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
In MATLAB, a vector is created by assigning the elements of the vector to a variable. This can be done in several ways depending on the source of the information.
—Enter an explicit list of elements
—Load matrices from external data files
—Using built-in functions
—Using own functions in M-files
This presentation displays the applications of CNNs, a quick review about Neural Networks and their drawbacks, the convolution process, padding, striding, convolution over volume, types of layers in CNN, max pool layer, fully connected layer, and lastly the famous CNNs, LetNet-5, AlexNet, VGG-16, ResNet and GoogLeNet.
Matlab is basically a high level language which has many specialized toolboxes for making things easier for us.
Matlab stands for MATrix LABoratory.
The first version of MATLAB was produced in the mid 1970s as a teaching tool. MATLAB started as an interactive program for doing matrix calculations.
MATLAB has now grown to a high level mathematical language that can solve integrals and differential equations numerically and plot a wide variety of two and three Dimensional graphs.
The expanded MATLAB is now used for calculations and simulation in companies and government labs ranging from aerospace, car design, signal analysis through to instrument control and financial analysis.
In practice, it provides a very nice tool to implement numerical method.
- The desktop includes these panels:
Current Folder — Access your files.
Command Window — Enter commands at the command line, indicated by the prompt (>>).
Workspace — Explore data that you create or import from files.
- what we learn:
1- Introduction to Matlab.
2- MATLAB InstallationVersion 2018.
3- Assignment.
4- Operations in MATLAB.
5- Vectors and Matrices in MATLAB.
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
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.
A Powerpoint Presentation designed to provide beginners to MATLAB an introduction to the MATLAB environment and introduce them to the fundamentals of MATLAB including matrix generation and manipulation, Arrays, MATLAB Graphics, Data Import and Export, etc
발표자: 이인웅 (연세대 박사과정)
발표일: 2017.12.
개요:
영상에서 사람의 행동을 인식하는 방법은 크게 영상에서 직접적으로 행동 라벨을 추출하는 것과 자세 정보를 기반으로 행동 라벨을 추출하는 것으로 나뉠 수 있습니다.
본 발표는 행동 인식에 대한 전반적인 개요를 설명하고 그 중에서도 사람의 자세 정보를 기반으로 하는 행동 인식 기술에 초점을 두고 최근 ICCV 2017 학회에서 발표된 Temporal Sliding LSTM 네트워크를 활용한 행동 인식 기술을 중점적으로 설명합니다. 구체적으로, 스켈레톤 기반 행동 인식 이슈, 제안하는 방법과 실험 결과들이 소개되고 앞으로 나아갈 만한 새로운 연구 이슈들도 추가적으로 설명합니다.
One-shot learning is an object categorization problem in computer vision. Whereas most machine learning based object categorization algorithms require training on hundreds or thousands of images and very large datasets, one-shot learning aims to learn information about object categories from one, or only a few, training images
In MATLAB, a vector is created by assigning the elements of the vector to a variable. This can be done in several ways depending on the source of the information.
—Enter an explicit list of elements
—Load matrices from external data files
—Using built-in functions
—Using own functions in M-files
This presentation displays the applications of CNNs, a quick review about Neural Networks and their drawbacks, the convolution process, padding, striding, convolution over volume, types of layers in CNN, max pool layer, fully connected layer, and lastly the famous CNNs, LetNet-5, AlexNet, VGG-16, ResNet and GoogLeNet.
Matlab is basically a high level language which has many specialized toolboxes for making things easier for us.
Matlab stands for MATrix LABoratory.
The first version of MATLAB was produced in the mid 1970s as a teaching tool. MATLAB started as an interactive program for doing matrix calculations.
MATLAB has now grown to a high level mathematical language that can solve integrals and differential equations numerically and plot a wide variety of two and three Dimensional graphs.
The expanded MATLAB is now used for calculations and simulation in companies and government labs ranging from aerospace, car design, signal analysis through to instrument control and financial analysis.
In practice, it provides a very nice tool to implement numerical method.
