Linearly independent function sets

In summary: But this example is so large that it's hardly general.In summary, the conversation discusses the linear independence of various sets of functions, including exponential functions, sine functions, gamma functions, and sine integrals. It is noted that almost all randomly collected sets of functions are linearly independent. The discussion also touches on the concept of infinity and the difficulty in proving linear independence for infinite sets of functions.
  • #1
hilbert2
Science Advisor
Insights Author
Gold Member
1,598
605
It is well known that the set of exponential functions

##f:\mathbb{R}\rightarrow \mathbb{R}_+ : f(x)=e^{-kx}##,

with ##k\in\mathbb{R}## is linearly independent. So is the set of sine functions

##f:\mathbb{R}\rightarrow [-1,1]: f(x) = \sin kx##,

with ##k\in\mathbb{R}_+##.

What about other kinds of special functions, would something like the set of gamma functions ##\Gamma (kx)## or sine integrals ##Si (kx)## also be linearly independent? Or the exponential integrals ##E_n (x)## of different integer orders ##n##?

Are there any good sources in literature that handle these questions?
 
Mathematics news on Phys.org
  • #2
Would Sturm-Liouville be a good starting point? If you have a set of functions that are solutions to differential equation, and you can show that the differential operator is self-adjoint, then the orthogonality of eigenfunctions follows automatically (e.g. Arfken & Weber "Mathematical Methodds for Physicists").

Indeed, both of your examples can be regrarded as eigen-functions of Laplace's equation.
 
  • Like
Likes hilbert2
  • #3
Yes, this is true for the exponential and sine/cosine functions. But the gamma function is not a solution of any differential equation, neither is the sine integral ##Si (x)## as far as I know.

It's quite easy to show that any finite set of exponentials ##e^{k_1 x}, e^{k_2 x}, \dots,e^{k_n x}##, with all ##k_i## different numbers, is linearly independent, because looking at the equation

##C_1 e^{k_1 x} + C_2 e^{k_2 x} + \dots + C_n e^{k_n x} = 0##,

one of the multipliers ##k_i## is largest and therefore the term on the LHS having it in the exponent will eventually grow much faster than all the other terms when ##x## is made large enough. The other terms can't therefore cancel it and the equation can't be true. This approach doesn't require operator theory, and can probably be applied to a finite set of scaled gamma functions ##\Gamma (kx)##.
 
  • #4
The same argument works for all functions where ##\frac{f_{k_1}(x)}{f_{k_2}(x)} \to \infty## for ##x\to \infty## for all ##k_1 > k_2## and similar relations. A different limit for x works as well.
 
  • Like
Likes hilbert2
  • #5
hilbert2 said:
What about other kinds of special functions

The property of being an independent set of functions isn't hard to satisfy. You can find much material about sets of functions that satisfy the stronger property of being orthogonal (with respect to some inner product). For example, there are many well know families of orthogonal polynomials.

One unifying way to look at special functions is to consider them as elements of matrices that implement representations of groups. https://bookstore.ams.org/mmono-22
 
  • Like
Likes StoneTemplePython, Cryo and hilbert2
  • #6
mfb said:
The same argument works for all functions where ##\frac{f_{k_1}(x)}{f_{k_2}(x)} \to \infty## for ##x\to \infty## for all ##k_1 > k_2## and similar relations. A different limit for x works as well.

Is there any known condition for this to also hold for an infinite sequence of functions? Or a continuum set of functions?
 
  • #7
mfb said:
The same argument works for all functions where ##\frac{f_{k_1}(x)}{f_{k_2}(x)} \to \infty## for ##x\to \infty## for all ##k_1 > k_2## and similar relations. A different limit for x works as well.

Questions that touch on infinity are very much at the edge of my comfort zone. Can I therefore ask you a question to educate myself? I would expect that a finite set of functions with property ##\frac{f_{k_1}(x)}{f_{k_2}(x)} \to \infty## for ##x\to \infty## can be linearly independent following the logic of hilbert2. Should one be cautious about infinite sets, countably infinite sets etc.?
 
  • #8
hilbert2 said:
Is there any known condition for this to also hold for an infinite sequence of functions? Or a continuum set of functions?
What do you really want to know? @mfb has just generalized your argument for ##e^{kx}## and strengthened that it applies to other families of functions, too. @Stephen Tashi has mentioned that linear independence is the standard, not the exception, i.e. a randomly gathered set of functions will a.a. be linear independent. Linear dependency is the zero set.

