laplace transform and inverse laplace, properties, Inverse Laplace Calculatio...Waqas Afzal
Laplace Transform
-Proof of common function
-properties
-Initial Value and Final Value Problems
Inverse Laplace Calculations
-by identification
-Partial fraction
Solution of Ordinary differential using Laplace and inverse Laplace
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
laplace transform and inverse laplace, properties, Inverse Laplace Calculatio...Waqas Afzal
Laplace Transform
-Proof of common function
-properties
-Initial Value and Final Value Problems
Inverse Laplace Calculations
-by identification
-Partial fraction
Solution of Ordinary differential using Laplace and inverse Laplace
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
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About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
AKS UNIVERSITY Satna Final Year Project By OM Hardaha.pdf
LaplaceTransformIIT.pdf
1. • Let f be a function. Its Laplace transform (function) is denoted
by the corresponding capitol letter F. Another notation is
• Input to the given function f is denoted by t; input to its Laplace
transform F is denoted by s.
• By default, the domain of the function f=f(t) is the set of all non-
negative real numbers. The domain of its Laplace transform
depends on f and can vary from a function to a function.
The Laplace Transform
L(f).
1
2. Definition of the Laplace Transform
• The Laplace transform F=F(s) of a function f=f
(t) is defined by
• The integral is evaluated with respect to t,
hence once the limits are substituted, what is
left are in terms of s.
L(f)(s) = F(s) =
� ∞
0
e−ts
f(t) dt.
2
4. At this stage we need to recall a limit from Cal 1:
Hence,
Thus,
F(s) =
1
s
, s > 0.
In this case the domain of the transform is the set of
all positive real numbers.
e−x
→
�
0 if x → +∞
+∞ if x → −∞
.
lim
b→+∞
e−bs
−s
=
�
0 if s > 0
+∞ if s < 0
.
4
5. Table of Transforms
f(t) = 1, t ≥ 0 F(s) = 1
s , s ≥ 0
f(t) = tn
, t ≥ 0 F(s) = n!
sn+1 , s ≥ 0
f(t) = eat
, t ≥ 0 F(s) = 1
s−a , s > a
f(t) = sin(kt), t ≥ 0 F(s) = k
s2+k2
f(t) = cos(kt), t ≥ 0 F(s) = s
s2+k2
f(t) = sinh(kt), t ≥ 0 F(s) = k
s2−k2 , s > |k|
f(t) = cosh(kt), t ≥ 0 F(s) = s
s2−k2 , s > |k|
5
6. The Laplace Transform is Linear
If a is a constant and f and g are functions, then
For example, by the above property (1)
As an another example, by property (2)
L(e5t
+ cos(3t)) = L(e5t
) + L(cos(3t)) =
1
s − 5
+
s
s2 + 9
, s > 5.
L(3t5
) = 3L(t5
) = 3
� 5!
s6
�
=
360
s6
, s > 0.
L(af) = aL(f) (1)
L(f + g) = L(f) + L(g) (2)
6
7. An example where both (1) and (2) are used,
L(3t7
+ 8) = L(3t7
) + L(8) = 3L(t7
) + 8L(1) = 3
� 7!
s8
�
+ 8
�1
s
�
, s > 0.
The Laplace transform of the product of two functions
L(fg) �= L(f)L(g).
As an example, we determine
The respective domains of the above three transforms
are s>0, s>6, and s>12; equivalently, s>12.
L(3 + e6t
)2
= L(3 + e6t
)(3 + e6t
) = L(9 + 6e6t
+ e12t
)
= L(9) + L(6e6t
+ L(e12t
)
= 9L(1) + 6L(e6t
) + L(e12t
)
=
9
s
+
6
s − 6
+
1
s − 12
.
7
8. The Inverse Transform
Lea f be a function and be its Laplace
transform. Then, by definition, f is the inverse
transform of F. This is denoted by
L(f) = F
L−1
(F) = f.
As an example, from the Laplace Transforms Table,
we see that
Written in the inverse transform notation
L−1
�
6
s2 + 36
�
= sin(6t).
