Skip to main content

Calculus III - 3-Dimensional Space: Equations of Lines

In this section we need to take a look at the equation of a line in  R 3 R 3 . As we saw in the previous section the equation  y = m x + b y = m x + b  does not describe a line in  R 3 R 3 , instead it describes a plane. This doesn’t mean however that we can’t write down an equation for a line in 3-D space. We’re just going to need a new way of writing down the equation of a curve. So, before we get into the equations of lines we first need to briefly look at vector functions. We’re going to take a more in depth look at vector functions later. At this point all that we need to worry about is notational issues and how they can be used to give the equation of a curve. The best way to get an idea of what a vector function is and what its graph looks like is to look at an example. So, consider the following vector function. → r ( t ) = ⟨ t , 1 ⟩ r → ( t ) = ⟨ t , 1 ⟩ A vector function is a function that takes one or more variables, one in this case, and returns a vector. Note as we

Differential Equations - First Order: Bernoulli



In this section we are going to take a look at differential equations in the form,
y+p(x)y=q(x)yn
where p(x) and q(x) are continuous functions on the interval we’re working on and n is a real number. Differential equations in this form are called Bernoulli Equations.
First notice that if n=0 or n=1 then the equation is linear and we already know how to solve it in these cases. Therefore, in this section we’re going to be looking at solutions for values of n other than these two.
In order to solve these we’ll first divide the differential equation by yn to get,
yny+p(x)y1n=q(x)
We are now going to use the substitution v=y1n to convert this into a differential equation in terms of v. As we’ll see this will lead to a differential equation that we can solve.
We are going to have to be careful with this however when it comes to dealing with the derivative, y. We need to determine just what y is in terms of our substitution. This is easier to do than it might at first look to be. All that we need to do is differentiate both sides of our substitution with respect to x. Remember that both v and y are functions of x and so we’ll need to use the chain rule on the right side. If you remember your Calculus I you’ll recall this is just implicit differentiation. So, taking the derivative gives us,
v=(1n)yny
Now, plugging this as well as our substitution into the differential equation gives,
11nv+p(x)v=q(x)
This is a linear differential equation that we can solve for v and once we have this in hand we can also get the solution to the original differential equation by plugging v back into our substitution and solving for y.
Let’s take a look at an example.

Example 1 Solve the following IVP and find the interval of validity for the solution.y+4xy=x3y2y(2)=1,x>0

So, the first thing that we need to do is get this into the “proper” form and that means dividing everything by y2. Doing this gives,
y2y+4xy1=x3The substitution and derivative that we’ll need here is,
v=y1v=y2yWith this substitution the differential equation becomes,
v+4xv=x3So, as noted above this is a linear differential equation that we know how to solve. We’ll do the details on this one and then for the rest of the examples in this section we’ll leave the details for you to fill in. If you need a refresher on solving linear differential equations then go back to that section for a quick review.
Here’s the solution to this differential equation.
v4xv=x3μ(x)=e4xdx=e4ln|x|=x4(x4v)dx=x1dxx4v=ln|x|+cv(x)=cx4x4lnxNote that we dropped the absolute value bars on the x in the logarithm because of the assumption that x>0.
Now we need to determine the constant of integration. This can be done in one of two ways. We can can convert the solution above into a solution in terms of y and then use the original initial condition or we can convert the initial condition to an initial condition in terms of v and use that. Because we’ll need to convert the solution to y’s eventually anyway and it won’t add that much work in we’ll do it that way.
So, to get the solution in terms of y all we need to do is plug the substitution back in. Doing this gives,
y1=x4(clnx)At this point we can solve for y and then apply the initial condition or apply the initial condition and then solve for y. We’ll generally do this with the later approach so let’s apply the initial condition to get,
(1)1=c2424ln2c=ln2116Plugging in for c and solving for y gives,
y(x)=1x4(ln2116lnx)=16x4(1+16lnx16ln2)=16x4(1+16lnx2)Note that we did a little simplification in the solution. This will help with finding the interval of validity.
Before finding the interval of validity however, we mentioned above that we could convert the original initial condition into an initial condition for v. Let’s briefly talk about how to do that. To do that all we need to do is plug x=2 into the substitution and then use the original initial condition. Doing this gives,
v(2)=y1(2)=(1)1=1So, in this case we got the same value for v that we had for y. Don’t expect that to happen in general if you chose to do the problems in this manner.
Okay, let’s now find the interval of validity for the solution. First, we already know that x>0 and that means we’ll avoid the problems of having logarithms of negative numbers and division by zero at x=0. So, all that we need to worry about then is division by zero in the second term and this will happen where,
1+16lnx2=0lnx2=116x2=e116x=2e1161.8788The two possible intervals of validity are then,
0<x<2e1162e116<x<and since the second one contains the initial condition we know that the interval of validity is then 2e116<x<.
Here is a graph of the solution.
Let’s do a couple more examples and as noted above we’re going to leave it to you to solve the linear differential equation when we get to that stage.


