Expanding Bilinear Map Power Series with Matrix/Vector Input

In summary: T(1 - A)x) instead …that's 1/(xT(1/∑An)x) …no, i don't see how you can ever get those xs from the bottom to the topOops. I forgot to write 1/(x^T (1-A)x). So what's the general procedure for this sort of problem?I'm working with a Gaussian function e^{-{\bf x^{T}}A{\bf x}} and I'd like to expand that in A?Any suggestions?
  • #1
unchained1978
93
0
I'm trying to expand a function of a bilinear map in a power series [itex]f({\bf x^{T}Ax})[/itex]. It isn't quite a matrix function because it takes a matrix and a vector and maps them into a scalar. I'd like to expand it into powers of [itex]\bf A[/itex], but still preserve the function as a scalar. As far as I can tell, a matrix power series takes a matrix as an input (like this one) but outputs a matrix (unlike this problem). I'm not sure how to proceed.
 
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  • #2
hi unchained1978! :smile:

if A = ∑ Bn, then xTAx = ∑ xTBnx :wink:

(btw, i don't bother to write matrices in bold: i write vectors bold, scalars small plain, and matrices big plain :wink:)
 
  • #3
Offtopic...

tiny-tim said:
(btw, i don't bother to write matrices in bold: i write vectors bold, scalars small plain, and matrices big plain :wink:)

I use the convention from linear analysis: scalars are lower case Greek, vectors are lower case Latin, and operators are upper case Latin. No need to worry about boldface :wink:
 
  • #4
tiny-tim said:
hi unchained1978! :smile:

if A = ∑ Bn, then xTAx = ∑ xTBnx :wink:

(btw, i don't bother to write matrices in bold: i write vectors bold, scalars small plain, and matrices big plain :wink:)

I'm not sure I understand how that relates to my problem. Let's say I have a function [itex]f({\bf x^{T}}A{\bf x})=\frac{1}{{\bf x^{T}}A{\bf x}}[/itex]. Are you saying this is the same as [itex]{\bf x^{T}}(1+A^{2}+A^{3}+...+A^{n}){\bf x}[/itex]?
 
  • #5
unchained1978 said:
I'm not sure I understand how that relates to my problem. Let's say I have a function [itex]f({\bf x^{T}}A{\bf x})=\frac{1}{{\bf x^{T}}A{\bf x}}[/itex]. Are you saying this is the same as [itex]{\bf x^{T}}(1+A^{2}+A^{3}+...+A^{n}){\bf x}[/itex]?

hmm … i didn't realize that's what you meant :redface:

let's use 1/(xT(1 - A)x) instead …

that's 1/(xT(1/∑An)x) …

no, i don't see how you can ever get those xs from the bottom to the top
 
  • #6
Oops. I forgot to write 1/(x^T (1-A)x). So what's the general procedure for this sort of problem? I'm working with a Gaussian function [itex]e^{-{\bf x^{T}}A{\bf x}}[/itex] and I'd like to expand that in A? Any suggestions?
 

1. What is a bilinear map power series?

A bilinear map power series is a mathematical function that takes in two inputs, typically in the form of a matrix and a vector, and produces an output by multiplying the two inputs together. The output is often a scalar value, but can also be a vector or matrix depending on the specific function being used.

2. How does expanding a bilinear map power series work?

Expanding a bilinear map power series involves taking the original function and rewriting it as a sum of power series, where each term represents a different degree of the input variables. This allows for a more efficient way of evaluating the function and can also provide insights into the properties of the function.

3. What is the purpose of using matrix and vector input in a bilinear map power series?

The use of matrix and vector input in a bilinear map power series allows for a more general and flexible function that can be applied to a wide range of mathematical problems. It also allows for the representation of higher-dimensional data and more complex relationships between variables.

4. Can bilinear map power series be used for real-world applications?

Yes, bilinear map power series have many practical applications in fields such as signal processing, machine learning, and cryptography. They can be used to model and analyze complex systems, make predictions, and solve optimization problems.

5. Are there any limitations to using bilinear map power series with matrix and vector input?

While bilinear map power series are a powerful tool in mathematics and science, they do have some limitations. These include potential convergence issues, difficulty in finding closed-form solutions for some functions, and the need for careful selection of input variables to avoid numerical instability.

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