L(sin(6t)) =
6
s2 + 36
.
8
9. Recall that Hence, for example,
L(tn
) = n!
sn+1 .
L−1
� 7!
s8
�
= t7
.
Here, by examining the power s8 we saw that n=7.
Now consider Here n+1=11. Hence n=10.
Now, we need to make the numerator to be 10!.
L−1
� 5
s11
�
.
L−1
�
5
s11
�
= 5L−1
�
1
s11
�
=
5
10!
L−1
�
10!
s11
�
=
5
10!
t10
.
9
10. Consider
, is that of the Laplace transforms of sin/cos.
s2
+ k2
L−1
�
7s + 15
s2 + 2
�
= L−1
�
7s
s2 + 2
�
+ L−1
�
15
s2 + 2
�
= 7L−1
�
s
s2 + 2
�
+ 15L−1
�
1
s2 + 2
�
= 7 cos(
√
2t) +
15
√
2
L−1
� √
2
s2 + 2
�
= 7 cos(
√
2t) +
15
√
2
sin(
√
2t)
More Examples of Inverse Transforms
L−1
�
7s + 15
s2 + 2
�
. The form of the denominator,
10
11. Partial Fractions
Consider the rational expressions
3s + 5
s2 − 3s − 10
=
3s + 5
(s − 5)(s + 2)
The denominator is factored, and the degree of the
numerator is at least one less that that of the
denominator, in fact, it is exactly one less than the
degree of the denominator.
We can, therefore, put the rational expression in
partial fractions. This means for constants A and B,
11
12. 3s + 5
(s − 5)(s + 2)
=
A
s − 5
+
B
s + 2
.
To determine A and B, first clear the denominators:
3s + 5
✭✭✭✭✭✭
✭
(s − 5)(s + 2)✭✭✭✭✭✭
✭
(s − 5)(s + 2) =
A
✘✘✘
✘
(s − 5)
✘✘✘
✘
(s − 5)(s + 2) +
B
✘✘✘
✘
(s + 2)
(s − 5)✘✘✘
✘
(s + 2).
Thus we have the polynomial equality:
3s + 5 = A(s + 2) + B(s − 5) = (A + B)s + 2A − 5B.
By comparing the coefficients of s and constant
coefficients, we get two equations in A and B.
A + B = 3
2A − 5B = 5
we have the decomposition
12
13. We can solve for A and B by using Cramer’s rule
A =
det
�
3 1
5 −5
�
det
�
1 1
2 −5
�, and B =
det
�
1 3
2 5
�
det
�
1 1
2 −5
�
Now by the definition of the determinant,
det
�
a b
c d
�
= ad − cb.
Hence,
A =
20
7
, and B =
1
7
.
.
13
14. We can now determine the inverse transform
L−1
�
3s + 5
(s − 5)(s + 2)
�
= L−1
�
A
s − 5
+
B
s + 2
�
= A L−1
�
1
s − 5
�
+ B L−1
�
1
s + 2
�
=
20
7
e5t
+
1
7
e−2t
.
This could also have been directly determined by
using a formula from your Table of Laplace
Transforms from the text.
This inverse transform will be used in slide #19 to
solve an IVP.
14
15. Put in partial fractions.
3s+4
(s−2)(s2+7)
Since s2 +7 is a quadratic, when it is put in partial
fractions, its numerator must be the general polynomial
of degree one.
3s+4
(s−2)(s2+7) = A
s−2 + Bs+D
s2+7
3s + 4
✭✭✭✭✭✭
✭
(s − 2)(s2
+ 7)✭✭✭✭✭✭
✭
(s − 2)(s2
+ 7) =
A
✘✘
✘
s − 2
✘✘✘
✘
(s − 2)(s2
+7)+
Bs + D
✘✘✘
s2
+ 7
(s−2)✘✘✘
✘
(s2
+ 7)
Hence, we have the equality of polynomials:
Comparing the coefficients of s2, s, and constant coefficients,
A + B = 0, −2B + D = 3, and 7A − 2D = 4.