- The desktop includes these panels:
Current Folder — Access your files.
Command Window — Enter commands at the command line, indicated by the prompt (>>).
Workspace — Explore data that you create or import from files.
- what we learn:
1- Introduction to Matlab.
2- MATLAB InstallationVersion 2018.
3- Assignment.
4- Operations in MATLAB.
5- Vectors and Matrices in MATLAB.
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
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.
A Powerpoint Presentation designed to provide beginners to MATLAB an introduction to the MATLAB environment and introduce them to the fundamentals of MATLAB including matrix generation and manipulation, Arrays, MATLAB Graphics, Data Import and Export, etc
발표자: 이인웅 (연세대 박사과정)
발표일: 2017.12.
개요:
영상에서 사람의 행동을 인식하는 방법은 크게 영상에서 직접적으로 행동 라벨을 추출하는 것과 자세 정보를 기반으로 행동 라벨을 추출하는 것으로 나뉠 수 있습니다.
본 발표는 행동 인식에 대한 전반적인 개요를 설명하고 그 중에서도 사람의 자세 정보를 기반으로 하는 행동 인식 기술에 초점을 두고 최근 ICCV 2017 학회에서 발표된 Temporal Sliding LSTM 네트워크를 활용한 행동 인식 기술을 중점적으로 설명합니다. 구체적으로, 스켈레톤 기반 행동 인식 이슈, 제안하는 방법과 실험 결과들이 소개되고 앞으로 나아갈 만한 새로운 연구 이슈들도 추가적으로 설명합니다.
One-shot learning is an object categorization problem in computer vision. Whereas most machine learning based object categorization algorithms require training on hundreds or thousands of images and very large datasets, one-shot learning aims to learn information about object categories from one, or only a few, training images
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/SIMULINK for Engineering Applications day 2:Introduction to simulinkreddyprasad reddyvari
3 days Hands on workshop on MATLAB/SIMULINK for Engineering Applications:
this workshop aims to make students to aware of MATLAB to do own projects in engineering life with best available technology E-Simulink Softwares and tools.
Computers and Programming , Programming Languages Types, Problem solving, Introduction to the MATLAB environment, Using MATLAB Documentation
Introduction to the course, Operating methodology-Installation Procedure
1. Compare a sample code in C with MATLAB
2. Trajectory of a particle in projectile motion ( solving quadratic equations)
3. Ideal gas law problem to find volume
Performing Manual and Automated Iterations in Engineering Equation Solver (EES) - Examples from Heat Transfer.
All the EES codes shown in the examples are available at: https://goo.gl/KExGFi
Learn how to model thermoelectric generator (TEG) modules when powered by solar energy. The advanced modeling is available here: https://www.researchgate.net/project/Solar-Thermoelectric-Generator
Outline:
1. Introduction
2. Solar Energy
3. Wind Energy
4. Hydropower
5. Biomass Energy
6. Geothermal Energy
7. Wave and Tidal Energy
Note: This is only the introduction part of a very big presentation. Please download the full version from here:
https://goo.gl/bXRLGd
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
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This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
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Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
2. Outline
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
naveedurrehman.com
3. Outline
8. Matrices and string arrays
9. Introduction to graphics
10. Loops
11. Custom functions and M-files
naveedurrehman.com
4. Introduction
• MATLAB stands for Matrix Laboratory
• The system was designed to make matrix
computations particularly easy
• It is a powerful computing system for
handling scientific and engineering
calculations.
• MATLAB system is Interpreter.
naveedurrehman.com
6. Introduction
Why MATLAB?
naveedurrehman.com
• MATLAB can be used interactively
• Easy format: Many science and
engineering problems can be solved by
entering one or two commands
• Rich with 2D and 3D plotting capabilities
• Countless libraries and still developing
7. Introduction
What you should already know?
naveedurrehman.com
• The mathematics associated with the
problem you want to solve in MATLAB.
• The logical plan or algorithm for solving a
particular problem.
