Introduction to MATLAB: A Beginner's Guide to Programming

Introduction to MATLAB: A Beginner's Guide to Programming

GitHub:

https://github.com/Sivatech24/MatLab-Works.git

GitHubPage

SinWave:

x = 0:pi/100:2*pi;

y = cos(x);

plot(x, y)

ylabel('Cosine functions') % Corrected single quotes

legend('cos(x)') % Corrected single quotes

title('example M-file') % Corrected single quotes

axis([0 2*pi -3 3])

Plot:

x = 0:0.1:2*pi;

y = sin(x);

plot(x, y, '--rs', 'LineWidth', 2, ...

    'MarkerEdgeColor', 'k', ...

    'MarkerFaceColor', 'b', ...

    'MarkerSize', 5)

Stem:

x = 0:0.1:2*pi;

y = sin(x);

stem(x,y)

SubPlot:

% Example usage of subplot function

x = 0:0.1:2*pi;

y1 = sin(x);

y2 = cos(x);

subplot(2,1,1); % Create a subplot grid of 2 rows and 1 column, and select the first subplot

plot(x, y1);

title('Sine Function');

subplot(2,1,2); % Select the second subplot

plot(x, y2);

title('Cosine Function');

SubPlot1:

x = 0:0.1:2*pi;

y = sin(x);

subplot(2, 1, 1);

plot(x, y);

title('Plot of sin(x)');

subplot(2, 1, 2);

stem(x, y);

title('Stem plot of sin(x)');

Hold:

x = 0:0.1:2*pi;

y = sin(x);

z = cos(x);

t = 0.01*tan(x);

plot(x, y, '--', x, z, '-', x, t, ':')

xlabel('0 to 2\pi') % Used backslash for pi

ylabel('Multiple Plot') % Adjusted the label

legend('sin(x)', 'cos(x)', '0.01*tan(x)') % Adjusted legend labels

title('My Plots')

3D code for logo:

Sample:

L = 40 * membrane(1, 25);

logoFig = figure('Color', [0 0 0]);

logoax = axes('Parent', logoFig);

s = surface(L, 'Parent', logoax);

1

L = 160*membrane(1,100);

2

f = figure;

ax = axes;

s = surface(L);

s.EdgeColor = 'none';

view(3)

3

ax.XLim = [1 201];

ax.YLim = [1 201];

ax.ZLim = [-53.4 160];

4

ax.CameraPosition = [-145.5 -229.7 283.6];

ax.CameraTarget = [77.4 60.2 63.9];

ax.CameraUpVector = [0 0 1];

ax.CameraViewAngle = 36.7;

5

ax.Position = [0 0 1 1];

ax.DataAspectRatio = [1 1 .9];

6

l1 = light;

l1.Position = [160 400 80];

l1.Style = 'local';

l1.Color = [0 0.8 0.8];

 

l2 = light;

l2.Position = [.5 -1 .4];

l2.Color = [0.8 0.8 0];

7

s.FaceColor = [0.9 0.2 0.2];

8

s.FaceLighting = 'gouraud';

s.AmbientStrength = 0.3;

s.DiffuseStrength = 0.6; 

s.BackFaceLighting = 'lit';

s.SpecularStrength = 1;

s.SpecularColorReflectance = 1;

s.SpecularExponent = 7;

9

axis off

f.Color = 'black';

3 dimension:

normalized:

[X, Y] = meshgrid(-10:0.25:10, -10:0.25:10);

f = sinc(sqrt((X/pi).^2 + (Y/pi).^2));

mesh(X, Y, f);

axis([-10 10 -10 10 -0.3 1])

xlabel('{\bf x}') % corrected single quotes

ylabel('{\bf y}') % corrected single quotes

zlabel('{\bf sinc} ({\bf R})') % corrected single quotes

hidden off

Unnormalized:

[X, Y] = meshgrid(-10:0.25:10, -10:0.25:10);

f = sinc(sqrt((X/pi).^2 + (Y/pi).^2));

surf(X, Y, f);

axis([-10 10 -10 10 -0.3 1]);

xlabel('{\bf x}'); % corrected single quotes

ylabel('{\bf y}'); % corrected single quotes

zlabel('{\bf sinc} ({\bf R})'); % corrected single quotes

Autocorrection using Matlab:

