.
 
  • #5
multiplication: [tex]\alpha[/tex]*n*[tex]f^{n-1}(x)[/tex]
addition: n*[tex](f+g)^{n-1}[/tex] = n*[[tex]f^{n-1}(x)[/tex]+[tex]g^{n-1}(x)[/tex]]
and then the n distributes.

Does this generalize all nth derivatives?

Is there away for me to import from Maple since I have Maple and Latex is to slow and cumbersome?
 
  • #6
Those expressions are wrong, given functions f,g and a constant c, their n-th derivatives are:

[tex]\left(f+g\right)^{\left(n\right)}\left(x\right)=f^{\left(n\right)}\left(x\right)+g^{\left(n\right)}\left(x\right)[/tex]

And:

[tex]\left(cf\right)^{\left(n\right)}\left(x\right)=cf^{\left(n\right)}\left(x\right)[/tex]
 
  • #7
But when the derivative is taking, don't the functions need to be multiplied by n and then the derivative is n-1?
 
  • #8
You are confusing the derivative of a power with the n-th derivative.
 

FAQ: Subspace, Linear Algebra, C^n[a,b]

What is subspace in linear algebra?

Subspace in linear algebra refers to a subset of a vector space that satisfies certain conditions. These conditions include containing the zero vector, being closed under addition and scalar multiplication, and containing all linear combinations of its vectors. In simpler terms, a subspace is a smaller space within a larger vector space that follows the same rules as the larger space.

What is the significance of subspace in linear algebra?

Subspaces play a crucial role in linear algebra because they allow for the simplification and generalization of concepts and problems. By studying a subspace, we can gain insights and solutions that can be applied to the larger vector space. Subspaces also provide a framework for understanding concepts like basis, dimension, and linear transformations.

How is linear algebra used in C^n[a,b]?

In C^n[a,b], linear algebra is used to study and manipulate continuous functions on the interval [a,b]. This includes finding solutions to differential equations, approximating functions, and understanding the behavior of functions. Linear algebra techniques such as basis and dimension can also be applied to C^n[a,b] to simplify problems and gain insights.

What is the role of C^n[a,b] in linear algebra?

C^n[a,b] is a specific vector space that contains all continuous functions on the interval [a,b]. This vector space is important in linear algebra because it allows for the study and application of linear algebra concepts and techniques to the real world. C^n[a,b] also serves as a foundation for more advanced mathematical topics such as Fourier analysis and functional analysis.

What are some real-world applications of subspace and linear algebra?

Subspace and linear algebra have numerous applications in fields such as physics, engineering, and computer science. Some examples include image and signal processing, data compression, quantum mechanics, and optimization problems. Linear algebra also plays a crucial role in machine learning and artificial intelligence, as it provides tools for analyzing and manipulating large datasets.

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