This document provides an introduction to using MATLAB for numerical computations and graphical output. It describes how to launch MATLAB, perform basic arithmetic operations and matrix calculations, use loops to iterate calculations, and generate different types of plots and graphs including sine waves, bar graphs, and subplots. The exercises walk through examples of these MATLAB functions and commands to familiarize users with its interface and capabilities.
This is the slides of the UCLA School of Engineering Matlab workshop on Matlab graphics.
Learning Matlab graphics by examples:
- In 2 hours, you will be able to create publication-quality plots.
- Starts from the basic 2D line plots to more advanced 3D plots.
- You will also learn some advanced topics like fine-tuning the appearance of your figure and the concept of handles.
- You will be able to create amazing animations: we use 2D wave equation and Lorentz attractor as examples.
Introduction
Plotting basic 2-D plots.
The plot command
The fplot command
Plotting multiple graphs in the same plot
Formatting plots
USING THE plot() COMMAND TO PLOT
MULTIPLE GRAPHS IN THE SAME PLOT
MATLAB PROGRAM TO PLOT VI CHARACTERISTICS OF A DIODE
SUMMARY
How to 2D plots in Matlab. Easy steps to graph mathematical functions.
You have to define your interval of interest and consider a step in your independent vector, then you have to define your function and use an appropriate 2D built-in function.
More information and examples:
http://matrixlab-examples.com/matlab-plot-2tier.html
This is the slides of the UCLA School of Engineering Matlab workshop on Matlab graphics.
Learning Matlab graphics by examples:
- In 2 hours, you will be able to create publication-quality plots.
- Starts from the basic 2D line plots to more advanced 3D plots.
- You will also learn some advanced topics like fine-tuning the appearance of your figure and the concept of handles.
- You will be able to create amazing animations: we use 2D wave equation and Lorentz attractor as examples.
Introduction
Plotting basic 2-D plots.
The plot command
The fplot command
Plotting multiple graphs in the same plot
Formatting plots
USING THE plot() COMMAND TO PLOT
MULTIPLE GRAPHS IN THE SAME PLOT
MATLAB PROGRAM TO PLOT VI CHARACTERISTICS OF A DIODE
SUMMARY
How to 2D plots in Matlab. Easy steps to graph mathematical functions.
You have to define your interval of interest and consider a step in your independent vector, then you have to define your function and use an appropriate 2D built-in function.
More information and examples:
http://matrixlab-examples.com/matlab-plot-2tier.html
1. Introduction to MATLAB and programming
2. Workspace, variables and arrays
3. Using operators, expressions and statements
4. Repeating and decision-making
5. Different methods for input and output
6. Common functions
7. Logical vectors
8. Matrices and string arrays
9. Introduction to graphics
10. Loops
11. Custom functions and M-files
I am Samuel H. I am a Mechanical Engineering Assignment Expert at matlabassignmentexperts.com. I hold a Ph.D. Matlab, University of Alberta, Canada. I have been helping students with their homework for the past 12 years. I solve assignments related to Mechanical Engineering.
Visit matlabassignmentexperts.com or email info@matlabassignmentexperts.com.
You can also call on +1 678 648 4277 for any assistance with Mechanical Engineering Assignments.
N-Queens Combinatorial Problem - Polyglot FP for fun and profit - Haskell and...Philip Schwarz
Learn how to write FP code that displays a graphical representation of all the numerous N-Queens solutions for N=4,5,6,7,8 .
See how to neatly solve the problem by exploiting its self-similarity and using a divide and conquer approach.
Make light work of assembling multiple images into a whole, by exploiting Doodle’s facilities for combining images using a relative layout.
See relevant FP functions, like Foldable’s intercalate and intersperse, in action.
