Solve Difference Equation: ΔP = e^P

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SUMMARY

The discussion centers on solving the difference equation ΔP = e^P, where ΔP is defined as P_2 - P_1. Participants explore converting this discrete equation into a continuous time expression, ultimately leading to the differential equation dP/dt = e^P. The conversation highlights the explosive growth of the function, as demonstrated by numerical examples, and emphasizes the need for context or initial values to understand the behavior of the equation. The conclusion is that without constraints, the function diverges rapidly.

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Cyrus
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I have a difference equation which is given as:

ΔP = e^P [1]

where we can re-write ΔP as: Δ P = P_2 - P_1, where the subscripts indicate two distinct discrete time indices.

What I would like to do: is to convert this into a continuous time expression and solve it, if possible.

In order to help give some insight, I will solve a similar type of problem where I know the solution.

ΔP = c_1 [2]

Note here, that in all cases we are running the recursive algorithm at a fixed data rate. Therefore, I can rewrite equation [1] as:

Δ P = P_2 - P_1 = c_2 ⋅ Δ t

where c_1 = c_2 ⋅ Δ t

This allows me to divide both sides by [equation] \Delta t [/equation]:

ΔP /Δt = c_2

And in the limit:

dP/dt = c_2

which then becomes:

P(t) - P(0) = c_2⋅(t - t_0)

And so the result is that this recursive equation [2] gives us a linear ramp if we were to implement it. What I am trying to do for equation [1] is figure out what this expression will look like.
 
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To which discrete time index is e^P refering?
 
You can approximate it by a "continuous derivative" with different results depending upon what "continuity" assumptions you make.
 
Cyrus said:
$$\Delta P = P_2 - P_1 = e^{P_1}$$
looks explosive if I try a few numbers:
Code:
n   P1           exp(P1)         P2
0   0.0001       1.0001      1.0002
1   1.0002       2.718826    3.719026
2   3.719026    41.2242     44.94323
3  44.94323      3.3E+19     3.3E+19
I find it hard to believe this is what's intended ... ?
 
Sorry all I forgot it's e^p1
 
BvU said:
looks explosive if I try a few numbers:
Code:
n   P1           exp(P1)         P2
0   0.0001       1.0001      1.0002
1   1.0002       2.718826    3.719026
2   3.719026    41.2242     44.94323
3  44.94323      3.3E+19     3.3E+19
I find it hard to believe this is what's intended ... ?

Good point, it's actually e^(p1 - c_3)

Which is a negative exponential, but we can rewrite that as e^p1 / e^c_3 so I left out the denominator since it was a constant value. c_3 is just a constant
 
HallsofIvy said:
You can approximate it by a "continuous derivative" with different results depending upon what "continuity" assumptions you make.

I'm open to any solutions that are simple with some reasonable assumptions. :-)
 
Cyrus said:
I'm open to any solutions that are simple with some reasonable assumptions. :-)
Hey look who's back :smile:
 
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Cyrus said:
Good point, it's actually e^(p1 - c_3)

Which is a negative exponential, but we can rewrite that as e^p1 / e^c_3 so I left out the denominator since it was a constant value. c_3 is just a constant
Still explodes, at some point P1 > c3.
Let C3 = 100 and P1 start at 1:

upload_2016-2-11_10-23-51.png
 
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  • #10
It looks like you have, for a fixed data rate
##\Delta P = e^P,## so ##P_2 - P_1 = e^{P_1 } \Delta t##?
In the same way you simplified the first problem,

##\frac{\delta P}{\delta t} = \frac{ P(t+\delta t) - P(t) }{ \delta t} = e^{ P(t) }.##
In the limit, this will give you ## P' = e^{P(t)} ##

As BvU has pointed out, no matter what your starting P_1 is, your function will eventually blow up. Is there some other context for this problem? Maybe some initial values?
 

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