1. MATLAB Introduction Main Features Simple programming rules
Extended accuracy
Continuity among integer, real and complex values
Comprehensive mathematical library
Extensive graphics tools
Linkages with other languages
Transportability across environment
MATLAB scripts will work on PC, UNIX, Mac 1

2. Typical uses include:
􀃎 Math and computation
􀃎 Algorithm development
􀃎 Modelling, simulation and prototyping
􀃎 Data analysis, exploration and visualization
􀃎 Scientific and engineering graphics
􀃎 Application development, including Graphical User Interface (GUI) building

3. The Advantages of MATLAB
Ease of Use.
Platform Independence
Predefined Function.
Device-Independent Plotting.
Graphical User Interface.
MATLAB Compiler.
a fraction of the time it would take to write a program in a scalar non-interactive language such as C, C++ or Fortran.
MATLAB is the tool of choice for high-productivity research, development and analysis

4. Disadvantage
it is an interpreted language and therefore can execute more slowly than compiled languages.
a full copy of MATLAB is five to ten times more expensive than a conventional C or Fortran compiler.

5. Starting MATLAB On UNIX : type matlab at command prompt
Click on the MATLAB icon if you are on a PC
Mac can probably do both…
Issues on startup
MATLAB needs a connection to the license server
Check internet connection
Too many users can use all available licenses 5

6. Starting MATLAB
Once MATLAB is running the GUI (Graphical User Interface) will appear
Default Window apperance 6

7. Starting MATLAB Command Window Main window in MATLAB
Commands entered here 7

9. Starting MATLAB
MATLAB displays >> prompt when ready for a command
Will have no >> prompt when processing commands
Newer versions also say “Ready” or “Busy” in lower left corner of GUI
Can use arrow keys to work through command history and modify commands
Essentially the same as UNIX command prompt 9

10. “MATrix LABoratory”
Powerful, extensible, highly integrated computation, programming, visualization, and simulation package
Widely used in engineering, mathematics, and science
Why?
Interactive code development proceeds incrementally; excellent development and rapid prototyping environment

11. Basic data element is the auto-indexed array
This allows quick solutions to problems that can be formulated in vector or matrix form
Powerful GUI tools
Large collection of toolboxes: collections of topic-related MATLAB functions that extend the core functionality significantly

12. Signal & Image Processing
MATLAB Toolboxes
Signal & Image Processing
Signal Processing
Image Processing
Communications 
Frequency Domain System Identification
Higher-Order Spectral Analysis
System Identification
Wavelet
Filter Design
Control Design 
Control System
Fuzzy Logic
Robust Control
μ-Analysis and Synthesis
Model Predictive Control
Math and Analysis
Optimization
Requirements Management Interface
Statistics
Neural Network
Symbolic/Extended Math
Partial Differential Equations
PLS Toolbox
Mapping
Spline
Data Acquisition and Import
Data Acquisition
Instrument Control
Excel Link
Portable Graph Object
Intro MATLAB 12

13. Toolboxes, Software, & Links
Intro MATLAB 13

14. MATLAB System
Language: arrays and matrices, control flow, I/O, data structures, user- defined functions and scripts
Working Environment: editing, variable management, importing and exporting data, debugging, profiling
Graphics system: 2D and 3D data visualization, animation and custom GUI development
Mathematical Functions: basic (sum, sin,…) to advanced (fft, inv, Bessel functions, …)
API: can use MATLAB with C, Fortran, and Java, in either direction

15. Desktop Tools (Matlab v6)
Command Window
type commands
Workspace
view program variables
clear to clear
double click on a variable to see it in the Array Editor
Command History
view past commands
save a whole session using diary
Launch Pad
access tools, demos and documentation

16. Data Types logical char CELL structure Java Classes Function handle
ARRAY
NUMERIC int,single,double

17. Variable Basics >> 16 + 24 ans = 40
>> product = 16 * 23.24
product =
371.84
>> product = 16 *555.24;
>> product
8883.8
no declarations needed
mixed data types
semi-colon suppresses output of the calculation’s result
Intro MATLAB 17