Code for part 3: https://github.com/philipschwarz/n-queens-combinatorial-problem-scala-part-3
1. Introduction to MATLAB and programming
2. Workspace, variables and arrays
3. Using operators, expressions and statements
4. Repeating and decision-making
5. Different methods for input and output
6. Common functions
7. Logical vectors
8. Matrices and string arrays
9. Introduction to graphics
10. Loops
11. Custom functions and M-files
I am Samuel H. I am a Mechanical Engineering Assignment Expert at matlabassignmentexperts.com. I hold a Ph.D. Matlab, University of Alberta, Canada. I have been helping students with their homework for the past 12 years. I solve assignments related to Mechanical Engineering.
Visit matlabassignmentexperts.com or email info@matlabassignmentexperts.com.
You can also call on +1 678 648 4277 for any assistance with Mechanical Engineering Assignments.
N-Queens Combinatorial Problem - Polyglot FP for fun and profit - Haskell and...Philip Schwarz
Learn how to write FP code that displays a graphical representation of all the numerous N-Queens solutions for N=4,5,6,7,8 .
See how to neatly solve the problem by exploiting its self-similarity and using a divide and conquer approach.
Make light work of assembling multiple images into a whole, by exploiting Doodle’s facilities for combining images using a relative layout.
See relevant FP functions, like Foldable’s intercalate and intersperse, in action.
Code for part 3: https://github.com/philipschwarz/n-queens-combinatorial-problem-scala-part-3
The frame work that I used for my Introduction to Matlab hour long course. Most of the instruction took place on a live Matlab screen, but this provided the framework
A basic overview, application and usage of MATLAB for engineers. It covered very basics essential that will help one to get started with MATLAB programming easily.
Provided by IDEAS2IGNITE
Introduction to Digital Image Processing Using MATLABRay Phan
This was a 3 hour presentation given to undergraduate and graduate students at Ryerson University in Toronto, Ontario, Canada on an introduction to Digital Image Processing using the MATLAB programming environment. This should provide the basics of performing the most common image processing tasks, as well as providing an introduction to how digital images work and how they're formed.
You can access the images and code that I created and used here: https://www.dropbox.com/sh/s7trtj4xngy3cpq/AAAoAK7Lf-aDRCDFOzYQW64ka?dl=0
The SlideShare 101 is a quick start guide if you want to walk through the main features that the platform offers. This will keep getting updated as new features are launched.
The SlideShare 101 replaces the earlier "SlideShare Quick Tour".
The name MATLAB stands for MATrix LABoratory.MATLAB is a high-performance language for technical computing.
It integrates computation, visualization, and programming environment. Furthermore, MATLAB is a modern programming language environment: it has sophisticated data structures, contains built-in editing and debugging tools, and supports object-oriented programming.
These factor make MATLAB an excellent tool for teaching and research.
SAMPLE QUESTIONExercise 1 Consider the functionf (x,C).docxagnesdcarey33086
SAMPLE QUESTION:
Exercise 1: Consider the function
f (x,C)=
sin(C x)
Cx
(a) Create a vector x with 100 elements from -3*pi to 3*pi. Write f as an inline or anonymous function
and generate the vectors y1 = f(x,C1), y2 = f(x,C2) and y3 = f(x,C3), where C1 = 1, C2 = 2 and
C3 = 3. Make sure you suppress the output of x and y's vectors. Plot the function f (for the three
C's above), name the axis, give a title to the plot and include a legend to identify the plots. Add a
grid to the plot.