Partial Fractions: More Examples
3s + 4 = A(s2
+ 7) + (Bs + D)(s − 2) = (A + B)s2
+ (−2B + D)s + 7A − 2D
15
16. From the first equation, we get that B=-A. Sub in the
second, to get
2A + D = 3 (1)
7A − 2D = 4 (2)
Then,
Hence,
A =
det
�
3 1
4 −2
�
det
�
2 1
7 −2
� =
−10
−11
, and D =
det
�
2 3
7 4
�
det
�
2 1
7 −2
� =
−13
−11
.
A =
10
11
, B = −A = −
10
11
, D =
13
11
.
16
17. Transforms of Derivatives
Given a function y=y(t), the transform of its
derivative y´ can be expressed in terms of the
Laplace transform of y: L(y�
) = sL(y) − y(0).
The corresponding formula for y´´ can be obtained
by replacing y by y´ (equation 1 below).
L(y�
)�
= sL(y�
) − y�
(0) (1)
= s(sL(y) − y(0)) − y�
(0) (2)
= s2
L(y) − sy(0) − y�
(0). (3)
Hence, L(y��
) = s2
L(y) − sy(0) − y�
(0).
17
18. Solving IVP with Laplace Transforms
Solve the IVP y�
− 5y = −e−2t
, y(0) = 3.
Taking the Laplace transform of both sides,
L(y�
− 5y) = L(−e−2t
) (1)
L(y�
) − 5L(y) = −
1
s + 2
(2)
sL(y) − y(0) − 5L(y) = −
1
s + 2
(3)
(s − 5)L(y) − 3 = −
1
s + 2
(4)
(s − 5)L(y) = −
1
s + 2
+ 3 =
3s + 5
s + 2
(5)
L(y) =
3s + 5
(s − 5)(s + 2)
(6)
Example 1:
Solution:
18
19. Hence, by the definition of the inverse transform,
y = L−1
�
3s + 5
(s − 5)(s + 2)
�
=
20
7
e5t
+
1
7
e−2t
.
The above inverse transform was found in slide # 14.
Solve the IVP:
Example 2:
y��
+ 7y = 10e2t
, y(0) = 0, y�
(0) = 3.
Solution: Taking the Laplace transform of both sides,
L(y��
) + 7L(y) = 10L(e2t
)
3
0
s2
L(y) − sy(0) − y�
(0) + 7L(y) = 10
s−2
19
21. Example 1 L(cos(kt)) = s
s2+k2 . To find L(eat
cos(kt))
we replace s by s-a. Hence,
L(eat
cos(kt)) = s−a
(s−a)2+k2 .
The inverse version is also useful:
The corresponding sine version is
L−1
�
k
(s−a)2+k2
�
= eat
sin(kt).
Notice matching s-a on the numerator and denominator.
Lemma: Let L(y(t)) = Y (s). Then L(eat
y(t)) = Y (s − a).
L−1
�
s−a
(s−a)2+k2
�
= eat
cos(kt).
21
22. Find: L−1
�
4s+1
s2+10s+34
�
.
Here the denominator does not factor over the reals.
Hence complete the square.
s2
+ 10s + 34 = s2
+ 10s + 25
� �� �
−25 + 34 = (s + 5)2
+ 9.
L−1
�
4s+1
s2+10s+34
�
= L−1
�
4s+1
(s+5)2+9
�
= L−1
�
4(s+5)−20+1
(s+5)2+9
�
= L−1
�
4(s+5)−19
(s+5)2+9
�
= 4L−1
�
(s+5)
(s+5)2+9
�
− 19L−1
�
1
(s+5)2+9
�
= 4e−5t
cos(3t) − 19
3 L−1
�
3
(s+5)2+9
�
= 4e−5t
cos(3t) − 19
3 e−5t
sin(3t).
this s must now be
made into (s+5).
22
23. Example 1: Now L(eat
) = 1
s−a , s �= a.
In other words, L−1
�
1
(s−a)2
�
= teat
.
