Approximating a number using linearization methods

In summary, the goal is to approximate the number \frac{-1+\sqrt{5}}{2} using linearization methods. However, this number can be approximated more accurately by using Newton-Raphson.
  • #1
MrCreamer
6
0

Homework Statement


The goal is to approximate the number [itex]\frac{-1+\sqrt{5}}{2}[/itex] using linearization methods.

Homework Equations


This number is a solution to x[itex]^{2}[/itex]=1-x

The Attempt at a Solution


I was told to use f(x)= x[itex]^{2}[/itex]+x-1 with the Newton method to find x[itex]_{1}[/itex],x[itex]_{2}[/itex],x[itex]_{3}[/itex],x[itex]_{4}[/itex] at x[itex]_{0}[/itex]=2;

The general equation was [itex]\frac{x^{2}_{n}+1}{2x_{n}+1}[/itex] thus yielding:
x[itex]_{1}[/itex] = 1
x[itex]_{2}[/itex] = [itex]\frac{2}{3}[/itex]
x[itex]_{3}[/itex] = [itex]\frac{13}{21}[/itex]
x[itex]_{4}[/itex] = [itex]\frac{610}{987}[/itex]

Using my calculator [itex]\frac{610}{987}[/itex] is extremely close to [itex]\frac{-1+\sqrt{5}}{2}[/itex].
 
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  • #2
MrCreamer said:

Homework Statement


The goal is to approximate the number [itex]\frac{-1+\sqrt{5}}{2}[/itex] using linearization methods.

Homework Equations


This number is a solution to x[itex]^{2}[/itex]=1-x

The Attempt at a Solution


I was told to use f(x)= x[itex]^{2}[/itex]+x-1 with the Newton method to find x[itex]_{1}[/itex],x[itex]_{2}[/itex],x[itex]_{3}[/itex],x[itex]_{4}[/itex] at x[itex]_{0}[/itex]=2;

The general equation was [itex]\frac{x^{2}_{n}+1}{2x_{n}+1}[/itex] thus yielding:
x[itex]_{1}[/itex] = 1
x[itex]_{2}[/itex] = [itex]\frac{2}{3}[/itex]
x[itex]_{3}[/itex] = [itex]\frac{13}{21}[/itex]
x[itex]_{4}[/itex] = [itex]\frac{610}{987}[/itex]

Using my calculator [itex]\frac{610}{987}[/itex] is extremely close to [itex]\frac{-1+\sqrt{5}}{2}[/itex].

So what is your question?
 
  • #3
How do I approximate [itex]\frac{-1+\sqrt{5}}{2}[/itex] without using a calculator using the methods of linearization
 
  • #4
MrCreamer said:
How do I approximate [itex]\frac{-1+\sqrt{5}}{2}[/itex] without using a calculator using the methods of linearization

I guess that depends on what you mean by "methods of linearization". Newton's law uses successive approximations, each of which use tangents to the curve to approximate the root. That seems like a linearization method to me.
 
  • #5
MrCreamer said:
How do I approximate [itex]\frac{-1+\sqrt{5}}{2}[/itex] without using a calculator using the methods of linearization

First option is to accept the fraction as is.
This is probably intended.
The fraction is the approximation.
No need to convert it to a decimal number.

Second option is to calculate the fraction by hand instead of with a calculator...

Third option, which is perhaps more what you want to know, is to estimate the fraction.
610/987 has a denominator that is 13 points below 1000. This is 1.3%.
So increase 610 by 1.3%, which is an increase of 8 to 618.
Then your fraction is:
$${610 \over 987} \approx {618 \over 1000} = 0.618$$
Is that close to what your calculator tells you?
 
  • #6
To be more specific, I am supposed to approximate this number using linearization and differentials i.e

i) L(x) ≈ f(a)+[itex]\frac{df(a)}{dx}[/itex](x-a) when f(x) ≈ L(x) only when x is close to a
ii) f(a+dx)≈f(a)+dy where dy=[itex]\frac{df(x)}{dx}[/itex]dx
 
  • #7
MrCreamer said:
To be more specific, I am supposed to approximate this number using linearization and differentials i.e

i) f(x) ≈ f(a)+[itex]\frac{df(a)}{dx}[/itex](x-a) when f(x) ≈ L(x) only when x is close to a
ii) f(a+dx)≈f(a)+dy where dy=[itex]\frac{df(x)}{dx}[/itex]dx

Yep. That's Newton-Raphson.

Suppose ##a## is your approximation xi and ##x## is your target.
Then ##f(x)## is zero (that's how you defined it).
From there you can deduce x, which will then be the next approximation xi+1.

In other words, this is exactly where the method of Newton-Raphson comes from.
 
  • #8
MrCreamer said:
To be more specific, I am supposed to approximate this number using linearization and differentials i.e

i) L(x) ≈ f(a)+[itex]\frac{df(a)}{dx}[/itex](x-a) when f(x) ≈ L(x) only when x is close to a
ii) f(a+dx)≈f(a)+dy where dy=[itex]\frac{df(x)}{dx}[/itex]dx

Well, ##x=4## is a point where the square root is easy to calculate so try$$
f(x) = -\frac 1 2 + \frac{\sqrt{x}} 2$$and use the linear approximation near ##x=4##.
 

What is linearization?

Linearization is a process in mathematics where a non-linear function is approximated by a linear function in order to simplify calculations or analysis.

Why do we use linearization methods to approximate numbers?

Linearization methods are useful for approximating numbers because they allow us to simplify complex mathematical functions and make them easier to analyze. This can be especially helpful when dealing with large numbers or complicated equations.

What are some common linearization methods?

Some commonly used linearization methods include linear approximation, Taylor series, and tangent line approximation. These methods involve using linear functions to approximate the values of non-linear functions at a specific point or interval.

What is the difference between linearization and linear regression?

Linearization is a method for approximating a non-linear function using a linear function, while linear regression is a statistical method used to find the best-fit line that represents a relationship between two variables. Linearization is often used in conjunction with linear regression to simplify the data analysis process.

How accurate are linearization methods in approximating numbers?

The accuracy of linearization methods in approximating numbers depends on the complexity of the original non-linear function and the specific method used. In general, the accuracy of linearization increases as the number of linear terms used in the approximation increases.

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