Example 2 Solve the following IVP and find the interval of validity for the solution.y=5y+e2xy2y(0)=2

The first thing we’ll need to do here is multiply through by y2 and we’ll also do a little rearranging to get things into the form we’ll need for the linear differential equation. This gives,
y2y5y3=e2xThe substitution here and its derivative is,
v=y3v=3y2yPlugging the substitution into the differential equation gives,
13v5v=e2xv15v=3e2xμ(x)=e15xWe rearranged a little and gave the integrating factor for the linear differential equation solution. Upon solving we get,
v(x)=ce15x317e2xNow go back to y’s.
y3=ce15x317e2xApplying the initial condition and solving for c gives,
8=c317c=13917Plugging in c and solving for y gives,
y(x)=(139e15x3e2x17)13There are no problem values of x for this solution and so the interval of validity is all real numbers. Here’s a graph of the solution.
Example 3 Solve the following IVP and find the interval of validity for the solution.6y2y=xy4y(0)=2

First get the differential equation in the proper form and then write down the substitution.
6y4y2y3=xv=y3v=3y4yPlugging the substitution into the differential equation gives,
2v2v=xv+v=12xμ(x)=exAgain, we’ve rearranged a little and given the integrating factor needed to solve the linear differential equation. Upon solving the linear differential equation we have,
v(x)=12(x1)+cexNow back substitute to get back into y’s.
y3=12(x1)+cexNow we need to apply the initial condition and solve for c.
18=12+cc=58Plugging in c and solving for y gives,
y(x)=2(4x4+5ex)13Next, we need to think about the interval of validity. In this case all we need to worry about it is division by zero issues and using some form of computational aid (such as Maple or Mathematica) we will see that the denominator of our solution is never zero and so this solution will be valid for all real numbers.
Here is a graph of the solution.
To this point we’ve only worked examples in which n was an integer (positive and negative) and so we should work a quick example where n is not an integer.



Example 4

Solve the following IVP and find the interval of validity for the solution.y+yxy=0y(1)=0

Let’s first get the differential equation into proper form.
y+1xy=y12y12y+1xy12=1The substitution is then,
v=y12v=12y12yNow plug the substitution into the differential equation to get,
2v+1xv=1v+12xv=12μ(x)=x12As we’ve done with the previous examples we’ve done some rearranging and given the integrating factor needed for solving the linear differential equation. Solving this gives us,
v(x)=13x+cx12In terms of y this is,
y12=13x+cx12Applying the initial condition and solving for c gives,
0=13+cc=13Plugging in for c and solving for y gives us the solution.
y(x)=(13x13x12)2=x32x32+19xNote that we multiplied everything out and converted all the negative exponents to positive exponents to make the interval of validity clear here. Because of the root (in the second term in the numerator) and the x in the denominator we can see that we need to require x>0 in order for the solution to exist and it will exist for all positive x’s and so this is also the interval of validity.
Here is the graph of the solution.

Comments

Popular posts from this blog

Digital Signal Processing - Basic Continuous Time Signals

To test a system, generally, standard or basic signals are used. These signals are the basic building blocks for many complex signals. Hence, they play a very important role in the study of signals and systems. Unit Impulse or Delta Function A signal, which satisfies the condition,   δ ( t ) = lim ϵ → ∞ x ( t ) δ ( t ) = lim ϵ → ∞ x ( t )   is known as unit impulse signal. This signal tends to infinity when t = 0 and tends to zero when t ≠ 0 such that the area under its curve is always equals to one. The delta function has zero amplitude everywhere except at t = 0. Properties of Unit Impulse Signal δ(t) is an even signal. δ(t) is an example of neither energy nor power (NENP) signal. Area of unit impulse signal can be written as; A = ∫ ∞ − ∞ δ ( t ) d t = ∫ ∞ − ∞ lim ϵ → 0 x ( t ) d t = lim ϵ → 0 ∫ ∞ − ∞ [ x ( t ) d t ] = 1 Weight or strength of the signal can be written as; y ( t ) = A δ ( t ) y ( t ) = A δ ( t ) Area of the weighted impulse signal can

Differential Equations - Systems: Solutions

Now that we’ve got some of the basics out of the way for systems of differential equations it’s time to start thinking about how to solve a system of differential equations. We will start with the homogeneous system written in matrix form, → x ′ = A → x (1) (1) x → ′ = A x → where,  A A  is an  n × n n × n  matrix and  → x x →  is a vector whose components are the unknown functions in the system. Now, if we start with  n = 1 n = 1 then the system reduces to a fairly simple linear (or separable) first order differential equation. x ′ = a x x ′ = a x and this has the following solution, x ( t ) = c e a t x ( t ) = c e a t So, let’s use this as a guide and for a general  n n  let’s see if → x ( t ) = → η e r t (2) (2) x → ( t ) = η → e r t will be a solution. Note that the only real difference here is that we let the constant in front of the exponential be a vector. All we need to do then is plug this into the differential equation and see what we get. First notice that

