Could someone please explain this? (HW-related)

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Homework Help Overview

The discussion revolves around the conversion of a system of differential equations into a linearized form using the Jacobian matrix. The original poster seeks clarification on the reasoning behind this process, particularly in the context of approximating nonlinear functions.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants explore the idea of linearizing a nonlinear system through Taylor expansion. Questions arise regarding the specific conditions, such as the initial point of approximation, and the nature of the functions involved.

Discussion Status

There is an ongoing exploration of the concept, with some participants providing insights into the mathematical foundations of the linearization process. The discussion includes various interpretations of the problem, but no consensus has been reached.

Contextual Notes

Participants note the importance of the initial point in the approximation and the assumptions related to the functions F and G being nonlinear. The original poster expresses a desire for deeper understanding, indicating a learning-focused approach.

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Homework Statement



So the last thing we got to learn before studying for finals ...

Homework Equations



... was converting something like

dx/dt = F(x,y)
dy/dt = G(x,y)

into a ...

The Attempt at a Solution



... system of equations like (x' y')T = J * (x y)T,

where J is the Jacobian Matrix [ (∂F/∂x ∂G/∂x)T , (∂D/∂y ∂G/∂y)T ].

I'm just wondering why exactly that works. Could someone show me a proof or something? Being the weird dude I am, I need to know these things. :wink:
 
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hm, perhaps you're approximating a nonlinear system by a linear. I'm thinking 'taylor expansion', but then this may be my response to everything. do you happen to know if the initial point is [F(x_o,y_o),G(x_o,y_o)]=[0,0]? that might help clarify things a bit...
 
xaos is right, this "conversion" of the problem is a local approximation of your F,G functions to an linear (or affine) function. In general the set of equations you give is not linear, the only way to "linearize" it is to do this Taylor expansion (assuming the F and G were not already linear).
 
Alright. I'll just roll with it.
 
In other words, at some point (x_0,y_0), F(x,y) is replaced by its "tangent plane approximation",
\frac{\partial F}{\partial x}(x_0,y_0)(x- x_0)+ \frac{\partial F(x_0, y_0)}{\partial y}(y- y_0)+ F(x_0, y_0)
and G(x, y) is replaced by its "tangent plane approximation",
\frac{\partial G}{\partial x}(x_0,y_0)(x- x_0)+ \frac{\partial G}{\partial y}(x_0, y_0)(y- y_0)+ G(x_0, y_0)

Now, you have the two equations
\frac{dx}{dt}= \frac{\partial F}{\partial x}(x_0,y_0)(x- x_0)+ \frac{\partial F(x_0, y_0)}{\partial y}(y- y_0)+ F(x_0, y_0)
\frac{dy}{dt}= \frac{\partial G}{\partial x}(x_0,y_0)(x- x_0)+ \frac{\partial G}{\partial y}(x_0, y_0)(y- y_0)+ G(x_0, y_0)

which we can write as the matrix equation
\frac{d}{dt}\begin{pmatrix}x \\ y\end{pmatrix}= \begin{pmatrix}\frac{\partial F}{\partial x}(x_0, y_0) & \frac{\partial F}{\partial y}(x_0, y_0) \\ \frac{\partial G}{\partial x}(x_0, y_0) & \frac{\partial G}{\partial y}(x_0, y_0)\end{pmatrix}\begin{pmatrix}x- x_0 \\ y- y_0\end{pmatrix}+ \begin{pmatrix}F(x_0, y_0) \\ G(x_0, y_0)\end{pmatrix}
 

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