(b) Without using inline or anonymous functions write a function+function structure m-file that does
the same job as in part (a)
SAMPLE LAB WRITEUP:
MAT 275 MATLAB LAB 1 NAME: __________________________
LAB DAY and TIME:______________
Instructor: _______________________
Exercise 1
(a)
x = linspace(-3*pi,3*pi); % generating x vector - default value for number
% of pts linspace is 100
f= @(x,C) sin(C*x)./(C*x) % C will be just a constant, no need for ".*"
C1 = 1, C2 = 2, C3 = 3 % Using commans to separate commands
y1 = f(x,C1); y2 = f(x,C2); y3 = f(x,C3); % supressing the y's
plot(x,y1,'b.-', x,y2,'ro-', x,y3,'ks-') % using different markers for
% black and white plots
xlabel('x'), ylabel('y') % labeling the axis
title('f(x,C) = sin(Cx)/(Cx)') % adding a title
legend('C = 1','C = 2','C = 3') % adding a legend
grid on
Command window output:
f =
@(x,C)sin(C*x)./(C*x)
C1 =
1
C2 =
2
C3 =
3
(b)
M-file of structure function+function
function ex1
x = linspace(-3*pi,3*pi); % generating x vector - default value for number
% of pts linspace is 100
C1 = 1, C2 = 2, C3 = 3 % Using commans to separate commands
y1 = f(x,C1); y2 = f(x,C2); y3 = f(x,C3); % function f is defined below
plot(x,y1,'b.-', x,y2,'ro-', x,y3,'ks-') % using different markers for
% black and white plots
xlabel('x'), ylabel('y') % labeling the axis
title('f(x,C) = sin(Cx)/(Cx)') % adding a title
legend('C = 1','C = 2','C = 3') % adding a legend
grid on
end
function y = f(x,C)
y = sin(C*x)./(C*x);
end
Command window output:
C1 =
1
C2 =
2
C3 =
3
Joe Bob
Mon lab: 4:30-6:50
Lab 3
Exercise 1
(a) Create function M-file for banded LU factorization
function [L,U] = luband(A,p)
% LUBAND Banded LU factorization
% Adaptation to LUFACT
% Input:
% A diagonally dominant square matrix
% Output:
% L,U unit lower triangular and upper triangular such that LU=A
n = length(A);
L = eye(n); % ones on diagonal
% Gaussian Elimination
for j = 1:n-1
a = min(j+p.
More instructions for the lab write-up1) You are not obli.docxgilpinleeanna
More instructions for the lab write-up:
1) You are not obligated to use the 'diary' function. It was presented only for you convenience. You
should be copying and pasting your code, plots, and results into some sort of "Word" type editor that
will allow you to import graphs and such. Make sure you always include the commands to generate
what is been asked and include the outputs (from command window and plots), unless the problem
says to suppress it.
2) Edit this document: there should be no code or MATLAB commands that do not pertain to the
exercises you are presenting in your final submission. For each exercise, only the relevant code that
performs the task should be included. Do not include error messages. So once you have determined
either the command line instructions or the appropriate script file that will perform the task you are
given for the exercise, you should only include that and the associated output. Copy/paste these into
your final submission document followed by the output (including plots) that these MATLAB
instructions generate.
3) All code, output and plots for an exercise are to be grouped together. Do not put them in appendix, at
the end of the writeup, etc. In particular, put any mfiles you write BEFORE you first call them.
Each exercise, as well as the part of the exercises, is to be clearly demarked. Do not blend them all
together into some sort of composition style paper, complimentary to this: do NOT double space.
You can have spacing that makes your lab report look nice, but do not double space sections of text
as you would in a literature paper.
4) You can suppress much of the MATLAB output. If you need to create a vector, "x = 0:0.1:10" for
example, for use, there is no need to include this as output in your writeup. Just make sure you
include whatever result you are asked to show. Plots also do not have to be a full, or even half page.
They just have to be large enough that the relevant structure can be seen.
5) Before you put down any code, plots, etc. answer whatever questions that the exercise asks first.
You will follow this with the results of your work that support your answer.
SAMPLE QUESTION:
Exercise 1: Consider the function
f (x,C)=
sin(C x)
Cx
(a) Create a vector x with 100 elements from -3*pi to 3*pi. Write f as an inline or anonymous function
and generate the vectors y1 = f(x,C1), y2 = f(x,C2) and y3 = f(x,C3), where C1 = 1, C2 = 2 and
C3 = 3. Make sure you suppress the output of x and y's vectors. Plot the function f (for the three
C's above), name the axis, give a title to the plot and include a legend to identify the plots. Add a
grid to the plot.
