This is an introduction to MATLAB. It was prepared for 4th grade students at university of Khartoum - surveying engineering department - along with the geometrical geodesy course.
Matlab for beginners, Introduction, signal processingDr. Manjunatha. P
The document provides an introduction and overview of MATLAB. It discusses that MATLAB was initially developed as a tool to help students learn linear algebra and is now a widely used software package for engineering and mathematical problems. The document then covers various MATLAB windows and basics like variables, matrices, plot commands, m-files, and flow control structures like for loops and if/else statements. It also provides examples of plotting functions and creating graphs with labels and titles.
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.
This document introduces MATLAB by covering topics like using it as a calculator, entering vectors and matrices, performing matrix operations and solving equations, plotting graphs, and more. It provides examples of basic arithmetic, creating and manipulating variables and matrices, plotting data, and solving systems of equations. Resources for learning more about MATLAB are also mentioned.
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
This document provides an overview of how to work with matrices in R. It discusses how to create vectors and matrices, perform basic operations like transposes and matrix multiplication, and calculate values like determinants and eigenvectors. The document demonstrates functions like matrix(), c(), t(), %*%, diag(), det(), solve(), and eigen() through examples of creating, manipulating, and analyzing matrices in R.
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
The document provides an overview of MATLAB, including what it is used for, its graphical user interface, help features, toolboxes, and how to connect to other programs. MATLAB is a numerical computing environment and programming language. It was originally designed for matrix manipulations but has been expanded to include tools for data analysis, signal processing, optimization, and more. Key aspects of MATLAB covered in the document include its command-line interface, workspace, command history, help system, built-in functions, matrices, plotting capabilities, and toolboxes for specialized tasks.
Matlab for beginners, Introduction, signal processingDr. Manjunatha. P
The document provides an introduction and overview of MATLAB. It discusses that MATLAB was initially developed as a tool to help students learn linear algebra and is now a widely used software package for engineering and mathematical problems. The document then covers various MATLAB windows and basics like variables, matrices, plot commands, m-files, and flow control structures like for loops and if/else statements. It also provides examples of plotting functions and creating graphs with labels and titles.
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.
This document introduces MATLAB by covering topics like using it as a calculator, entering vectors and matrices, performing matrix operations and solving equations, plotting graphs, and more. It provides examples of basic arithmetic, creating and manipulating variables and matrices, plotting data, and solving systems of equations. Resources for learning more about MATLAB are also mentioned.
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
This document provides an overview of how to work with matrices in R. It discusses how to create vectors and matrices, perform basic operations like transposes and matrix multiplication, and calculate values like determinants and eigenvectors. The document demonstrates functions like matrix(), c(), t(), %*%, diag(), det(), solve(), and eigen() through examples of creating, manipulating, and analyzing matrices in R.
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
The document provides an overview of MATLAB, including what it is used for, its graphical user interface, help features, toolboxes, and how to connect to other programs. MATLAB is a numerical computing environment and programming language. It was originally designed for matrix manipulations but has been expanded to include tools for data analysis, signal processing, optimization, and more. Key aspects of MATLAB covered in the document include its command-line interface, workspace, command history, help system, built-in functions, matrices, plotting capabilities, and toolboxes for specialized tasks.
This document provides an overview of data types and operators in MATLAB. It discusses the main data types including matrices, vectors, strings, structures, cell arrays, and numeric precision. It describes how to create and manipulate different data types using vectors, indexing, and the colon operator. The document also covers common operators for arithmetic, relational, logical, and bitwise operations. Structures are highlighted as useful for passing arguments to functions or making code robust against changes.
This document discusses the importance and advantages of MATLAB. It notes that MATLAB has matrices as its basic data element, supports vectorized operations, and has built-in graphical and statistical functions. Toolboxes can further expand MATLAB's functionality. While it uses more memory and CPU time than other languages, MATLAB allows both command line and programming capabilities. The document provides examples of how to create matrices, perform operations on matrices using functions like sum(), transpose(), and indexing. It also discusses matrix multiplication and how operations depend on matrix dimensions.