Lemma: Let L(f(t)) = F(s). Then L(tf(t)) = −F�
(s).
Hence, L(teat
) = −
�
1
s−a
��
= 1
(s−a)2 , s �= a.
Example 2: Find
Solution: Now Then by the Lemma,
f(t) = L−1
(ln
�
s + 2
s − 3
�
).
L(f(t)) = ln
�
s + 2
s − 3
�
.
Next Slide
L(tf(t)) = −
�
ln
�
s + 2
s − 3
���
= −(ln(s + 2) − ln(s − 3))�
23
24. L(tf(t)) = −(
1
s + 2
−
1
s − 3
) =
1
s − 3
−
1
s + 2
.
Hence, tf(t) = L−1
(
1
s − 3
) − L−1
(
1
s + 2
)
= e3t
− e−2t
.
Hence, f(t) =
e3t
− e−2t
t
, t > 0.
24
25. Unit Function and Piece-wise Defined Functions
Let a≥0. The Heaviside unit function U(t–a) is defined by
U(t − a) =
�
1 if t ≥ a
0 if 0 ≤ t < a
.
The unit function can be used to express piecewise
functions.
a
1
25
26. Let f be the piecewise defined function
Now consider the function
If 0≤t<8, then U(t–8) = 0. Then
If t≥8, then U(t–8) = 1.
4 + (6 − 4)U(t − 8) = 4 + 6 − 4 = 6.
Thus, we see that
f(t) = 4 + 2U(t − 8).
f(t) =
�
4 if 0 ≤ t < 8
6 if t ≥ 8
.
Example 1:
4 + (6 − 4)U(t − 8).
4 + (6 − 4)U(t − 8) = 4.
Then
26
27. Consider the piecewise defined function
f(t) =
t if 0 ≤ t < 2
t2
if 2 ≤ t < 6
t3
if 6 ≤ t
.
We can express f in terms of unit functions.
f(t) = t + (t2
− t)U(t − 2) + (t3
− t2
)U(t − 6).
Example 2:
Notice how the coefficients of the unit functions are
related to the outputs by the piece-wise defined
function.
27
28. Truncating a Function
a
y=f(t) y=g(t)
The graph of g has been obtained by truncating that of f.
g(t) =
�
0 if 0 ≤ t < a
f(t) if t ≥ a
. g(t) = f(t)U(t − a).
28
29. Truncating a Function
a
y=f(t) y=g(t)
The graph of g has been obtained by truncating that of f.
y=g
b
g(t) = f(t)U(t − a) − f(t)U(t − b).
g(t) =
0 if 0 ≤ t < a
f(t) if a ≤ t < b
0 if b ≤ t
.
a b
29
30. Translating and Truncating a Function
a
y=f(t) y=g(t)
The graph of g has been obtained translating the
graph of f by c units to the right and then
truncating it.
b
a b
y=g
y=g
c
y=f(t-c)
g(t) =
0 if 0 ≤ t < a
f(t − c) if a ≤ t < b
0 if b ≤ t
.
30
31. y=f(a)
a
=
�
0 if 0 ≤ t < a
f(t − a) if a ≤ t
.
y(t) = f(t − a)U(t − a)
Example 1: Find L(sin(t − 2)U(t − 2)).
Solution: Here a is 2 and f(t − 2) = sin(t − 2). We
need f(t) to determine F(s). We can get it from the
formula for f(t–2) by replacing t by t+2.
f(t + 2 − 2) = sin(t + 2 − 2), i.e., f(t) = sin(t). Hence,
L(sin(t − 2)U(t − 2)) = F(s)e−2s
= 1
s2+4 e−2s
.
Proposition 1 Let a ≥ 0 and L(f(t)) = F(s). Then
L(f(t − a)U(t − a)) = e−as
F(s).
31
32. Example 2: Determine L(t2
U(t − 2)).
Solution: Recall the formula
L(f(t − a)U(t − a)) = e−as
F(s), where F(s) = L(f).
