Can I linearize this equation?

In summary, jason is trying to approximate a sinus function in the frequency domain and he is unsure of what form it should be in. He would like help with this.
  • #1
Jarfi
384
12
By using the laplace transform:

$f(t)=sin(Φ(t))$

I want it in the form:

F(S)/Φ(S)

The purpose is to linearize it in order to put it into a larger transfer function, so far my only solution is to simplify it using taylor expansion.
 
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  • #2
Yes, you can linearize - just Taylor expand about the relavent point. However, since you really care about the Laplace transform of this, the linear approximation will only help you if ##\phi(t) ## changes very little for ##0<t<\infty##.
 
  • #3
jasonRF said:
Yes, you can linearize - just Taylor expand about the relavent point. However, since you really care about the Laplace transform of this, the linear approximation will only help you if ##\phi(t) ## changes very little for ##0<t<\infty##.
Taylor expansion the sin function would yield a polynomial of several orders, say I had two 3 order approximated sinus functions in series(with an output between them), then I have a 6th order polynomial, increasing complexity. So i was hoping for another solution.

Φ is from 0-45°
 
  • #4
I don't understand what you mean. A linear approximation is, by definition, linear. How would it be 6th order?

If you want a linear approximation, it obviously must be of the form ##\sin\phi(t) \approx a \, \phi(t) + b##. How you select ##a## and ##b## depends upon what criterion makes the most sense for the problem you are trying to solve. Unless you tell us what problem you are actually trying to solve I doubt I can help much more.

jason
 
  • #5
jasonRF said:
I don't understand what you mean. A linear approximation is, by definition, linear. How would it be 6th order?

If you want a linear approximation, it obviously must be of the form ##\sin\phi(t) \approx a \, \phi(t) + b##. How you select ##a## and ##b## depends upon what criterion makes the most sense for the problem you are trying to solve. Unless you tell us what problem you are actually trying to solve I doubt I can help much more.

jason

It's linear in the frequency domain, NOT in the time domain: My preferrence is exactly not to approximate it, but to convert it. I already know how to approximate-linearize a sinus function
 
  • #6
Jarfi said:
It's linear in the frequency domain, NOT in the time domain: My preferrence is exactly not to approximate it, but to convert it. I already know how to approximate-linearize a sinus function

Jarfi said:
By using the laplace transform:

$f(t)=sin(Φ(t))$

I want it in the form:

F(S)/Φ(S)

The purpose is to linearize it in order to put it into a larger transfer function, so far my only solution is to simplify it using taylor expansion.

I still don't know what you are asking - you use the word "it" a lot, and now it is clear that the word "it" may refer to different things in different places. So … what exactly are you trying to approximate and in what form? What do you mean by "convert it"? When you say linear, do you mean a linear function of ##\Phi(s)##, or a linear function of ##s##?

I would be happy to help if you answer these questions, or (probably better) just state a more explicit question that helps us understand what you are doing.

jason
 

1. Can I linearize any equation?

No, not every equation can be linearized. Linearization is only possible for equations that have a linear relationship between the variables. Non-linear equations cannot be linearized.

2. How do I linearize an equation?

To linearize an equation, you must manipulate it into the form of a straight line, y = mx + b. This can be done by rearranging terms, taking the logarithm, or using other mathematical techniques.

3. What are the benefits of linearizing an equation?

Linearizing an equation can make it easier to analyze and solve. It can also help to identify the relationship between variables and make predictions based on the data.

4. Can I linearize a set of data points?

Yes, you can use linear regression to find the best fit line for a set of data points. This is a common method for linearizing data in order to analyze it.

5. Are there any limitations to linearizing an equation?

Yes, linearization can only be used for equations with a linear relationship between variables. It also assumes that the data is accurate and follows a specific pattern, which may not always be the case in real-world scenarios.

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