MATLAB is a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numeric computation. It allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages. MATLAB is widely used in engineering and science fields as well as finance, and it supports a variety of applications. Some key capabilities include data analysis and visualization, numeric computation, algorithm and system modeling and simulation, and customizable programming.
Advanced MATLAB Tutorial for Engineers & ScientistsRay Phan
This is a more advanced tutorial in the MATLAB programming environment for upper level undergraduate engineers and scientists at Ryerson University. The first half of the tutorial covers a quick review of MATLAB, which includes how to create vectors, matrices, how to plot graphs, and other useful syntax. The next part covers how to create cell arrays, logical operators, using the find command, creating Transfer Functions, finding the impulse and step response, finding roots of equations, and a few other useful tips. The last part covers more advanced concepts such as analytically calculating derivatives and integrals, polynomial regression, calculating the area under a curve, numerical solutions to differential equations, and sorting arrays.
This document provides an introduction and overview of MATLAB. It discusses MATLAB basics like the command window and variables. It also covers topics like working with matrices, vectors, plotting, scripts and functions. Specific MATLAB commands covered include plot, mesh, surf, contour and more. Functions like length, dot, cross and special matrices like ones, zeros and eye are also explained.
This document provides an overview of optimization techniques that can be performed using MATLAB. It discusses unconstrained optimization problems where the goal is to minimize or maximize an objective function without any constraints on the variables. Constrained optimization problems are also discussed, where the goal is to optimize the objective function subject to certain equality and inequality constraints. MATLAB functions like fminsearch and fmincon can be used to find the optimal solution for unconstrained and constrained problems respectively. Gradient-based methods for solving constrained optimization problems are also briefly covered.
General principles and tricks for writing fast MATLAB code.
Powerpoint slides: https://uofi.box.com/shared/static/yg4ry6s1c9qamsvk6sk7cdbzbmn2z7b8.pptx
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
MATLAB/SIMULINK for Engineering Applications day 2:Introduction to simulinkreddyprasad reddyvari
The document provides an introduction to MATLAB and Simulink through a presentation. It discusses what MATLAB and Simulink are, their basic functions and capabilities, and how to get started using them. The presentation covers topics such as vectors, matrices, plotting, control structures, M-files, and writing user-defined functions. The goal is to help attendees gain basic knowledge of MATLAB/Simulink and be able to explore them on their own.
This presentation provides an introduction to MATLAB. It discusses what MATLAB is, its advantages and disadvantages, typical uses, and how to start the MATLAB environment. It demonstrates basic MATLAB commands like plotting a sine wave and performing calculations. It also covers different types of files used in MATLAB like M-files, MAT-files and MEX-files. The presentation shows how to address matrices, perform matrix operations, and use functions to build matrices. It encourages viewers to access the online MATLAB helpdesk for additional information and support.
The document provides an introduction to MATLAB. It discusses that MATLAB is a numerical computing environment and programming language. It can be used for matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages. The document then covers various MATLAB basics like the MATLAB environment, matrix operations, data types, mathematical and logical operators, and plotting functions. It provides examples of creating and manipulating matrices and vectors in MATLAB.
This document introduces the open-source software FreeMat, which provides basic MATLAB functions for numerical computing and plotting. It covers entering vectors and matrices, performing arithmetic operations and matrix products, using FreeMat to solve linear equations, and plotting basic graphs. FreeMat is an alternative to MATLAB that lacks some toolboxes but works for basic functions. The workshop teaches essential skills like variable names, order of operations, and matrix inversion.
CETPA INFOTECH PVT LTD is one of the IT education and training service provider brands of India that is preferably working in 3 most important domains. It includes IT Training services, software and embedded product development and consulting services.
http://www.cetpainfotech.com
The document discusses various plotting commands and functions in MATLAB. It begins with an outline of topics to be covered, which include the plot command, line specifications, additional plot commands, the fplot command for plotting functions, plotting 2D and 3D functions, and plotting complex numbers. Examples are provided to illustrate how to use the plot command to plot basic functions, combine multiple plots, and customize line properties. Additional commands like hold on and gca are described for combining plots and modifying axis properties. The document provides guidance on plotting, customizing plots, and saving figure files in MATLAB.