18. Variable Basics >> clear clear removes all variables;
>> product = 2 * 3^3;
>> comp_sum = (2 + 3i) + (2 - 3i);
>> show_i = i^2;
>> save three_things
>> load three_things
>> who
Your variables are:
comp_sum product show_i
>> product
product = 54
>> show_i
show_i = -1
clear removes all variables;
clear x y removes only x and y
complex numbers (i or j) require no special handling
save/load are used to
retain/restore workspace variables
use home to clear screen and put cursor at the top of the screen
Intro MATLAB 18

19. The basic data type used in MATLAB is the double precision array
MATLAB Data
The basic data type used in MATLAB is the double precision array
No declarations needed: MATLAB automatically allocates required memory
Resize arrays dynamically
To reuse a variable name, simply use it in the left hand side
of an assignment statement
MATLAB displays results in scientific notation
Use File/Preferences and/or format function to change default
short (5 digits), long (16 digits)
format short g; format compact (my preference)
Intro MATLAB 19

20. Matrices a vector x = [1 2 5 1] x = 1 2 5 1
a matrix x = [1 2 3; 5 1 4; ]
transpose y = x.’ y = 1 2 5

21. Matrices x(i,j) subscription whole row whole column y=x(2,3) y = 4
y=x(:,2) 2 1
x(i,j) subscription
whole row
whole column

22. Operators (arithmetic)
+ addition
Subtraction
Multiplication
/ division
^ power
‘ complex conjugate transpose
.* element-by-element mult
./ element-by-element div
.^ element-by-element power
.‘ transpose

23. Operators (relational, logical)
== equal
~= not equal
< less than
<= less than or equal
greater than
>= greater than or equal
& AND
| OR
~ NOT
pi …
j imaginary unit,
i same as j

24. Generating Vectors from functions
x = zeros(1,3)
x =
x = ones(1,3)
x = rand(1,3)
zeros(M,N) MxN matrix of zeros
ones(M,N) MxN matrix of ones
rand(M,N) MxN matrix of uniformly distributed random numbers on (0,1)

25. Graph Functions (summary)
plot linear plot
stem discrete plot
grid add grid lines
xlabel add X-axis label
ylabel add Y-axis label
title add graph title
subplot divide figure window
figure create new figure window
pause wait for user response

26. To create variables >>a=1 a = 1 >> b=4 b = 4
>> c=a+b
c = 5
>> d=cos(a)
d =

27. >>t=[ ]
t =
>>t=[ ];
>> t=1:5 %equally spaced arrays
>> t=1:0.5:4
t =

28. >>Whos %To know the variables typed so far
Name Size Bytes Class Attributes
a x double
b x double
c x double
d x double
t x double

29. One and two dimentional arrays
>>data=rand(2,2)
data =
>>size(data)
ans =
>>x=3+4i
x = i

30. >>a=[1 2 3;4 5 6;7 8 9] a = 1 2 3 >>b=a' b = 1 4 7
>>a(2,3)
ans =6
>>b=a'
b =
>>c=a*b
c =

31. >>c=a.*b
c =

32. >> data=rand(5,5)
data =
>> data(1:3,2:end)
ans =
>> data(1:2,:)=0
data =

33. >> a=1.5
a =1.5000
>> whos
Name Size Bytes Class Attributes
a x double
>>format long
>>1/7
ans =
>>format short
>> 1/7
ans =0.1429

34. >>x=3.2
x =3.2000
>>exp(x)
ans =
Boolean Expression
>> d(1)=true
d =1
>> d(2)=false
d =
>>a=1.5
a =
>> a<5
ans = 1

35. Matrix
>>a=[ ]
a =
>>a=[1 2;3 4]
a =
>>a=1:10
a =

36. >> a=1:10
a =
>> a=1:2:10
a =
>>10:-2:1
ans =

37. >>I = eye(3), x = [8; -4; 1], I*x I = 1 0 0 0 1 0 0 0 1
x = 8 -4 1
ans = 4

38. >> a=rand(4,4)
a =
>>a(1,2)
ans =0.6324

39. >> a(1,[1,2])
ans =
>> a(1,:)
ans =
>> a(1,2:end)
ans =
a =

40. >> a(1,2:end-1)=[10,10]
a =
>> a(1:2,:)=[]
a =

41. >>a(5) ans = 0.1576 >> a(:) ans = 0.1270 0.9134 0.2785
0.5469
0.1576
0.9706
0.8003
0.1419
a =

