Understanding Convolution Integral in Time Domain Analysis of First-Order DEs, Lecture notes of Differential and Integral Calculus

This document delves into the convolution integral, a pure time domain analysis technique for understanding the response of first-order differential equations. The author discusses the concept of integrating factors, the unit step function, and the definition of convolution. The output of a first-order differential equation with input x(t) is shown to be given by the convolution of the input and the impulse response of the system.

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2.1 The Convolution Integral
So now we have examined several simple properties that the differential equation satisfies
linearity and time-invariance. We have also seen that the complex exponential has the special
property that it passes through changed only by a complex numer the differential equation. Also,
we have discussed the roll of tansforms, as representing arbitrary inputs via the superpositions of
complex exponentials. This discussion is often called a ”frequency domain analysis”. Frequency
domain analysis studyies the outputs of linear and time-invariant systems via their response to
complex exponentials. Now we turn our focus to a pure time domain analysis, understanding the
response of the differential equation directly in terms of its time domain inputs. For this we
explore the ”convolution integral”. We do this by solving the first-order differential equation
directly using integrating factors. For this, examine the differential equation and introduce the
integrating factor f(t) which has the property that it makes one side of the equation into a total
differential. Define


which implies

This implies the integrating factor is

, and using the boundary condition y(−) = 0 the
total differential is solved giving




We have almost arrived at our convolution formula. For this introduce the unit step function, and
the definition of the convolution formulation. The unit-step function is zero to the left of the
origin, and 1 elsewhere:
1, 0
0, 0
Definition 2.2. Given time signals f(t), g(t), then their convolution is defined as
 

Proposition 2.1. The output of this first order differential equation with input x(t) is given
according to



To see this, simply use the property of the unit step to rewrite the solution of Eqn. 13 according to
pf2

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2.1 The Convolution Integral

So now we have examined several simple properties that the differential equation satisfies linearity and time-invariance. We have also seen that the complex exponential has the special property that it passes through changed only by a complex numer the differential equation. Also, we have discussed the roll of tansforms, as representing arbitrary inputs via the superpositions of complex exponentials. This discussion is often called a ”frequency domain analysis”. Frequency domain analysis studyies the outputs of linear and time-invariant systems via their response to complex exponentials. Now we turn our focus to a pure time domain analysis, understanding the response of the differential equation directly in terms of its time domain inputs. For this we explore the ”convolution integral”. We do this by solving the first-order differential equation directly using integrating factors. For this, examine the differential equation and introduce the integrating factor f(t) which has the property that it makes one side of the equation into a total differential. Define

ᡘ䙦ᡲ䙧ᡶ䙦ᡲ䙧 㐄 ᡘ䙦ᡲ䙧ᡷ䙢䙦ᡲ䙧 ㎗ ᡘ䙦ᡲ䙧ᡓᡷ䙦ᡲ䙧

which implies

ᡘ䙢䙦ᡲ䙧ᡷ䙦ᡲ䙧 ㎗ ᡘ䙦ᡲ䙧ᡷ䙢䙦ᡲ䙧 㐄 ᡘ䙦ᡲ䙧ᡷ䙢䙦ᡲ䙧 ㎗ ᡓᡘ䙦ᡲ䙧ᡷ䙦ᡲ䙧

This implies the integrating factor is ᡘ䙦ᡲ䙧 㐄 ᡗ〨ぇ, and using the boundary condition y(−∞) = 0 the total differential is solved giving

⡹⦘

We have almost arrived at our convolution formula. For this introduce the unit step function, and the definition of the convolution formulation. The unit-step function is zero to the left of the origin, and 1 elsewhere:

Definition 2.2. Given time signals f(t), g(t), then their convolution is defined as

⡹⦘

Proposition 2.1. The output of this first order differential equation with input x(t) is given according to

ᡷ䙦ᡲ䙧 㐄 ᡶ䙦ᡲ䙧 ᒙᒙ ᡗ⡹〨ぇᡳ䙦ᡲ䙧

To see this, simply use the property of the unit step to rewrite the solution of Eqn. 13 according to

⡹⦘

We make the following comment. Notice the output is a function of the input “convolved” with a property of the system, ᡗ⡹〨ぇᡳ䙦ᡲ䙧. This property we will call the “impulse response” of the system and we will study it extensively. For LTI systems this will always be true, although the property of the system will change depending on the system. So we have arrived at the second major component of our study of linear, time-invariant systems. To understand the outputs of LTI systems to arbitrary inputs, one needs to understand the convolution integral. The remaining 12 lectures work to generalize and strengthen the these very notions.