This document provides an introduction and overview of MATLAB. It covers MATLAB basics like matrices and arrays, plotting, and functions. The document is divided into sections on MATLAB desktop basics, matrices and arrays, graphics like line plots, programming and scripts, and help/documentation. It is intended as training material for a lab course on signal processing using MATLAB.
- The document provides an introduction to linear algebra and MATLAB. It discusses various linear algebra concepts like vectors, matrices, tensors, and operations on them.
- It then covers key MATLAB topics - basic data types, vector and matrix operations, control flow, plotting, and writing efficient code.
- The document emphasizes how linear algebra and MATLAB are closely related and commonly used together in applications like image and signal processing.
This document provides an introduction to MATLAB. It discusses what MATLAB is, how to perform basic matrix operations and use script files and M-files. It also covers some common MATLAB commands and functions. MATLAB can be used for applications like plotting, image processing, robotics and GUI design. Key topics covered include matrices, vectors, scalars, matrix operations, logical and relational operators, selection and repetition structures, and reading/writing data files. Plotting functions allow creating graphs and 3D surface plots. Image processing, robotics and GUI design are listed as potential application areas.
MATLAB is a high-level programming language and interactive environment for numerical computation, visualization, and programming. It is used widely in academia and industry in engineering and scientific fields. Some key points:
- MATLAB was developed by MathWorks and was originally created to provide easy access to matrix data and calculations.
- It includes a base program and various toolboxes for specialized tasks like fuzzy logic, neural networks, etc.
- MATLAB has a graphical user interface for interacting with data and visualizing results. It also allows programming in a matrix-based language.
- It is widely used for technical computing tasks like data analysis, modeling, simulation and algorithm development in many domains like engineering, science and education
This document provides information on generating and manipulating matrices in MATLAB. It discusses how to explicitly enter small matrices by separating elements with blanks/commas and rows with semicolons. Large matrices can be entered over multiple lines using the return button. Individual elements can be accessed and altered using indices in parentheses. Columns and rows can be appended to matrices using various commands. A colon is used to extract submatrices. Logical operators compare matrices and return 1s and 0s. Functions like diag(), fliplr(), flipud() and rot90() manipulate matrices. Random matrices can be generated using commands like rand() and ones(). Vectors subtracted from matrices using broadcasting. Example problems demonstrate generating matrices from vectors and manipulating the matrices.
This document provides an overview of MATLAB, including the MATLAB desktop, variables, vectors, matrices, matrix operations, array operations, built-in functions, data visualization, flow control using if and for statements, and user-defined functions. It introduces key MATLAB concepts like the command window, workspace, and editor. It also demonstrates how to create and manipulate variables, vectors, matrices, and plots in MATLAB.
This document discusses MATLAB and provides examples of generating common discrete time signals such as unit impulse, unit step, ramp, exponential and sawtooth signals. MATLAB is an interpreted language well-suited for matrix manipulation and contains built-in functions. Typical uses include math, modelling, data analysis and visualization. Scripts allow executing a series of commands and signals can be plotted versus time or index.
This document provides an overview of data types and operators in MATLAB. It discusses the main data types including matrices, vectors, strings, structures, cell arrays, and numeric precision. It describes how to create and manipulate different data types using vectors, indexing, and the colon operator. The document also covers common operators for arithmetic, relational, logical, and bitwise operations. Structures are highlighted as useful for passing arguments to functions or making code robust against changes.
This document discusses the importance and advantages of MATLAB. It notes that MATLAB has matrices as its basic data element, supports vectorized operations, and has built-in graphical and statistical functions. Toolboxes can further expand MATLAB's functionality. While it uses more memory and CPU time than other languages, MATLAB allows both command line and programming capabilities. The document provides examples of how to create matrices, perform operations on matrices using functions like sum(), transpose(), and indexing. It also discusses matrix multiplication and how operations depend on matrix dimensions.
