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 - Series Solutions: Examples - i


Before we get into finding series solutions to differential equations we need to determine when we can find series solutions to differential equations. So, let’s start with the differential equation,
(1)p(x)y+q(x)y+r(x)y=0
This time we really do mean nonconstant coefficients. To this point we’ve only dealt with constant coefficients. However, with series solutions we can now have nonconstant coefficient differential equations. Also, in order to make the problems a little nicer we will be dealing only with polynomial coefficients.
Now, we say that x=x0 is an ordinary point if provided both
q(x)p(x)andr(x)p(x)
are analytic at x=x0. That is to say that these two quantities have Taylor series around x=x0. We are going to be only dealing with coefficients that are polynomials so this will be equivalent to saying that
p(x0)0
for most of the problems.
If a point is not an ordinary point we call it a singular point.
The basic idea to finding a series solution to a differential equation is to assume that we can write the solution as a power series in the form,
(2)y(x)=n=0an(xx0)n
and then try to determine what the an’s need to be. We will only be able to do this if the point x=x0, is an ordinary point. We will usually say that (2) is a series solution around x=x0.
Let’s start with a very basic example of this. In fact, it will be so basic that we will have constant coefficients. This will allow us to check that we get the correct solution.


Example 1 Determine a series solution for the following differential equation about x0=0.
y+y=0

Notice that in this case p(x)=1 and so every point is an ordinary point. We will be looking for a solution in the form,
y(x)=n=0anxnWe will need to plug this into our differential equation so we’ll need to find a couple of derivatives.
y(x)=n=1nanxn1y(x)=n=2n(n1)anxn2Recall from the power series review section on power series that we can start these at n=0 if we need to, however it’s almost always best to start them where we have here. If it turns out that it would have been easier to start them at n=0we can easily fix that up when the time comes around.
So, plug these into our differential equation. Doing this gives,
n=2n(n1)anxn2+n=0anxn=0The next step is to combine everything into a single series. To do this requires that we get both series starting at the same point and that the exponent on the x be the same in both series.
We will always start this by getting the exponent on the x to be the same. It is usually best to get the exponent to be an n. The second series already has the proper exponent and the first series will need to be shifted down by 2 in order to get the exponent up to an n. If you don’t recall how to do this take a quick look at the first review section where we did several of these types of problems.
Shifting the first power series gives us,
n=0(n+2)(n+1)an+2xn+n=0anxn=0Notice that in the process of the shift we also got both series starting at the same place. This won’t always happen, but when it does we’ll take it. We can now add up the two series. This gives,
n=0[(n+2)(n+1)an+2+an]xn=0Now recalling the fact from the power series review section we know that if we have a power series that is zero for all x(as this is) then all the coefficients must have been zero to start with. This gives us the following,
(n+2)(n+1)an+2+an=0,n=0,1,2,This is called the recurrence relation and notice that we included the values of n for which it must be true. We will always want to include the values of n for which the recurrence relation is true since they won’t always start at n = 0 as it did in this case.
Now let’s recall what we were after in the first place. We wanted to find a series solution to the differential equation. In order to do this, we needed to determine the values of the an’s. We are almost to the point where we can do that. The recurrence relation has two different an’s in it so we can’t just solve this for an and get a formula that will work for all n. We can however, use this to determine what all but two of the an’s are.
To do this we first solve the recurrence relation for the an that has the largest subscript. Doing this gives,
an+2=an(n+2)(n+1)n=0,1,2,Now, at this point we just need to start plugging in some value of n and see what happens,
n=0a2=a0(2)(1)n=1a3=a1(3)(2)
 
n=2a4=a2(4)(3)=a0(4)(3)(2)(1)n=3a5=a3(5)(4)=a1(5)(4)(3)(2)
 
n=4a6=a4(6)(5)=a0(6)(5)(4)(3)(2)(1)n=5a7=a5(7)(6)=a1(7)(6)(5)(4)(3)(2)
 