In this case, a=2, and f(t − a) = f(t − 2) = t2
.
to obtain F(s), we first need f(t). In order to
do that
replace t in the formula for f(t–2) by t+2.
f(t − 2) = t2
f(t + 2 − 2) = (t + 2)2
= t2
+ 4t + 4
f(t) = t2
+ 4t + 4
F(s) = L(t2
) + 4L(t) + 4L(1)
=
2
s3
+
4
s2
+
4
s
, s > 0.
Thus L(t2
U(t − 2)) =
� 2
s3 + 4
s2 + 4
s
�
e−2s
, s > 0.
32
33. Example 3: Determine L
�
sin(π
2 t)U(t − 3)
�
.
Now to obtain ,
Solution: Comparing U(t − a)
Hence, f(t − 3) = sin(π
2 t). f(t)
by in the formula for f(t − 3).
t + 3 Then,
f(t + 3 − 3) = sin(π
2 (t + 3)) = sin(π
2 t + π
2 3)).
Now an elementary trig identity states
sin(3π
2 + θ) = − cos(θ).
Whence, f(t) = − cos(π
2 t). Thus F(s) = − s
s2+ π2
4
.
L
�
sin(π
2 t)U(t − 3)
�
= e−3s s
s2+ π2
4
.
U(t − 3) with , we get a=3.
replace t
33
34. Let
L−1
(e−as
F(s)) = U(t − a)f(t − a).
L−1
(F(s)) = f(t). Then
Example 1: L−1
�
s
s2 + 4
�
= cos(2t).
Hence L−1
�
s
s2 + 4
e−7s
�
= cos(2(t − 7))U(t − 7).
The presence of e−7s
caused two changes to cos(2t) :
the input t was replaced by t − 7 and then cos(2(t − 7))
was multiplied by U(t − 7).
Recall
34
35. Example 2: Determine L−1
�
e−7s
(s − 5)2 + 4
�
.
First consider the inverse without the factor e−7s
.
L−1
�
1
(s − 5)2 + 4
�
= e5t
sin(2t).
Thus,
L−1
�
e−7s
(s − 5)2 + 4
�
=
� �� �
e5(t−7)
sin(2(t − 7)) U(t − 7).
Replace t by t–7.
35
36. Convolutions
Let f and g be functions. The convolution of f with
g is defined by
����
f ∗ g(t) =
� t
0
f(τ)g(t − τ) dτ.
Thus in a convolution integral, in general, you will see a
factor (the t in the output by f replaced by ), and a
factor (the t in the output by g replaced by ).
t − τ
τ
sin 3t ∗ e5t
=
� t
0
sin(3τ)
� �� �
e5(t−τ)
� �� � dτ.
the factor the factor
τ t − τ
τ
t − τ
36
37. Example 1: Let and
f(t) = t2 g(t) = 2t + 3. Find f ∗ g.
Solution:
f ∗ g(t) =
� t
0
f(t)g(t − τ) dτ =
� t
0
τ2
(2(t − τ) + 3) dτ.
=
� t
0
τ2
(2t + 3 − τ) dτ = (2t + 3)
� t
0
τ2
dτ −
� t
0
τ3
dτ
= (2t + 3)
�
τ3
3
�t
0
−
�
τ4
4
�t
0
= (2t + 3)t3
3 − t4
4
=
5t4
12
+ t3
.
37
38. Example 2:
Express the following integral as a convolution.
� t
0
τ3
cos(t − τ) dτ.
‘τ’ factor ‘t − τ’ factor
Replace τ by t to
get the first factor
of the convolution
Replace t − τ by t to
get the second factor
of the convolution
� t
0
τ3
cos(t − τ) dτ = t3
∗ cos(t)
38
39. Example 3:
� t
0
e2(t−τ)
τ3
dτ = t3
∗ e2t
.
Example 4:
In the following example ‘t − τ’ factor is missing.
That is because the second factor of the convolution
was a constant. � t
0
τ3
dτ = t3
∗ 1.
Example 5:
� t
0
et−2τ
dτ =
� t
0
e−τ
et−τ
dτ = e−t
∗ et
.