MATLAB is a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numeric computation. It allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages. MATLAB is widely used in engineering and science fields as well as finance, and it supports a variety of applications. Some key capabilities include data analysis and visualization, numeric computation, algorithm and system modeling and simulation, and customizable programming.
Advanced MATLAB Tutorial for Engineers & ScientistsRay Phan
This is a more advanced tutorial in the MATLAB programming environment for upper level undergraduate engineers and scientists at Ryerson University. The first half of the tutorial covers a quick review of MATLAB, which includes how to create vectors, matrices, how to plot graphs, and other useful syntax. The next part covers how to create cell arrays, logical operators, using the find command, creating Transfer Functions, finding the impulse and step response, finding roots of equations, and a few other useful tips. The last part covers more advanced concepts such as analytically calculating derivatives and integrals, polynomial regression, calculating the area under a curve, numerical solutions to differential equations, and sorting arrays.
This document provides an introduction and overview of MATLAB. It discusses MATLAB basics like the command window and variables. It also covers topics like working with matrices, vectors, plotting, scripts and functions. Specific MATLAB commands covered include plot, mesh, surf, contour and more. Functions like length, dot, cross and special matrices like ones, zeros and eye are also explained.
This document provides an overview of optimization techniques that can be performed using MATLAB. It discusses unconstrained optimization problems where the goal is to minimize or maximize an objective function without any constraints on the variables. Constrained optimization problems are also discussed, where the goal is to optimize the objective function subject to certain equality and inequality constraints. MATLAB functions like fminsearch and fmincon can be used to find the optimal solution for unconstrained and constrained problems respectively. Gradient-based methods for solving constrained optimization problems are also briefly covered.
General principles and tricks for writing fast MATLAB code.
Powerpoint slides: https://uofi.box.com/shared/static/yg4ry6s1c9qamsvk6sk7cdbzbmn2z7b8.pptx
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
MATLAB/SIMULINK for Engineering Applications day 2:Introduction to simulinkreddyprasad reddyvari
The document provides an introduction to MATLAB and Simulink through a presentation. It discusses what MATLAB and Simulink are, their basic functions and capabilities, and how to get started using them. The presentation covers topics such as vectors, matrices, plotting, control structures, M-files, and writing user-defined functions. The goal is to help attendees gain basic knowledge of MATLAB/Simulink and be able to explore them on their own.
This presentation provides an introduction to MATLAB. It discusses what MATLAB is, its advantages and disadvantages, typical uses, and how to start the MATLAB environment. It demonstrates basic MATLAB commands like plotting a sine wave and performing calculations. It also covers different types of files used in MATLAB like M-files, MAT-files and MEX-files. The presentation shows how to address matrices, perform matrix operations, and use functions to build matrices. It encourages viewers to access the online MATLAB helpdesk for additional information and support.
The document provides an introduction to MATLAB. It discusses that MATLAB is a numerical computing environment and programming language. It can be used for matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages. The document then covers various MATLAB basics like the MATLAB environment, matrix operations, data types, mathematical and logical operators, and plotting functions. It provides examples of creating and manipulating matrices and vectors in MATLAB.
This document introduces the open-source software FreeMat, which provides basic MATLAB functions for numerical computing and plotting. It covers entering vectors and matrices, performing arithmetic operations and matrix products, using FreeMat to solve linear equations, and plotting basic graphs. FreeMat is an alternative to MATLAB that lacks some toolboxes but works for basic functions. The workshop teaches essential skills like variable names, order of operations, and matrix inversion.
CETPA INFOTECH PVT LTD is one of the IT education and training service provider brands of India that is preferably working in 3 most important domains. It includes IT Training services, software and embedded product development and consulting services.
http://www.cetpainfotech.com
The document discusses various plotting commands and functions in MATLAB. It begins with an outline of topics to be covered, which include the plot command, line specifications, additional plot commands, the fplot command for plotting functions, plotting 2D and 3D functions, and plotting complex numbers. Examples are provided to illustrate how to use the plot command to plot basic functions, combine multiple plots, and customize line properties. Additional commands like hold on and gca are described for combining plots and modifying axis properties. The document provides guidance on plotting, customizing plots, and saving figure files in MATLAB.
