Norms of a general vector space

In summary, the norm of a vector in the vector space of continuous functions on a closed interval [a, b] has physical significance as it allows us to measure the distance between functions and determine their convergence. The specific value of the norm, such as 1/3, depends on the inner product used to define it. For example, if the inner product is defined as the integral over [a, b], then the norm is related to the area of the function. Different norms can provide different measures of size for functions, such as average value or maximum value. Inner products are more special than norms as they also allow for the measurement of angles.
  • #1
matqkks
285
5
All continuous functions on closed interval [a, b] form a vector space. The functions in this space are the vectors. However what is the physical significance of the norm of a vector in this space? For example if we found the norm of a function is 1/3 what does this signify? Does it dependent on the inner product used to define the norm?
Say if the inner product is the integral over [a, b] does this mean that the norm is related to the area?
 
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  • #2
matqkks said:
All continuous functions on closed interval [a, b] form a vector space. The functions in this space are the vectors. However what is the physical significance of the norm of a vector in this space? For example if we found the norm of a function is 1/3 what does this signify? Does it dependent on the inner product used to define the norm?
Say if the inner product is the integral over [a, b] does this mean that the norm is related to the area?

Yes, if you define the inner product as

[tex]<f,g>=\int_a^b{f(t)g(t)dt}[/tex]

then your norm will be

[tex]\|f\|_2=\sqrt{\int_a^b{|f(t)|^2dt}}[/tex]

This means that a function f will be close to 0 if the area of f is very low. More generally, a function f will be close to g if their area's are close together.

You have different possible norms on the continuous functions, and all describe something different. Good questions you should ask for each norm is "what functions are close to the 0 function" or "when are two functions close together".
 
  • #3
norms measure the size of things. integral norms for functions measure the average value, max norms measure the maximum value, integrals of squares measure the average squared value. you must decide in a physical situation which of these measures suits your problem.
 
  • #4
If you have an inner product, then there is a standard way of defining the norm and so the "length" of a vector. However, it is possible to have a norm without an inner product.

[itex]L_1([a, b])[/itex] is the set of functions, f(x), such that the Lebesque integral, [itex]\int |f(x)|dx[/itex] exists. And, of course, we define the norm of f to be that integral.

The crucial point of the norm of a function is that it allows us to measure the distance between functions, allowing us to talk about convergence of sequences of functions.
 
  • #5
as halls says, inner products are more special than norms, and allow also to measure angles.
 

Related to Norms of a general vector space

What is a vector space?

A vector space is a mathematical structure that consists of a set of vectors, which can be added together and multiplied by scalars (numbers), and follows certain rules and properties.

What are the properties of a vector space?

The properties of a vector space include closure under addition and scalar multiplication, associativity and commutativity of addition, existence of an additive identity element (zero vector), existence of a multiplicative identity element (scalar 1), and distributivity of scalar multiplication over vector addition.

What is the norm of a vector in a general vector space?

The norm of a vector in a general vector space is a measure of its size or magnitude. It is typically denoted as ||x|| and can be calculated using different methods depending on the specific vector space and its associated metric.

What are the different types of norms in a general vector space?

There are several types of norms that can be used in a general vector space, including Euclidean norm, Manhattan norm, Maximum norm, and p-norm. Each type of norm has its own formula for calculation and represents different ways of measuring the size of a vector.

Why are norms important in a general vector space?

Norms are important in a general vector space because they allow us to measure the magnitude of a vector and compare it to other vectors. They also help us define concepts like distance and convergence in vector spaces, which are essential in many areas of mathematics, physics, and engineering.

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