(b) Without using inline or anonymous functions write a function+function structure m-file that does
the same job as in part (a)
SAMPLE LAB WRITEUP:
MAT 275 MATLAB LAB 1 NAME: ...
MATLAB sessions: Laboratory 2
MAT 275 Laboratory 2
Matrix Computations and Programming in MATLAB
In this laboratory session we will learn how to
1. Create and manipulate matrices and vectors.
2. Write simple programs in MATLAB
NOTE: For your lab write-up, follow the instructions of LAB1.
Matrices and Linear Algebra
⋆ Matrices can be constructed in MATLAB in different ways. For example the 3 × 3 matrix
A =
8 1 63 5 7
4 9 2
can be entered as
>> A=[8,1,6;3,5,7;4,9,2]
A =
8 1 6
3 5 7
4 9 2
or
>> A=[8,1,6;
3,5,7;
4,9,2]
A =
8 1 6
3 5 7
4 9 2
or defined as the concatenation of 3 rows
>> row1=[8,1,6]; row2=[3,5,7]; row3=[4,9,2]; A=[row1;row2;row3]
A =
8 1 6
3 5 7
4 9 2
or 3 columns
>> col1=[8;3;4]; col2=[1;5;9]; col3=[6;7;2]; A=[col1,col2,col3]
A =
8 1 6
3 5 7
4 9 2
Note the use of , and ;. Concatenated rows/columns must have the same length. Larger matrices can
be created from smaller ones in the same way:
c⃝2011 Stefania Tracogna, SoMSS, ASU
MATLAB sessions: Laboratory 2
>> C=[A,A] % Same as C=[A A]
C =
8 1 6 8 1 6
3 5 7 3 5 7
4 9 2 4 9 2
The matrix C has dimension 3 × 6 (“3 by 6”). On the other hand smaller matrices (submatrices) can
be extracted from any given matrix:
>> A(2,3) % coefficient of A in 2nd row, 3rd column
ans =
7
>> A(1,:) % 1st row of A
ans =
8 1 6
>> A(:,3) % 3rd column of A
ans =
6
7
2
>> A([1,3],[2,3]) % keep coefficients in rows 1 & 3 and columns 2 & 3
ans =
1 6
9 2
⋆ Some matrices are already predefined in MATLAB:
>> I=eye(3) % the Identity matrix
I =
1 0 0
0 1 0
0 0 1
>> magic(3)
ans =
8 1 6
3 5 7
4 9 2
(what is magic about this matrix?)
⋆ Matrices can be manipulated very easily in MATLAB (unlike Maple). Here are sample commands
to exercise with:
>> A=magic(3);
>> B=A’ % transpose of A, i.e, rows of B are columns of A
B =
8 3 4
1 5 9
6 7 2
>> A+B % sum of A and B
ans =
16 4 10
4 10 16
10 16 4
>> A*B % standard linear algebra matrix multiplication
ans =
101 71 53
c⃝2011 Stefania Tracogna, SoMSS, ASU
MATLAB sessions: Laboratory 2
71 83 71
53 71 101
>> A.*B % coefficient-wise multiplication
ans =
64 3 24
3 25 63
24 63 4
⋆ One MATLAB command is especially relevant when studying the solution of linear systems of dif-
ferentials equations: x=A\b determines the solution x = A−1b of the linear system Ax = b. Here is an
example:
>> A=magic(3);
>> z=[1,2,3]’ % same as z=[1;2;3]
z =
1
2
3
>> b=A*z
b =
28
34
28
>> x = A\b % solve the system Ax = b. Compare with the exact solution, z, defined above.
x =
1
2
3
>> y =inv(A)*b % solve the system using the inverse: less efficient and accurate
ans =
1.0000
2.0000
3.0000
Now let’s check for accuracy by evaluating the difference z − x and z − y. In exact arithmetic they
should both be zero since x, y and z all represent the solution to the system.
