Can a Neumann Series Be Proposed for the Resolvent Kernel in Iterative Methods?

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In summary, the conversation discusses an integral equation with a known Kernel and a small eigenvalue, "lambda". The question is whether a "Neumann series" can be proposed for the resolvent Kernel in order to solve the equation, or if the iteration procedure is enough. The conversation also includes a joke about the pronunciation of "lambda" and the suggestion that the person could be a successful Hollywood comedian instead of wasting time on this platform.
  • #1
eljose
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let be the integral equation:

[tex] f(x)=\lambda \int_{0}^{1}dyK(x,y)f(y) [/tex]

where the Kernel is known and "lambada" is an small eigenvalue... the question is if i want to solve i propose the iterative scheme:

[tex] f_{n+1} (x)=\lambda \int_{0}^{1}dyK(x,y)f_n(y) [/tex]

My question is if in this case i can propose a "Neumann series" for the resolvent Kernel R(x,y) in the form...

[tex] R= \sum_{n=0}^{\infty} \lambda ^ n K^{n} [/tex]

for K^n the n-th iterated kernel since the equation is HOmogeneus (all the functions involved except the Kernel are unknown) or if we have enough with the iteration procedure to solve the equation..thanks.
 
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  • #2
"lambda" is an eigenvalue. "Lambada" is a dance!
 
  • #3
HallsofIvy said:
"lambda" is an eigenvalue. "Lambada" is a dance!
:rofl: :rofl: :rofl:
 
  • #4
- Ooooh...¡what a wonderful and marvelous joke¡¡..I ask myself daily why you are here wasting your time when you could be a "millionaire" Hollywood comediant like Eddie Murphy or appear on "Saturday Night LIfe"...
 
  • #5
I keep asking myself that!
 

What are iterative methods?

Iterative methods are numerical techniques used to approximate the solution to a mathematical problem by repeatedly applying a set of operations on an initial guess until a desired level of accuracy is achieved. They are commonly used in scientific computing, especially for solving large and complex systems of equations.

What are the advantages of using iterative methods?

One major advantage of iterative methods is that they are often more efficient and require less memory compared to direct methods, especially for large systems. They also allow for a trade-off between accuracy and computation time, as the accuracy can be controlled by the number of iterations performed.

What types of problems are typically solved using iterative methods?

Iterative methods are commonly used to solve problems involving systems of linear equations, such as those arising in optimization, physics, engineering, and economics. They can also be used for solving eigenvalue problems, differential equations, and other types of mathematical problems.

What are some common iterative methods?

Some common iterative methods include the Jacobi method, Gauss-Seidel method, successive over-relaxation (SOR) method, and conjugate gradient method. Each of these methods have their own advantages and are suited for different types of problems.

What are the limitations of iterative methods?

One limitation of iterative methods is that they may not always converge to a solution, especially if the problem is ill-conditioned or if the initial guess is not close enough to the true solution. In addition, the rate of convergence may be slow for some problems, requiring a large number of iterations to achieve the desired accuracy.

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