N = 1024;

f = 1;

fs = 200;

n = 0:N-1;

x = sin(2*pi*f*n/fs);

t = (0:N-1)/fs; % corrected the calculation of time vector

subplot(2,1,1);

plot(t,x);

title('Sinewave of frequency 1000 Hz'); % corrected the frequency in the title

xlabel('Time [s]');

ylabel('Amplitude');

grid on; % corrected the grid command

Rxx = xcorr(x); % corrected function name to xcorr

subplot(2,1,2);

plot(-N+1:N-1, Rxx); % corrected the x-axis values for the autocorrelation

title('Autocorrelation of Sinewave');

xlabel('Lags');

ylabel('Autocorrelation');

grid on; % corrected the grid command

Batman:

xr = linspace(-7,7,1500);

yr = linspace(4.5,-4.5,1500);

x = repmat( xr , [ numel(yr) 1 ] );

y = repmat( yr' , [ 1 numel(xr) ] );

batman = (((x/7).^2.*sqrt(abs(abs(x)-3)./(abs(x)-3))+((y/3).^2) .*  ...

           sqrt(abs(y+(3*sqrt(33)/7))./(y+(3*sqrt(33)/7))))-1) .* ...

         (abs(x/2)-((3*sqrt(33)-7)/112).*(x.^2)-3+sqrt(1-(abs(abs(x)-2)-1).^2) - y) .* ...

         (9*sqrt(abs((abs(x)-1).*(abs(x)-0.75))./((1-abs(x)) .* (abs(x)-0.75)))-8*abs(x)-y) .* ...

         (3*abs(x)+0.75*sqrt(abs((abs(x)-0.75).*(abs(x)-0.5))./((0.75-abs(x)).*(abs(x)-0.5)))-y) .* ...

         (2.25*sqrt(abs((x-0.5).*(x+0.5))./((0.5-x).*(0.5+x)))-y) .* ...

         (((6*sqrt(10))/7)+(1.5-0.5*abs(x)) .* sqrt(abs(abs(x)-1)./(abs(x)-1))-((6*sqrt(10))/14).*sqrt(4-(abs(x)-1).^2)-y);

imagesc( log(abs(batman)) );

Commands:

SPY

PENNY

Progress bar:

clc;

clear all;

tic;

disp ('Hello, World!'); % Changed the string literal delimiter

h = waitbar(0,'Please wait...'); % Changed the string literal delimiter

n = 0;

for i = 1:100

    waitbar(i/100, h); % Fixed waitbar syntax

    for j = 1:100

        for k = 0:100

            n = factorial(2); % Calculating factorial(2) repeatedly, which doesn't depend on loop variables

        end

    end

end

close(h);

toc

Description:

Are you eager to dive into the world of MATLAB programming but unsure where to start? Look no further! Our comprehensive tutorial is designed specifically for beginners, providing a step-by-step guide to mastering MATLAB. MATLAB, short for MATrix LABoratory, is a powerful software tool widely used in various fields, including engineering, mathematics, physics, and finance. With its intuitive interface and extensive library of functions, MATLAB is ideal for data analysis, visualization, and algorithm development. In this tutorial, we'll walk you through the fundamentals of MATLAB programming, starting with the basics of the MATLAB environment. You'll learn how to navigate the MATLAB interface, create scripts and functions, and execute commands efficiently. Next, we'll explore MATLAB syntax, covering essential programming concepts such as variables, data types, operators, and control flow structures. Whether you're new to programming or transitioning from another language, this tutorial will help you grasp MATLAB's syntax quickly and effectively. As we delve deeper, we'll demonstrate how to manipulate arrays and matrices in MATLAB, leveraging its powerful vectorized operations for efficient computation. You'll discover how to perform common mathematical and statistical calculations, generate plots and visualizations, and customize your MATLAB environment to suit your preferences. Moreover, we'll introduce you to MATLAB's extensive library of built-in functions and toolboxes, empowering you to tackle a wide range of tasks with ease. From signal processing and image analysis to machine learning and optimization, MATLAB offers a wealth of tools for solving complex problems in diverse domains. Throughout the tutorial, we'll provide practical examples and exercises to reinforce your understanding of MATLAB concepts and techniques. Whether you're a student, researcher, or professional, this tutorial will equip you with the skills and knowledge needed to harness the full potential of MATLAB in your work and studies. By the end of this tutorial, you'll have a solid foundation in MATLAB programming and the confidence to tackle real-world projects with confidence. So why wait? Join us on this exciting journey and unlock the endless possibilities of MATLAB today! Don't forget to subscribe to our channel for more tutorials, tips, and tricks to enhance your MATLAB skills. Happy coding! Tags:

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