  
 
 a2k=(1)ka0(2k)!,k=1,2, a2k+1=(1)ka1(2k+1)!,k=1,2,
Notice that at each step we always plugged back in the previous answer so that when the subscript was even we could always write the an in terms of a0 and when the coefficient was odd we could always write the an in terms of a1. Also notice that, in this case, we were able to find a general formula for an’s with even coefficients and an’s with odd coefficients. This won’t always be possible to do.
There’s one more thing to notice here. The formulas that we developed were only for k=1,2, however, in this case again, they will also work for k=0. Again, this is something that won’t always work, but does here.
Do not get excited about the fact that we don’t know what a0 and a1 are. As you will see, we actually need these to be in the problem to get the correct solution.
Now that we’ve got formulas for the an’s let’s get a solution. The first thing that we’ll do is write out the solution with a couple of the an’s plugged in.
y(x)=n=0anxn=a0+a1x+a2x2+a3x3++a2kx2k+a2k+1x2k+1+=a0+a1xa02!x2a13!x3++(1)ka0(2k)!x2k+(1)ka1(2k+1)!x2k+1+The next step is to collect all the terms with the same coefficient in them and then factor out that coefficient.
y(x)=a0{1x22!+(1)kx2k(2k)!+}+a1{xx33!++(1)k(2k+1)!x2k+1+}=a0k=0(1)kx2k(2k)!+a1k=0(1)kx2k+1(2k+1)!In the last step we also used the fact that we knew what the general formula was to write both portions as a power series. This is also our solution. We are done.

Before working another problem let’s take a look at the solution to the previous example. First, we started out by saying that we wanted a series solution of the form,
y(x)=n=0anxn
and we didn’t get that. We got a solution that contained two different power series. Also, each of the solutions had an unknown constant in them. This is not a problem. In fact, it’s what we want to have happen. From our work with second order constant coefficient differential equations we know that the solution to the differential equation in the last example is,
y(x)=c1cos(x)+c2sin(x)
Solutions to second order differential equations consist of two separate functions each with an unknown constant in front of them that are found by applying any initial conditions. So, the form of our solution in the last example is exactly what we want to get. Also recall that the following Taylor series,
cos(x)=n=0(1)nx2n(2n)!sin(x)=n=0(1)nx2n+1(2n+1)!
Recalling these we very quickly see that what we got from the series solution method was exactly the solution we got from first principles, with the exception that the functions were the Taylor series for the actual functions instead of the actual functions themselves.
Now let’s work an example with nonconstant coefficients since that is where series solutions are most useful.

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 - 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 ) y n y ′ + p ( x ) y = q ( x ) y n where  p ( x ) p ( x )  and  q ( x ) q ( x )  are continuous functions on the interval we’re working on and  n n  is a real number. Differential equations in this form are called  Bernoulli Equations . First notice that if  n = 0 n = 0  or  n = 1 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 n  other than these two. In order to solve these we’ll first divide the differential equation by  y n y n  to get, y − n y ′ + p ( x ) y 1 − n = q ( x ) y − n y ′ + p ( x ) y 1 − n = q ( x ) We are now going to use the substitution  v = y 1 − n v = y 1 − n  to convert this into a differential equation in terms of  v v . As we’ll see this will lead to a differential equation that we can solve. We are going to have to be c

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

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 - 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

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 - Partial: Summary of Separation of Variables

Throughout this chapter we’ve been talking about and solving partial differential equations using the method of separation of variables. However, the one thing that we’ve not really done is completely work an example from start to finish showing each and every step. Each partial differential equation that we solved made use somewhere of the fact that we’d done at least part of the problem in another section and so it makes some sense to have a quick summary of the method here. Also note that each of the partial differential equations only involved two variables. The method can often be extended out to more than two variables, but the work in those problems can be quite involved and so we didn’t cover any of that here. So with all of that out of the way here is a quick summary of the method of separation of variables for partial differential equations in two variables. Verify that the partial differential equation is linear and homogeneous. Verify that the boundary condi

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 - First Order: Modeling - ii

Example 4  A 50 kg object is shot from a cannon straight up with an initial velocity of 10m/s off a bridge that is 100 meters above the ground. If air resistance is given by 5 v v  determine the velocity of the mass when it hits the ground. First, notice that when we say straight up, we really mean straight up, but in such a way that it will miss the bridge on the way back down. Here is a sketch of the situation. Notice the conventions that we set up for this problem. Since the vast majority of the motion will be in the downward direction we decided to assume that everything acting in the downward direction should be positive. Note that we also defined the “zero position” as the bridge, which makes the ground have a “position” of 100. Okay, if you think about it we actually have two situations here. The initial phase in which the mass is rising in the air and the second phase when the mass is on its way down. We will need to examine both situations and set up an IVP for