This document provides an introduction and overview of MATLAB. It covers MATLAB basics like matrices and arrays, plotting, and functions. The document is divided into sections on MATLAB desktop basics, matrices and arrays, graphics like line plots, programming and scripts, and help/documentation. It is intended as training material for a lab course on signal processing using MATLAB.
- The document provides an introduction to linear algebra and MATLAB. It discusses various linear algebra concepts like vectors, matrices, tensors, and operations on them.
- It then covers key MATLAB topics - basic data types, vector and matrix operations, control flow, plotting, and writing efficient code.
- The document emphasizes how linear algebra and MATLAB are closely related and commonly used together in applications like image and signal processing.
This document provides an introduction to MATLAB. It discusses what MATLAB is, how to perform basic matrix operations and use script files and M-files. It also covers some common MATLAB commands and functions. MATLAB can be used for applications like plotting, image processing, robotics and GUI design. Key topics covered include matrices, vectors, scalars, matrix operations, logical and relational operators, selection and repetition structures, and reading/writing data files. Plotting functions allow creating graphs and 3D surface plots. Image processing, robotics and GUI design are listed as potential application areas.
MATLAB is a high-level programming language and interactive environment for numerical computation, visualization, and programming. It is used widely in academia and industry in engineering and scientific fields. Some key points:
- MATLAB was developed by MathWorks and was originally created to provide easy access to matrix data and calculations.
- It includes a base program and various toolboxes for specialized tasks like fuzzy logic, neural networks, etc.
- MATLAB has a graphical user interface for interacting with data and visualizing results. It also allows programming in a matrix-based language.
- It is widely used for technical computing tasks like data analysis, modeling, simulation and algorithm development in many domains like engineering, science and education
This document provides information on generating and manipulating matrices in MATLAB. It discusses how to explicitly enter small matrices by separating elements with blanks/commas and rows with semicolons. Large matrices can be entered over multiple lines using the return button. Individual elements can be accessed and altered using indices in parentheses. Columns and rows can be appended to matrices using various commands. A colon is used to extract submatrices. Logical operators compare matrices and return 1s and 0s. Functions like diag(), fliplr(), flipud() and rot90() manipulate matrices. Random matrices can be generated using commands like rand() and ones(). Vectors subtracted from matrices using broadcasting. Example problems demonstrate generating matrices from vectors and manipulating the matrices.
This document provides an overview of MATLAB, including the MATLAB desktop, variables, vectors, matrices, matrix operations, array operations, built-in functions, data visualization, flow control using if and for statements, and user-defined functions. It introduces key MATLAB concepts like the command window, workspace, and editor. It also demonstrates how to create and manipulate variables, vectors, matrices, and plots in MATLAB.
This document discusses MATLAB and provides examples of generating common discrete time signals such as unit impulse, unit step, ramp, exponential and sawtooth signals. MATLAB is an interpreted language well-suited for matrix manipulation and contains built-in functions. Typical uses include math, modelling, data analysis and visualization. Scripts allow executing a series of commands and signals can be plotted versus time or index.
MATLAB is a high-level programming language and computing environment used for numerical computations, visualization, and programming. The document discusses MATLAB's capabilities including its toolboxes, plotting functions, control structures, M-files, and user-defined functions. MATLAB is useful for engineering and scientific calculations due to its matrix-based operations and built-in functions.
This document provides an introduction and overview of image processing using Matlab. It discusses the basics of Matlab including its environment, syntax, variables, vectors and matrices. It then covers image processing topics such as importing and exporting images, viewing histograms, and applying filters like box filters and linear filters to images. The document is intended to teach the fundamentals of working with images in the Matlab programming language.