Calculus III - 3-Dimensional Space: Equations of Lines

In this section we need to take a look at the equation of a line in  R 3 R 3 . As we saw in the previous section the equation  y = m x + b y = m x + b  does not describe a line in  R 3 R 3 , instead it describes a plane. This doesn’t mean however that we can’t write down an equation for a line in 3-D space. We’re just going to need a new way of writing down the equation of a curve. So, before we get into the equations of lines we first need to briefly look at vector functions. We’re going to take a more in depth look at vector functions later. At this point all that we need to worry about is notational issues and how they can be used to give the equation of a curve. The best way to get an idea of what a vector function is and what its graph looks like is to look at an example. So, consider the following vector function. → r ( t ) = ⟨ t , 1 ⟩ r → ( t ) = ⟨ t , 1 ⟩ A vector function is a function that takes one or more variables, one in this case, and returns a vector. Note as we

Differential Equations - First Order: Modeling - i

We now move into one of the main applications of differential equations both in this class and in general. Modeling is the process of writing a differential equation to describe a physical situation. Almost all of the differential equations that you will use in your job (for the engineers out there in the audience) are there because somebody, at some time, modeled a situation to come up with the differential equation that you are using. This section is not intended to completely teach you how to go about modeling all physical situations. A whole course could be devoted to the subject of modeling and still not cover everything! This section is designed to introduce you to the process of modeling and show you what is involved in modeling. We will look at three different situations in this section : Mixing Problems, Population Problems, and Falling Objects. In all of these situations we will be forced to make assumptions that do not accurately depict reality in most cases, but wi

Digital Signal Processing - Miscellaneous Signals

There are other signals, which are a result of operation performed on them. Some common type of signals are discussed below. Conjugate Signals Signals, which satisfies the condition  x ( t ) = x ∗ ( − t ) are called conjugate signals. Let  x ( t ) = a ( t ) + j b ( t ) So,  x ( − t ) = a ( − t ) + j b ( − t ) And  x ∗ ( − t ) = a ( − t ) − j b ( − t ) By Condition,  x ( t ) = x ∗ ( − t ) If we compare both the derived equations 1 and 2, we can see that the real part is even, whereas the imaginary part is odd. This is the condition for a signal to be a conjugate type. Conjugate Anti-Symmetric Signals Signals, which satisfy the condition  x ( t ) = − x ∗ ( − t ) are called conjugate anti-symmetric signal Let  x ( t ) = a ( t ) + j b ( t ) So  x ( − t ) = a ( − t ) + j b ( − t ) And  x ∗ ( − t ) = a ( − t ) − j b ( − t ) − x ∗ ( − t ) = − a ( − t ) + j b ( − t ) By Condition  x ( t ) = − x ∗ ( − t ) Now, again compare, both the equations just as w

Differential Equations - Systems: Repeated Eigenvalues - i

This is the final case that we need to take a look at. In this section we are going to look at solutions to the system, → x ′ = A → x x → ′ = A x → where the eigenvalues are repeated eigenvalues. Since we are going to be working with systems in which  A A  is a  2 × 2 2 × 2  matrix we will make that assumption from the start. So, the system will have a double eigenvalue,  λ λ . This presents us with a problem. We want two linearly independent solutions so that we can form a general solution. However, with a double eigenvalue we will have only one, → x 1 = → η e λ t x → 1 = η → e λ t So, we need to come up with a second solution. Recall that when we looked at the double root case with the second order differential equations we ran into a similar problem. In that section we simply added a  t t  to the solution and were able to get a second solution. Let’s see if the same thing will work in this case as well. We’ll see if → x = t e λ t → η x → = t e λ t η → will also be a