8. Introduction
What to learn in MATLAB?
naveedurrehman.com
• The exact rules for writing MATLAB
statements and using MATLAB utilities
• Converting algorithm into MATLAB
statements and/or program
9. Introduction
What you will learn with experience?
naveedurrehman.com
• To design, develop and implement
computational and graphical tools to do
relatively complex problems
• To develop a toolbox of your own that
helps you solve problems of interest
• To adjust the look of MATLAB to make
interaction more user-friendly
12. Introduction
Using command prompt:
naveedurrehman.com
• Command line: The line with >> prompt
• Command-line editing:
• Use Backspace, Left-arrow, Right-arrow
• Up-arrow and Down-arrow for accessing history
• Smart recall: type some character and press Up-
arrow and Down-arrow
• Execution: Enter
27. Matrices
naveedurrehman.com
X = [1 2; 3 4]
Y = 2 .* X
Scalar operations with matrix:
X = [1 2; 3 4]
Y = [5 6; 7 8]
Z = X.*Y
Scalar operations between matrices:
37. Polynomials
naveedurrehman.com
P = [1 7 0 -5 9]
A polynomial can be represented as a vector.
Example:
To solve a polynomial at some value of x:
polyval(P,4)
52. Symbolic diff. and int.
naveedurrehman.com
Differentiation:
syms t
f = 3*t^2 + 2*t^(-2);
diff(f)
Integration and area under the curve:
syms x
f = 2*x^5
int(f)
area = double(int(f, 1.8, 2.3))
53. Symbolic expand and collect
naveedurrehman.com
Expand:
syms x
syms y
expand((x-5)*(x+9))
expand(sin(2*x))
expand(cos(x+y))
54. Symbolic factor. and simplification
naveedurrehman.com
Factorization:
syms x
syms y
factor(x^3 - y^3)
Simplification:
syms x
syms y
simplify((x^4-16)/(x^2-4))
56. Complex numbers
naveedurrehman.com
S = sqrt(Z) % using De Moivre's formula
More functions:
E = exp(Z)
A = angle(Z) % in radians
In polar coordinates:
M = abs(Z) % magnitude
57. M-Files: Programming mode
naveedurrehman.com
M-Files are also called Matlab program files.
• Go to File > New > M-File or just type edit
to start with a new m-file.
• Always save M-File file before execution.
Ctrl+S can be used as keyboard shortcut.
• To execute codes, use F5. If the Current
Directory is set, you may drag-drop the
file or type its file name (with out
extension).
59. Resetting in M-Files
naveedurrehman.com
Use clear and clc in the beginning of any
program. This will:
1. Delete all variables from workspace
2. Wipe the command window and set
cursor at top.
60. Comments in M-Files
naveedurrehman.com
1. Use % symbol before program comments.
2. The Comment and Uncomment submenu
in Text menu in editor’s tab can also be
used.
3. Program comments are not read by
MATLAB interpreter.
64. Sample program: Vertical Motion
naveedurrehman.com
g = 9.81; % acceleration due to gravity
u = 60; % initial velocity in metres/sec
t = 0 : 0.1 : 12.3; % time in seconds
s = u .* t + g / 2 .* t .^ 2; % vertical displacement in metres
plot(t, s)
title( 'Vertical motion under gravity' )
xlabel( 'time' )
ylabel( 'vertical displacement' )
grid
disp( [t' s'] ) % display a table
65. Taking input from user
naveedurrehman.com
Use input function to take input from user.
A = input('How many apples: ');
Numeric input:
N = input('Enter your name: ','s');
String input:
67. Saving and loading via files
naveedurrehman.com
save and load commands are used to save
and load a variable via files:
A = rand(3,3);
save record.txt A -ascii
C = load('record.txt')
Files can be generated by external programs
or data loggers can be read using load.