To me it is similar to the situation of transcendental numbers: almost all are. To prove it in certain cases is another question, which depends on the way those numbers are defined, since definitions tend to use an algebraic notation. Here we have a similar situation: almost all are (linearly independent), and a proof depends on their definition, which again is given by a restricted set of letters which are introduced to describe algebraic or analytic dependencies. So we even have a slightly better situation given, as our alphabet isn't restricted to linear relationships.

Nevertheless, a certain situation is driven by the definition of said functions. The general statement is: a.a. (randomly) collected functions are linear independent. If we drop the random aspect of it, then we will find ourselves in a certain situation, which requires a definition to be given - not just some examples.
 
  • #9
Linear independence means there is no finite sum that adds up to zero. It doesn't matter if we have an infinite set of functions to draw from or not: The finite sum will always have one function that dominates.
 
  • Like
Likes hilbert2
  • #10
Ok, thanks, I think this clarified the matter.

Edit: I initially went in the trap of thinking that it would be difficult to find this kind of function sequences without exhausting the possibilities, but then again, the set of integers divisible by ##10^6## is as "large" as the set of all integers, and the Cantor set is as large as ##\mathbb{R}##, so this isn't really surprising after all.
 
Last edited:
  • #11
I think that given any set of countably many functions, the set of linear independent functions to them is dense in the usual, non-trivial topologies like metric induced or Zariski.
 
  • #12
I was thinking of something like a cartesian product of infinitely many ##\mathcal{C}^\infty## sets as a set of all ordered sequences of well behaved functions. Then it could be shown that any subset of nonzero "volume" contains a lin. independent sequence.
 
  • #13
hilbert2 said:
I was thinking of something like a cartesian product of infinitely many ##\mathcal{C}^\infty## sets as a set of all ordered sequences of well behaved functions. Then it could be shown that any subset of nonzero "volume" contains a lin. independent sequence.
You mean for instance, given ##S \subseteq \{\,\exp(kx)\,\}\times \{\,\Gamma(kx)\,\}\times \{\,Si(kx)\,\}\times \{\,\ldots\,\}\times\ldots ## and ##\lambda(S) > 0## according to some Lebesgue measure contains a linear independent sequence? Beside the difficulty to achieve a positive measure of such a thin set, there shouldn't be a problem to find such a sequence: looks as all are. As mentioned earlier, linear independence is the standard and linear dependence the exception.
 

1. What is the definition of a linearly independent function set?

A linearly independent function set is a collection of functions in which no function can be expressed as a linear combination of the other functions in the set. This means that the functions are not dependent on each other and cannot be reduced to simpler forms.

2. How do you determine if a function set is linearly independent?

To determine if a function set is linearly independent, you can use the definition of linear independence, which states that for a set of functions to be linearly independent, the only solution to the equation c1f1(x) + c2f2(x) + ... + cnfn(x) = 0 must be c1 = c2 = ... = cn = 0. In other words, the only way for the sum of the functions to equal zero is if all the coefficients are zero.

3. Why is it important for a function set to be linearly independent?

It is important for a function set to be linearly independent because it allows for unique solutions to be found in applications such as linear algebra and differential equations. If a function set is linearly dependent, it means that some functions in the set can be expressed as combinations of others, which can lead to redundant information and make it difficult to find a unique solution.

4. Can a linearly independent function set have an infinite number of functions?

Yes, a linearly independent function set can have an infinite number of functions. As long as each function in the set is not a linear combination of any other function, the set can be considered linearly independent. This is commonly seen in sets of polynomials, where the degree of the polynomials can continue to increase without affecting the linear independence of the set.

5. Are all bases for a vector space linearly independent function sets?

Yes, all bases for a vector space are linearly independent function sets. A basis is a set of linearly independent vectors that span a vector space, meaning that any vector in the space can be expressed as a linear combination of the basis vectors. Therefore, by definition, a basis must be linearly independent.

Similar threads

Replies
6
Views
856
Replies
2
Views
1K
  • General Math
Replies
1
Views
901
Replies
4
Views
429
Replies
6
Views
1K
  • Linear and Abstract Algebra
Replies
5
Views
1K
  • Calculus and Beyond Homework Help
Replies
19
Views
975
  • Calculus and Beyond Homework Help
Replies
1
Views
301
  • Differential Equations
Replies
1
Views
668
Replies
3
Views
1K
Back
Top