The document provides an introduction to MATLAB and Simulink. It describes MATLAB as a numerical computing environment and matrix laboratory that is used for data analysis, algorithm development, modeling, and more across many disciplines. Simulink is introduced as a block diagram environment for multi-domain simulation and model-based design. Key features and uses of MATLAB and Simulink are outlined, including acquiring and analyzing data, developing functions and algorithms, modeling and simulation.
This document provides an introduction to MATLAB programming. It discusses resources for the course including the course web page and slides. It then explains what MATLAB is, how to get started using it on Windows and Linux systems, and how to get help. It also covers the MATLAB desktop environment, performing calculations on the command line, entering numeric arrays, indexing into matrices, basic plotting commands, and logical indexing.
An Introduction to MATLAB for beginnersMurshida ck
This document provides an introduction to MATLAB, including:
- MATLAB is a program for numerical computation, originally designed for matrix operations. It has expanded capabilities for data analysis, signal processing, and other scientific tasks.
- The MATLAB desktop includes tools like the Command Window, Workspace, and Figure Window. Common commands are introduced for arithmetic, variables, arrays, strings and plots.
- Arrays in MATLAB can represent vectors and matrices. Commands are demonstrated for creating, manipulating, and performing operations on arrays.
This document provides an overview of MATLAB, its applications, and how to use its features. MATLAB can be used for numerical computation and was originally designed for matrix operations. It has since expanded to include tools for data analysis, signal processing, optimization, and more. The document describes MATLAB's basic interface and commands, how to work with matrices and vectors, perform math operations and logical operations, plot functions, write M-files and functions, and save and load work. It also briefly mentions Simulink for modeling and simulating dynamic systems.
MATLAB is a high-level technical computing language where everything is represented as a matrix. It has tools for doing mathematical computations and graphics. The MATLAB desktop provides menus, toolbars, and areas to view commands, workspace, and output. MATLAB supports defining vectors and matrices, basic matrix and array operations, built-in mathematical functions, 2D plotting, annotation, discrete data plotting using stem, and dividing plotting windows into subplots. Common commands include clear to remove variables and close to remove plots.
This document provides an introduction and overview of MATLAB. MATLAB is a high-performance language for technical computing, computation, visualization, and programming. It is useful for tasks like math and computation, algorithm development, modeling, simulation, data analysis, scientific and engineering graphics, and application development. MATLAB represents everything as matrices and is an interpreted language, so no compilation is needed. It has a vast library of functions and is widely used in teaching and research. While it is good for rapid prototyping, MATLAB may be slow for some processes and not well-suited for large-scale system development or web applications. The document provides examples of MATLAB code and discusses how images can be represented and manipulated as matrices in MATLAB.
INTRODUCTION TO MATLAB for PG students.pptKarthik537368
MATLAB is a high-performance language used for technical computing and programming. It allows matrix manipulation, computation, visualization, and algorithm development. MATLAB is well-suited for image processing and computer vision tasks because images can be represented as matrices and MATLAB contains extensive image processing functions. While MATLAB is easy to use and good for prototyping, it is slower than other languages for some processes and not designed for large-scale development.
This document provides a summary of a course on introduction to MATLAB. The course includes 7 lectures covering topics like variables, operations, plotting, visualization, programming, solving equations and advanced methods. It will have problem sets to be submitted after each lecture and requirements to pass include attending all lectures and completing all problem sets. The course materials provide an overview of MATLAB including getting started, creating and manipulating variables, and basic plotting.
Introduction to Matlab
Lecture 1:
Introduction: What is Matlab, History of Matlab, strengths, weakness
Getting familiar with the interface: Layout, Pull down menus
Creating and manipulating objects: Variables (scalars, vectors, matrices, text strings), Operators (arithmetic, relational, logical) and built-in functions
MATLAB is scientific computing environment. If you are student ( engineering,statics, mathematical modelling ) , MATLAB is great tool to accomplish task.
This is widely used tool in simulation, computation mathematics, engineering,
econometric modelling and lists goes on.