We see that the convolution is not the constant
e−t
∗ et
Here is an alternative view of the same integral
� t
0
et−2τ
dτ =
� t
0
et
e−2τ
dτ = et
� t
0
e−2τ
dτ = et
(e−2t
∗ 1).
However, in general f(g ∗ h) �= (fg) ∗ (fh).
function 1.
39
40. Laplace Transform of Convolutions
The Laplace transform of the product of two functions
is not equal to the product of the two transforms:
L(fg) �= L(f)L(g).
The convolution behaves far better:
L(f ∗ g) = L(f)L(g).
Example 1: Without evaluating the integral, find
L
�� t
0
e2(t−τ)
τ3
dτ
�
.
By Example 3 of the previous slide
L
�� t
0
e2(t−τ)
τ3
dτ
�
= L
�
t3
∗ e2t
�
= L(t3
)L(e2t
)= 3!
s4(s−2) , s > 2.
40
41. Example 2: L
�� t
0
et+τ
sin(t − τ) dτ
�
= L
�� t
0
et
eτ
sin(t − τ) dτ
�
= L
�
et
� t
0
eτ
sin(t − τ) dτ
�
= L
�
et
(et
∗ sin t)
�
Now L(et
∗ sin t) = L(et
)L(sin t) = 1
s−1
1
s2+1 , s > 1.
The effect of multiplying this input to the Laplace
transform by et
is to replace the s in the output by
L
�
et
(et
∗ sin t)
�
= 1
(s−1)−1
1
(s−1)2+1 = 1
(s−2)((s−1)2+1) , s > 2.
s–1. Hence
41
42. Example 3: Find L
�� t
0
t sin(τ) dτ
�
.
L
�� t
0
t sin(τ) dτ
�
= L
�
t
� t
0
sin(τ) dτ
�
Solution:
= L (t(sin t ∗ 1))
Recall that L(tf(t)) = −F�
(s), where L(f(t)) = F(s).
Now, L ((sin t ∗ 1)) = L(sin t)L(1) = 1
s2+1
1
s , s > 0.
Hence, L (t(sin t ∗ 1)) = −
�
1
s(s2+1)
��
, s > 0
= − 3s2
+1
s2(s2+1)2 , s > 0.
42
43. Integro-differential Equations
Solve:
f(t) = t + sin t ∗ f(t) Now use the
Hence,
Laplace transform to convert the convolution product
to regular products.
L(f(t)) = L(t) + L(sin t ∗ f(t)) = 1
s2 + 1
s2+1 L(f(t).
(1 − 1
s2+1 )L(f(t)) = 1
s2
(s2
+1−1
s2+1 )L(f(t)) = 1
s2 i.e., ( s2
s2+1 )L(f(t)) = 1
s2
Thus, L(f(t)) = s2
+1
s4 = 1
s2 + 1
s4 . Hence,
f(t) = L−1
� 1
s2
�
+ L−1
� 1
s4
�
= L−1
� 1
s2
�
+ 1
3! L−1
� 3!
s4
�
= t + t3
6 .
Notice that .
f(t) = t +
� t
0
sin(τ)f(t − τ) dτ. input to f
Solution:
Example:
43
44. Solve: y�
(t) = 1 − sin t −
� t
0
y(τ) dτ, y(0) = 0.
L(y�
(t)) = L(1) − L(sin t) − L
�� t
0
y(τ) dτ
�
,
Take Laplace
transforms to get
sL(y(t)) − y(0) = 1
s − 1
s2+1 − L(y(t) ∗ 1),
sL(y(t)) = 1
s − 1
s2+1 − L(y(t))L(1),
sL(y(t)) = 1
s − 1
s2+1 − L(y(t))
s ,
sL(y(t)) + L(y(t))
s = 1
s − 1
s2+1 ,
(s + 1
s )L(y(t)) = 1
s − 1
s2+1 ,
(s2
+1)
s L(y(t)) = 1
s − 1
s2+1 , Next Slide
44
45. L(y(t)) = s
(s2+1)
1
s − s
(s2+1)
1
s2+1 ,
L(y(t)) = 1
(s2+1) − s
(s2+1)2 ,
y(t) = L−1
�
1
(s2+1)
�
− L−1
�
s
(s2+1)2
�
,
y(t) = sin t − 1
2 t sin t �
45
46. Using the Dirac’s Delta Function
Solve the IVP y�
+ 4y = δ(t − 2), y(0) = 6.
