If f ( x ) is a polynomial satisfying f ′ ( x ) + 2 f ( x ) = x + 1 , where f : R → R . Find f ( 2 1 . 5 )
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You are using a huge theorem in analysis in order to apply your "linear operator" proof. In fact, you are also making a huge assumption that your function must be a smooth function .
IE What is the domain and range space of your linear operator L ? To justify that those are correct, you need some kind of representation theorem.
Hence I object to "Note the topic is algebra. Calculus solutions will be frowned.". I have changed the topic to calculus.
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Ok sir. In that sense if i was to make it correct I have to derive all the properties of linear algebra. So its better to be a calculus sum
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It's not just the "properties of linear algebra". In fact, that is the trivial part of doing the calculations.
To start off,
if
the domain space of
L
is "all differentiable functions", then what do you think is the range space of
L
? Note that it is possible for the derivative of a differentiable function to have an
essential discontinuity
, and so the function isn't just
L: {differentiable functions} to {polynomials}.
That is where the "theorem in analysis" comes in, which is that what you are currently saying is applying the
stone-weierstrass theorem
to conclude that the set of polynomials are dense in the differentiable functions, which is why the linear operator interpretation works with a basis of
{
x
n
}
. We then need to do more work, to get
L: {smooth functions} to {smooth functions}, where we use a basis of
{
x
n
}
to represent the space of smooth functions.
It would be a purely algebra question if you stated that f ( x ) is a polynomial function and allowed the algebraic use of ( x n ) ′ = n x n − 1 along with the linearity of derivatives. This gets past using the theorem that I stated above.
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@Calvin Lin – Thank you for ntroducing me to the that theorem, and the use of the derivative however brings the use of calculus. As we need to use the derivative of x n , we are introducing calculus there. So there isnt a pure algebraic method for these maybe.
Let S = x → ∞ lim e − x ∫ 0 x ∫ 0 x u − v e u − e v d u d v
S = x → ∞ lim e − x ∫ 0 x ∫ 0 x e v u − v e u − v − 1 d u d v
S = x → ∞ lim e − x k = 1 ∑ ∞ k ! 1 ∫ 0 x ∫ 0 x e v ( u − v ) k − 1 d u d v
S = x → ∞ lim e − x k = 1 ∑ ∞ k . k ! 1 ∫ 0 x e v [ ( x − v ) k − ( − v ) k ] d v
S = x → ∞ lim e − x k = 1 ∑ ∞ k . k ! 1 ∫ 0 x e v ( x − v ) k d v − k = 1 ∑ ∞ k . k ! 1 e − ∞ ∫ 0 ∞ e v ( − v ) k d v
S = x → ∞ lim e − x k = 1 ∑ ∞ k . k ! 1 ∫ 0 x e x . e − v v k d v
S = k = 1 ∑ ∞ k . k ! 1 ∫ 0 ∞ e − v v k d v
S = k = 1 ∑ ∞ k . k ! Γ ( k + 1 ) = k ≥ 1 ∑ k 1 = + ∞
This is a first order linear differential equation in standard form. The standard method for solving these is using the integrating factor method, where you multiply both sides of the equation y'+p(x)*y=q(x) by e^(integral of p(x)dx) in order for the LHS to look like the derivative of the product of two functions.
So, e^(2x) will be our integrating factor. After integrating the derivative product on the LHS, you're left with e^(2x) y = the integral of (e^(2x) (x+1))dx. Split the RHS integral into two parts. The integral of e^(2x)*x dx can be evaluated using integration by parts and letting u=x and dv = e^(2x)dx.
e^(2x) y= (1/2) x e^(2x) - integral ((1/2)e^(2x)dx) + (1/2)e^(2x) e^(2x) y = (1/2) x e^(2x)-(1/4)e^(2x)+(1/2)e^(2x) + C multiplying both sides by e^(-2x) yields: y= (1/2) x - (1/4) + (1/2) + C y= (1/2) x + (1/4)
Now, evaluating y(21.5)= (1/2)(43/2)+(1/4) = 11
Simple standard approach. This is how we avoid the assumption that the function is a polynomial.
Yes, it's like this ↑ , but I think there is a small typo in the penultimate row, I think it should be y = ( 1 / 2 ) x − ( 1 / 4 ) + ( 1 / 2 ) + C ⋅ e − 2 x . And, since y is a polynomial it must be C = 0 . And your reply is very good too... If someone wants more details he can visit Integrating factors in diferential equations and Differential equations with constant coefficients ... @Aditya Sharma , would you like to create with me a wiki about variable changes in differential equations, dealing for example Bernouilli equation, Riccati equation, and Euler equation and others strange changes? I start and you later can help me...
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Yes obviously, Please start creating one. The intermix of the topics make this hugely interesting. I will contribute to it surely. :)
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Thank you very much, I'll start very soon... When I think you can deal, for example, Bernouilli equation I can name you... If you don't agree, or you want to ask me some doubt or something, here is my adress gtemplado@hotmail.es, cheers and thank you, see you soon...
Guillermo, thank you! You're correct. I will try to contribute to the wiki! :)
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Thank you very much!...you and anyone are welcome if they want to contribute to the wiki . I'm going to try to start it today...
Another method could be to write y'+2y=x+1 and then solve for its characteristic equation, i.e. when the equation is homogeneous.
the characteristic equation is:
r+2=0 so the complementary solution is y=c1*e^(-2x), but the complementary solution is of the least importance because we need a particular solution.
The best guess for a particular solution is Ax+B. The particular solution's derivative is y_p' = A
Plugging these back into the original yields
Setting coefficients equal A+2(Ax+B) = x+1 A+2B=1 2A=1 A=1/2 B=1/4
So you have y_p = .5*x+.25
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A Linear Operator L is defined by the following two conditions :
{ L ( u + v ) = L ( u ) + L ( v ) L ( c u ) = c L ( u )
Naturally the differential operator satisfies both the Additivity & Homogeneity together called Linearity
So Naturally we could frame it as ( d x d + 2 ) f = x + 1 where f is a quadratic expression.
( d x d + 2 ) f = d x d ( a x 2 + b x + c ) + 2 a x 2 + 2 b x + 2 c = 2 a x 2 + ( 2 a + 2 b ) x + ( b + 2 c )
Conveniently [ ⎝ ⎛ 2 2 0 0 2 1 0 0 2 ⎠ ⎞ ⎝ ⎛ a b c ⎠ ⎞ ] B
where a x 2 + b x + c = [ ⎝ ⎛ a b c ⎠ ⎞ ] B
So we get a equation as follows : ⎝ ⎛ 2 2 0 0 2 1 0 0 2 ⎠ ⎞ ⎝ ⎛ a b c ⎠ ⎞ = ⎝ ⎛ 0 1 1 ⎠ ⎞
Solving we get the solution vector ⎝ ⎛ 0 2 1 4 1 ⎠ ⎞
So f ( x ) = 4 2 x + 1 ⟹ f ( 2 1 . 5 ) = 1 1