MATLAB is a matrix laboratory software package for numerical computation and visualization. It provides functions and tools for matrix manipulation, plotting and visualization, implementation of algorithms, data analysis, and numerical solution of problems. MATLAB has a programming language and interactive environment for algorithm development, data visualization, data analysis and numeric computation. It supports matrix and array operations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
This document provides an introduction and overview of MATLAB. It discusses what MATLAB is, its main features and interfaces. Some key points covered include:
- MATLAB is a computing environment for doing matrix manipulations, calculations and data analysis. It has specialized toolboxes for tasks like signal processing and system analysis.
- The main interfaces are the command window, workspace, command history and editor window. Commands can be executed directly, through script files or custom functions.
- MATLAB handles matrices and vectors natively and has extensive math and graphics functions. Basic operations include matrix/vector creation, arithmetic, plotting and flow control structures.
- Help is available through the help menu, demos and documentation. Common functions covered
Performance van Java 8 en verder - Jeroen BorgersNLJUG
We weten allemaal dat de grootste verbetering die Java 8 brengt de ondersteuning voor lambda-expressies is. Dit introduceert functioneel programmeren in Java. Door het toevoegen van de Stream API wordt deze verbetering nog groter: iteratie kan nu intern worden afgehandeld door een bibliotheek, je kunt daarmee nu het beginsel "Tell, don’t ask" toepassen op collecties. Je kunt gewoon vertellen dat er een ??functie uitgevoerd moet worden op je verzameling, of vertellen dat dat parallel, door meerdere cores moet gebeuren. Maar wat betekent dit voor de prestaties van onze Java-toepassingen? Kunnen we nu meteen volledig al onze CPU-cores benutten om betere responstijden te krijgen? Hoe werken filter / map / reduce en parallele streams precies intern? Hoe wordt het Fork-Join framework hierin gebruikt? Zijn lambda's sneller dan inner klassen? - Al deze vragen worden beantwoord in deze sessie. Daarnaast introduceert Java 8 meer performance verbeteringen: tiered compilatie, PermGen verwijdering, java.time, Accumulators, Adders en Map verbeteringen. Ten slotte zullen we ook een kijkje nemen in de keuken van de geplande performance verbeteringen voor Java 9: benutting van GPU's, Value Types en arrays 2.0.
Here are the key points about scalar-matrix addition in MATLAB:
- a is a scalar (single value)
- b is a matrix (2D array)
- To add a scalar to a matrix, MATLAB adds the scalar to each element of the matrix
- c = b + a performs element-wise addition, adding the value of a (which is 3) to each element of b
- The result c is the matrix b with 3 added to each element
So c would be:
c =
4 5 6
7 8 9
Scalar-matrix operations in MATLAB perform the operation on each element of the matrix.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
The CBC machine is a common diagnostic tool used by doctors to measure a patient's red blood cell count, white blood cell count and platelet count. The machine uses a small sample of the patient's blood, which is then placed into special tubes and analyzed. The results of the analysis are then displayed on a screen for the doctor to review. The CBC machine is an important tool for diagnosing various conditions, such as anemia, infection and leukemia. It can also help to monitor a patient's response to treatment.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
8. Simple MATLAB Program
>> x=5
x =
5
>> y=2
y =
2
>> ans = x * y
ans =
10
• Note:
• Creates the ans variable automatically
when you specify no output argument.
13. Long Vector, Matrix
>> x = 1:10
x =
1 2 3 4 5 6 7 8 9 10
>> x = 1:0.5:5
x =
1 1.5 2 2.5 3 3.5 4 4.5 5
>> [1:4; 5:8]
x =
1 2 3 4
5 6 7 8
• If you want to create a row
vector, containing numbers
from 1 to 10, you write
• If you want to specify an
increment value other than
one, for example
• Also you can create a matrix
using the colon.
14. Creating Vectors, Matrices from functions
>> x = zeros(2,3)
x =
0 0 0
0 0 0
>> x = ones(1,3)
x =
1 1 1
>> x = rand(1,3)
x =
0.8147 0.9058 0.1270
• zeros(m,n) m x n matrix of
zeros.
• ones(m,n) m x n matrix of
ones.
• rand(m,n) m x n matrix of
uniformly
distributed random number in
the interval (0,1).
