First variation of convolution of two nonlinear functions

In summary, the conversation discusses a new variational principle presented in a paper and how the approach is used in deriving the equation of motion for a Duffing oscillator. The functional setup and the use of integration by parts for convolutions are mentioned, but there is difficulty in incorporating a nonlinear term. The question is posed if there is a way to manipulate the convolutions to get the desired dynamics.
  • #1
rrhd
2
0
A new variational principle is presented in this paper: http://arxiv.org/ftp/arxiv/papers/1112/1112.2286.pdf

When trying to derive something like the equation of motion of a Duffing oscillator, I take the following approach:

Set up the functional as such:
$$
\mathcal{I}\left(t,x(t),\dot{x}(t)\right) = \frac{1}{2}\left[\dot{x} * \dot{x} \right]+\frac{\beta}{2}\left[x * x \right]+\frac{\alpha}{4}\left[x^2 * x^2 \right]
$$

Where:
$$
\left[f * g\right]=\int^{t}_{0}f\left(t-\tau\right)g\left(\tau\right)\,\text{d}\tau
$$

Now, normally, I would take the first variation of the expression for $\mathcal{I}$ and then collect the similar variations $\delta x$ and equate their coefficient to zero, but it's not immediately obvious how one would do that with this expression:


$$
\mathcal{I}= \left[\delta\dot{x} * \dot{x} \right]+\beta\left[\delta x * x \right]+\alpha\left[x \delta x * x^2 \right]
$$

Using the integration by parts principle for convolutions, we get:

$$
\mathcal{I}= \left[\delta x * \left(\ddot{x}+\beta x\right) \right]+\left[x \delta x * x^2 \right]+\left.\delta x \dot{x}\right]^{t}_{0}
$$

Where it not for the nonlinear term in the last term of $\mathcal{I}$, I would have the full dynamics, namely:
$$
\ddot{x}+\beta x=0
$$

Although the dynamics should be:

$$
\ddot{x}+\beta x+\alpha x^3 =0
$$

But there is no way I can see of incorporating the convolution term with $x\delta x$ into the other terms convolved with $\delta x$.

I've tried playing around with the properties of convolutions and so far have not found a solution.

Is there a way to manipulate this convolutions to get the desired dynamics?
 
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  • #2
Any method that would enable me to reexpress:
$$
\left[x \delta x * x^2 \right]
$$

As the variation convolved with something else would work.
 

Related to First variation of convolution of two nonlinear functions

What is the first variation of convolution of two nonlinear functions?

The first variation of convolution of two nonlinear functions refers to the measure of change in the output of the convolution operation when there is a small change in the input functions. It is a way to quantify the sensitivity of the convolution to small changes in the input.

How is the first variation of convolution calculated?

The first variation of convolution is calculated by taking the partial derivatives of the convolution integral with respect to each input function and then evaluating the result at a specific point. This results in a vector of values that represents the sensitivity of the convolution at that point.

What is the significance of the first variation of convolution?

The first variation of convolution is significant because it allows us to understand how the output of the convolution changes with respect to changes in the input functions. This can help us analyze and optimize the performance of convolutional neural networks, which heavily rely on convolutions.

Can the first variation of convolution be negative?

Yes, the first variation of convolution can be negative. This means that the convolution is relatively insensitive to changes in the input functions at that specific point.

Are there any applications of the first variation of convolution?

Yes, the first variation of convolution has various applications in fields such as signal processing, image processing, and machine learning. It is commonly used in the analysis and optimization of convolutional neural networks, as well as in the development of new convolutional algorithms.

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