Differential Equations - Systems: Repeated Eigenvalues - ii

Example 3  Solve the following IVP. → x ′ = ( − 1 3 2 − 1 6 − 2 ) → x → x ( 2 ) = ( 1 0 ) x → ′ = ( − 1 3 2 − 1 6 − 2 ) x → x → ( 2 ) = ( 1 0 ) First the eigenvalue for the system. det ( A − λ I ) = ∣ ∣ ∣ ∣ − 1 − λ 3 2 − 1 6 − 2 − λ ∣ ∣ ∣ ∣ = λ 2 + 3 λ + 9 4 = ( λ + 3 2 ) 2 ⇒ λ 1 , 2 = − 3 2 det ( A − λ I ) = | − 1 − λ 3 2 − 1 6 − 2 − λ | = λ 2 + 3 λ + 9 4 = ( λ + 3 2 ) 2 ⇒ λ 1 , 2 = − 3 2 Now let’s get the eigenvector. ( 1 2 3 2 − 1 6 − 1 2 ) ( η 1 η 2 ) = ( 0 0 ) ⇒ 1 2 η 1 + 3 2 η 2 = 0 η 1 = − 3 η 2 ( 1 2 3 2 − 1 6 − 1 2 ) ( η 1 η 2 ) = ( 0 0 ) ⇒ 1 2 η 1 + 3 2 η 2 = 0 η 1 = − 3 η 2 → η = ( − 3 η 2 η 2 ) η 2 ≠ 0 → η ( 1 ) = ( − 3 1 ) η 2 = 1 η → = ( − 3 η 2 η 2 ) η 2 ≠ 0 η → ( 1 ) = ( − 3 1 ) η 2 = 1 Now find  → ρ ρ → , ( 1 2 3 2 − 1 6 − 1 2 ) ( ρ 1 ρ 2 ) = ( − 3 1 ) ⇒ 1 2 ρ 1 + 3 2 ρ 2 = − 3 ρ 1 = − 6 − 3 ρ 2 ( 1 2 3 2 − 1 6 − 1 2 ) ( ρ 1 ρ 2 ) = ( − 3 1 ) ⇒ 1 2 ρ 1 + 3 2 ρ 2 = − 3 ρ 1 = − 6 − 3 ρ 2 → ρ = ( − 6 − 3 ρ 2 ρ 2 ) ⇒ → ρ = ( − 6 0 ) if  ρ 2 = 0 ρ → = ( − 6 − 3 ρ

Differential Equations - Basic Concepts: Definitions

Differential Equation The first definition that we should cover should be that of  differential equation . A differential equation is any equation which contains derivatives, either ordinary derivatives or partial derivatives. There is one differential equation that everybody probably knows, that is Newton’s Second Law of Motion. If an object of mass  m m  is moving with acceleration  a a  and being acted on with force  F F  then Newton’s Second Law tells us. F = m a (1) (1) F = m a To see that this is in fact a differential equation we need to rewrite it a little. First, remember that we can rewrite the acceleration,  a a , in one of two ways. a = d v d t OR a = d 2 u d t 2 (2) (2) a = d v d t OR a = d 2 u d t 2 Where  v v  is the velocity of the object and  u u  is the position function of the object at any time  t t . We should also remember at this point that the force,  F F  may also be a function of time, velocity, and/or position. So, with all these things in

Differential Equations - Laplace Transforms: Table

f ( t ) = L − 1 { F ( s ) } f ( t ) = L − 1 { F ( s ) } F ( s ) = L { f ( t ) } F ( s ) = L { f ( t ) }  1 1 s 1 s e a t e a t 1 s − a 1 s − a t n , n = 1 , 2 , 3 , … t n , n = 1 , 2 , 3 , … n ! s n + 1 n ! s n + 1 t p t p ,  p > − 1 p > − 1 Γ ( p + 1 ) s p + 1 Γ ( p + 1 ) s p + 1 √ t t √ π 2 s 3 2 π 2 s 3 2 t n − 1 2 , n = 1 , 2 , 3 , … t n − 1 2 , n = 1 , 2 , 3 , … 1 ⋅ 3 ⋅ 5 ⋯ ( 2 n − 1 ) √ π 2 n s n + 1 2 1 ⋅ 3 ⋅ 5 ⋯ ( 2 n − 1 ) π 2 n s n + 1 2 sin ( a t ) sin ⁡ ( a t ) a s 2 + a 2 a s 2 + a 2 cos ( a t ) cos ⁡ ( a t ) s s 2 + a 2 s s 2 + a 2 t sin ( a t ) t sin ⁡ ( a t ) 2 a s ( s 2 + a 2 ) 2 2 a s ( s 2 + a 2 ) 2 t cos ( a t ) t cos ⁡ ( a t ) s 2 − a 2 ( s 2 + a 2 ) 2 s 2 − a 2 ( s 2 + a 2 ) 2 sin ( a t ) − a t cos ( a t ) sin ⁡ ( a t ) − a t cos ⁡ ( a t ) 2 a 3 ( s 2 + a 2 ) 2 2 a 3 ( s 2 + a 2 ) 2 sin ( a t ) + a t cos ( a t ) sin ⁡ ( a t ) + a t cos ⁡ ( a t ) 2 a s 2 ( s 2 + a 2 ) 2 2 a s 2 ( s 2 + a 2 ) 2 cos ( a t ) − a t sin ( a t ) cos ⁡ ( a t ) −