L(y�
) + 4L(y) = L(δ(t − 2))
� �� �
sL(y) − y(0) +4L(y) =
e−2s
s
(s + 4)L(y) = y(0) +
e−2s
s
= 6 +
e−2s
s
L(y) =
6
(s + 4)
+
e−2s
s(s + 4)
=
6
(s + 4)
+
e−2s
4s
−
e−2s
4(s + 4)
y(t) = 6e−4t
+
1
4
U(t − 2) −
e−4(t−2)
4
U(t − 2).
46
47. Systems of Equations and Laplace Transform
Let and be functions of Suppose
x = x(t) y = y(t) t.
y by converting the equations into two in and .
By taking the Laplace Transforms, we will solve for x and
sL(x) − x(0) + 3L(x) + sL(y) − y(0) =
1
s
sL(x) − x(0) − L(x) + sL(y) − y(0) =
1
s − 1
.
L(x) L(y)
From (1)
From (2)
(1)
(2)
(3)
(4)
From (3)
From (4)
x�
+ 3x + y�
= 1
x�
− x + y�
= et
, x(0) = 0, y(0) = 0.
L(x�
) + 3L(x) + L(y�
) = L(1)
L(x�
) − L(x) + L(y�
) = L(et
).
47
48. Using and and collecting like terms
x(0) = 0 y(0) = 0,
Using Cramer’s rule,
L(x) =
det
�
1
s s
1
s−1 s
�
det
�
s + 3 s
s − 1 s
�, L(y) =
det
�
s + 3 1
s
s − 1 1
s−1
�
det
�
s + 3 s
s − 1 s
�
L(x) =
1 − s
s−1
s2 + 3s − s2 + s
, L(y) =
s+3
s−1 − s−1
s
s2 + 3s − s2 + s
(s + 3)L(x) + sL(y) =
1
s
(s − 1)L(x) + sL(y) =
1
s − 1
48
49. L(x) =
1 − s
s−1
4s
, L(y) =
s+3
s−1 − s−1
s
4s
L(x) =
1
4s
−
1
4(s − 1)
, L(y) =
s + 3
4s(s − 1)
−
s − 1
4s2
Hence, .
x(t) = 1
4 − 1
4 et
. In L(y) put the first fraction in
partial fractions and distribute the s2 in the second
L(y) = − 3
4s + 1
s−1 −
� 1
4s − 1
4s2
�
. Hence,
L(y) = −1
s + 1
s−1 + 1
4s2 . Hence, y = −1 + et
+ 1
4 t.
The partial fraction calculations:
s+3
4s(s−1) = A
s + B
s−1 ⇒ s + 3 = 4A(s − 1) + 4Bs. Hence,
4A + 4B = 1 and .
−4A = 3. Solve for A and B.
to get .
49
50. Periodic Functions
The graph is made by repeating a beginning part. The
T 2T 3T
t
f(t)
T+t
f(T+t)
2T+t
f(2T+t)
This part is repeated
smallest T>0 such that f(t+T)=f(t) for all t is called
period of the function. The Laplace transform of f is
L(f)(s) =
1
1 − e−T s
� T
0
e−ts
f(t) dt.
0
50
51. 2a 4a 6a
Example: Find the Laplace Transform of the periodic
function f whose graph is given below.
1
-1
The period of f is 2a and, i.e., f(t)=f(t+2a), for all t and
f(t) =
�
1 if 0 ≤ t < a
−1 if a ≤ t < 2a
.
L(f(t))(s) =
1
1 − e−2as
� 2a
0
e−ts
f(t) dt,
Applying the formula for the transform of a periodic function, we have
51