68. Communication with MS Excel
naveedurrehman.com
csvread and csvwrite commands are used to
read and save variable in MS Excel format file:
A = rand(3,3);
csvwrite('record.csv',A)
B = csvread('record.csv')
70. Relational operators
naveedurrehman.com
5 > 3
A = 5;
B = 10;
C = B >= A
== Equals to
< Less than
> Greater than
<= Less than or equals to
>= Greater than or equals to
~= Not equals to
71. Logical operators
naveedurrehman.com
(5 > 3) & (10 < 4)
A = 5;
B = 10;
C = 30;
D = 100;
E = (B >= A) | (D<C)
~ Logical Not
| Logical OR
& Logical AND
AND
1 & 1 = 1
1 & 0 = 0
0 & 1 = 0
0 & 0 = 0
OR
1 | 1 = 1
1 | 0 = 1
0 | 1 = 1
0 | 0 = 0
72. Condition using if constructs
naveedurrehman.com
if predicate
statements
end
if predicate
statements
else
statements
end
if predicate
statements
elseif predicate
statements
elseif predicate
statements
end
if predicate
statements
elseif predicate
statements
else
statements
end
1
2
3 4
82. Logical vectors
naveedurrehman.com
The elements of a logical vector are either 1
or 0. In the following example, G and H are
logical vectors:
R = rand(1,10);
G = R>0.5;
H = (R>=0.5) | (R<=0.3);
99. Example: Palindrome!
naveedurrehman.com
Ask user to input a number. Check if it is
palindrome or not.
Hint:
A palindrome number is a number such that if
we reverse it, it will not change. Use:
1. num2str: converts number to a string
2. fliplr: flips a string, left to right
3. str2num: converts string to a number
100. Example: Projectile motion
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Ask user to enter initial velocity and angle from
horizontal for a projectile motion.
Calculate:
1. Range
2. Flight time
3. Max. height
Also plot:
1. Projectile trajectory (x vs. y)
2. Projectile angle vs. speed
104. Example: pi using Monte Carlo
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R
Area of circle / Area of square = pi*r^2 / (2r)^2
C / S = pi / 4
pi = 4 * C / S
Prove that the
value of pi is 3.142
105. Example: pi using Monte Carlo
naveedurrehman.com
Procedure:
1. Throw T number of darts
2. Count the number of darts falling inside Circle (C)
3. Count the number of darts falling inside Square (S)
4. Calculate pi = 4 * C / S
106. Example: pi using Monte Carlo
naveedurrehman.com
Hint:
1. Assume that radius (R) is 1 unit.
2. Generate T number of X and Y random numbers
between 0 and 1. Let the dart fall on square at
(X,Y).
3. Calculate position of dart by P2 = X2 + Y2
4. Increment in C if P <= 1
5. Darts inside square will be S = T
111. M-File functions
naveedurrehman.com
function [sum,avg] = mysumavg(n1, n2, n3)
%This function calculates the sum and
% average of the three given numbers
sum = n1+n2+n3;
avg = sum/3;
mysumavg.m:
[thesum,theavg] = mysumavg(1,2,3)
program.m:
113. M-File functions with subfunctions
naveedurrehman.com
function [o1,o2…] = function(in1,in2…)
….
end
function [o1,o2…] = subfunction(in1,in2…)
….
end
function.m:
114. M-File functions with subfunctions
naveedurrehman.com
Note:
1. File name should be as same as main
function’s name
2. Variables of main function are unknown
in subfunction
3. Variables of sub function are unknown in
main function
115. M-File functions with subfunctions
naveedurrehman.com
Write a function to calculate roots of a
quadratic equation. The discriminant should
be calculated in a sub function.
116. M-File functions with nested funcs
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function [o1,o2…] = function(in1,in2…)
….
function [o1,o2…] = nestfunction(in1,in2…)
….
End
…
end
function.m:
117. M-File functions with nested funcs
naveedurrehman.com
Note:
1. File name should be as same as main
function’s name
2. Variables of main function and sub
functions are known.
118. M-File functions with nested funcs
naveedurrehman.com
Write a function calculate roots of a
quadratic equation. The discriminant should
be calculated in a nested function.