>> z - x % error for backslash command
ans =
0
0
0
>> z - y % error for inverse
ans =
1.0e-015 *
-0.4441
0
-0.88 ...
MATLAB DOCUMENTATION ON SOME OF THE MODULES
A.Generate videos in which a skeleton of a person doing the following Gestures.
1.Tilting his head to right and left
2.Tilting his hand to right and left
3.Walking
in matlab.
B. Write a MATLAB program that converts a decimal number to Roman number and vice versa.
C.Using EZ plot & anonymous functions plot the following:
· Y=Sqrt(X)
· Y= X^2
· Y=e^(-XY)
D.Take your picture and
· Show R, G, B channels along with RGB Image in same figure using sub figure.
· Convert into HSV( Hue, saturation and value) and show the H,S,V channels along with HSV image
E.Record your name pronounced by yourself. Try to display the signal(name) in a plot vs Time, using matlab.
F.Write a script to open a new figure and plot five circles, all centered at the origin and with increasing radii. Set the line width for each circle to something thick (at least 2 points), and use the colors from a 5-color jet colormap (jet).
G. NEWTON RAPHSON AND SECANT METHOD
H.Write any one of the program to do following things using file concept.
1.Create or Open a file
2. Read data from the file and write data to another file
3. Append some text to already existed file
4. Close the file
I.Write a function to perform following set operations
1.Union of A and B
2. Intersection of A and B
3. Complement of A and B
(Assume A= {1, 2, 3, 4, 5, 6}, B= {2, 4, 6})
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
PHP Frameworks: I want to break free (IPC Berlin 2024)
Matlab 1
1. POLYTECHNIC UNGKU OMAR
ELECTRICAL ENGINEERING DEPARTMENT
Course : E5124 DATA COMMUNICATION (Lab work)
Experiment : Matlab 1 – Get Familiarize (Matrices and Plot)
The objective of this session is to learn:
- How to launch the matlab software
- Few simple calculations and formulation
- Plot command and graphical output
Introduction
Matlab is a tool for doing numerical computations with matrices and vectors. It can also display information
graphically. The best way to learn what Matlab can do is to work through some examples at the computer. After
reading and familiarize with this exercise you will be able to solve construct own work.
Starting MATLAB
Launch MATLAB by double-clicking on the MATLAB icon on your Windows desktop. When you start MATLAB, a
special window called the MATLAB desktop appears. The desktop is a window that contains other windows. The
major tools within or accessible from the desktop are (refer Fig 1):
- The Command Window
- The Command History
- The Workspace
- The Current Directory
- The Help Browser
- The Start button
1
2. Fig 1 : The graphical interface to the Matlab workspace
Table below shows arithmetic operators for calculation and equation in Matlab application.
As an example of a simple interactive calculation, just type the expression you want to evaluate. Let's start at the
very beginning. For example, let's suppose you want to calculate the expression, 1 + 2 x 3. You type it at the prompt
command (>>) as follows,
2
3. >> 1+2*3
ans =
7
You will have noticed that if you do not specify an output variable, MATLAB uses a default variable ans, short for
answer, to store the results of the current calculation. Note that the variable ans is created (or overwritten, if it is
already existed). To avoid this, you may assign a value to a variable or output argument name. For example,
>> x = 1+2*3
x=
7
will result in x being given the value 1 + 2 x 3 = 7. This variable name can always be used to refer to the results of the
previous computations. Therefore, computing 4x will result in
>> 4*x
ans =
28.0000
Exercise
1. Matrix
1.1 Insert the following expression and observe the result.
>>aa=[l 3 4; 5 7 8; 2 3 5]
Observation
>> y=[10; 9; 8]
Observation
3
4. 1.2 Insert both expressions.