17. Matrix Index
• Given
A =
1 2 3
4 5 6
7 8 9
>> A(-2), A(0)
Error: Subscript indices must either be real positive integers or logicals.
>> A(4,2)
Error: Index exceeds matrix dimensions.
18. Matrices Operations
• Given A and B: A =
1 2 3
4 5 6
7 8 9
B =
6 4 9
2 8 1
5 1 3
>> A + B
ans =
7 6 12
6 13 7
12 9 12
>> A - B
ans =
-5 -2 -6
2 -3 5
2 7 6
>> A * B
ans =
25 23 20
64 62 59
103 101 98
>> A’
ans =
1 4 7
2 5 8
3 6 9
• Subtraction• Addition • Product • Transpose
20. Matrix Functions
Function Definition
det Determinant
diag Diagonal matrices and diagonals of a
matrix
eig Eigenvalues and eigenvectors
inv Matrix inverse
norm Matrix and vector norms
rank Number of linearly independent rows
or columns
21. Matrix Functions
• Given: A =
1 2
3 4
>> det(A)
ans =
-2
>> diag(A)
ans =
1
4
>> inv(A)
ans =
-2 1
1.5 -0.5
>> norm(A)
ans =
5.4650
22. Concatenation of Matrices
>> x = [1 2]
x =
1 2
>> y = [3 4]
y =
3 4
>> A = [x y]
A =
1 2 3 4
>> B = [x; y]
B =
1 2
3 4
• Given:
• you can create a matrix or construct one from other matrices.
23. Mathematical Functions
Function Definition Function Definition
sqrt(x) Square root exp(x) Exponential
angle(x) Phase angle round(x) Round to nearest
integer
abs(x) Absolutevalue ceil(x) Round towards
plus infinity
rem(x) Reminder after
division
floor(x) Round towards
minus infinity
size(x) The dimensions
of a matrix
log(x) Natural logarithm
min(x) Minimum value length(x) The length of a
matrix
max(x) Maximum value sign(x) Signum function
24. Trigonometric Functions
Function Definition Function Definition
sin(x) Sine in radians sind(x) Sine in degrees
cos(x) Cosine in radians cosd(x) Cosine in degrees
tan(x) Tangent in
radians
tand(x) Tangent in
degrees
sec(x) Secant in radians secd(x) Secant in degrees
csc(x) Cosecant in
radians
cscd(x) Cosecant in
degrees
cot(x) Cotangent in
radians
cotd(x) Cotangent in
degrees
deg2rad(x) Convert angle
from degrees to
radians
rad2deg(x) Convert angle
from radians to
degrees
25. Trigonometric Functions (Inverse)
Function Definition Function Definition
asin(x) Inverse sine in
radians
asind(x) Inverse sine in
degrees
acos(x) Inverse cosinein
radians
acosd(x) Inverse cosinein
degrees
atan(x) Inverse tangent
in radians
atand(x) Inverse tangent
in degrees
asec(x) Inverse secantin
radians
asecd(x) Inverse secantin
degrees
acsc(x) Inverse cosecant
in radians
acscd(x) Inverse cosecant
in degrees
acot(x) Inverse
cotangent in
radians
acotd(x) Inverse
cotangent in
degrees
27. 2D Plotting In MATLAB
• Note:
• The semicolon(;) tells MATLAB not to
display any output from that command.
>> x = [0:0.1:2*pi];
>> y = sin(x);
>> plot(x, y)
Sine function in range 0 ≤ x ≤ 2π.
• We are going to plot the function sin(x) between 0 ≤ x ≤ 2π.
• First, we define the range of the independent variable, x to be between 0 and
2π. i.e. between 0 and 360.
• Then, we define the dependent variable,
y by writing the command y = sin(x).
• We plot using the function, plot(x,y).
28. Labels
• title()
• xlabel()
• ylabel()
>> title(‘Sine function in range 0 ≤ x ≤ 2π’)
>> xlabel(‘Angles x’)
>> ylabel(‘y = sin(x)’)