>>aa=[l 3 4; 5 7 8; 2 3 5];
>> y=[10; 9; 8];
Now obtain result for following expression
>>aay
Observation
>>inv(aa)*y
Observation
>> [inv(aa)*y aay]
Observation
Explain your observation for expression [inv(aa)*y aay]
_____________________________________________________________________________________
_____________________________________________________________________________________
2. Matrix Loop
2.1 Insert following expression and obtain result
4
5. >> a = [ 0.8 0.1; 0.2 0.9 ]
Observation
>> x = [ 1; 0 ]
Observation
2.2 Type below expression and state your observation
>> a = [ 0.8 0.1; 0.2 0.9 ];
>> x = [ 1; 0 ];
>> for i = 1:20, x = a*x, end
Observation
5
6. 3. Plot
MATLAB has an excellent set of graphic tools. Plotting a given data set or the results of computation is
possible with very few commands. You are highly encouraged to plot mathematical functions and results of
analysis as often as possible. Trying to understand mathematical equations with graphics is an enjoyable and
very e±cient way of learning mathematics. Being able to plot mathematical functions and data freely is the
most important step, and this section is written to assist you to do just that.
3.1 Let say, your given few samples of variable which need to find out their performance rate. Now, insert following
expression:-
>> a=[1 2 3 4 6 4 3 4 5]
Observation
>> b=a+2
Observation
3.2 Use plot command to plot your result.
>> plot(b)
Observation
>> grid on
Observation
6
7. 3.3 Use label and title command to provide information at graph. Type this command step by step in order to
observe result. Before you type command, display your Matlab window panel and graph window side by
side in order to get better view.
>> xlabel('Sequence of b')
>> ylabel('b value')
>> title(‘Graphical output for b sequence of number’)
Observation
3.4 Bar command used to plot bar graph which able to show us the statistical result.
>> bar(b)
>> xlabel('Number of sample')
>> ylabel('Weight of random samples in kg')
Observation
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8. >> plot(b,'*')
>> axis([0 12 0 10])
Observation
What did you see from both graphs? Explain.
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3.5 To make a graph of y = sin(t) on the interval t = 0 to t = 10, do the following steps:
>> t = 0:.3:10;
>> y = sin(t);
>> plot(t,y)
>> title('Sine wave ')
>> xlabel(‘Time, t')
>> ylabel('Amplitude')
Observation
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9. 3.6 Plotting multiple wave or result in single graph. Execute following command and make your observation.
Insert title and label by yourself.
>> t=0:0.1:30;
>> y1=sin(t);
>> y2=cos(t);
>> plot(t,y1,'--',t,y2,'-r')
Observation
>> t=0:0.1:30;
>> y1=sin(t).*t;
>> y2=cos(t).*t;
>> plot(t,y1,'--',t,y2,'-r')
Observation
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10. 3.7 Subplot
The subplot is used to put multiple plots on the same MATLAB figure window.
subplot(pqr) - p & q represent matrixes, r locating position for plotted graph
a) Write the following expression and obtain the result.
>> x = 0 : 0.1 : 3 *pi;
>> y = sin(x);
>> z = cos(x);
>> subplot(222)
>> plot(x,y)
>> title('Sine wave y')
>> xlabel('time, x')
>> ylabel('Amplitude, y')
>> subplot(223)
>> title('x and z')
>> subplot(224)
>> plot(x,y,'-',x,z,' -- ')
>> title('x and [y z]')
b) Once complete your subplot, insert label and title for each graph individually. Use example as given in
above command.
Observation
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11. c) Discrete sample graphical output.
Type following command and make observation. State the differences between both results.
>> p=0:0.05:5;
>> q=sin(p.^2);
>> plot(p,q);
Observation
>> p=0:0.05:5;
>> q=sin(p.^2);
>> stem(p,q);
Observation
Reflection
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