42. >> a<0.5
ans =
>> a(a<0.5)= -1
a =
>> ind=find(a<0.5)
ind = 1 3 5 8
a =

43. [r,c]=find(a<0.5)
r = 1 2
c = 3 4 a=

44. >> numel(a)
ans = 8
>> a=rand(2,2)
a =
>> b=[a,a]
b =

45. >> b=[a;a]
b =
>> a=1.5
a =1.5000
>> if a<5
disp('it is within the range')
end
it is within the range
b =

46. Character constant >> name='john' name = john
>>[name 'smith']
ans =Johnsmith
>>name(1:2)
ans = jo
>> k= % index with which to construct a sring
k = 1
>> str=['ring' num2str(k)]
str = ring1

47. Structure >> car.year=2010 ans = 2010 >> car.color=‘red’
ans =red
>> car.name=‘maruthi’
ans =maruthi

48. >>car=struct('year','2010','color','red','name','maruthi')
>>cars=[car;car]
cars =
2x1 struct array with fields:
year
color
name

49. >> cars(2).name='feat'
2x1 struct array with fields:
year
color
name
>>cars.name
ans = maruthi
ans = feat

50. >> cars(1).name,cars(2).name
ans = maruthi
ans = Feat
Cell Array
mycell={1 2 3;'test' [1;2] false}
mycell =
[1] [ 2] [3]
'test' [2x1 double] [0]

51. >> mycell={1, 2,'orange',true}
>>y=mycell(1,1)
y =
[1]
>> y=mycell(1,2)
[2]

52. >> y=mycell(1,3)
y = 'orange‘
>>y=mycell(1,4)
y = [1]
>>class(y)
ans = Cell

53. >>y=mycell{1,3}
y =orange
>>class(y)
ans = char

54. >> mycell{3:4}
ans = Orange
ans =1
>> newcell={mycell{3:4}}
newcell = 'orange' [1]

55. Flow Control if A > B 'greater' elseif A < B 'less' else 'equal'
end
for x = 1:10
r(x) = x;
if statement
switch statement
for loops
while loops
continue statement
break statement

56. >> x = pi*(-1:3), round(x) %Round to nearest integer
ans =
>> fix(x) %Round toward zero
>> floor(x) % rounds against negative infinity

57. >> ceil(x) % Round towards positive infinity
ans =
>> sign(x), if the corresponding element of X is greater than zero
0 if the corresponding element of X equals zero
-1 if the corresponding element of X is less than zero
ans =

58. Plotting the figure
>>t=0:0.05:0.5
>>y=sin(2*pi*t)
y =
>>plot(t,y)

59. Random Numbers
x=rand(100,1);
stem(x);
hist(x,100)

60. Line Styles & Colours Colours Line Styles y yellow . point
The default is to plot solid lines. A solid white line is
produced by
>> plot(x,y,'w-')
The third argument is a string whose rst character
species the colour(optional) and the second the line
style. The options for colours and styles are:
Colours Line Styles
y yellow point
m magenta o circle
c cyan x x-mark
r red plus
g green solid
b blue * star
w white : dotted
k black dashdot
-- dashed

61. plot(x,y,'*') x=1:5 x = 1 2 3 4 5 >> y=log(x) y =
>> y=log(x)
y =
>> plot(x,y)
plot(x,y,'*')

62. >>t=[12 23]
t =
>> y=[1,5]
y =
>> plot(t,y)
>> plot(t,y,'r-')

63. Loops >>x = -1:.05:1; >> for n = 1:2:8
subplot(4,2,n), plot(x,sin(n*pi*x))
subplot(4,2,n+1), plot(x,cos(n*pi*x))
end
draw sin(n*pi*x)and cos sin(n*pi*x)for n = 1; 3; 5; 7 alongside
each other.
We may use any legal variable name as the \loop counter"
(n in the above examples) and it can be made to run
through all of the values in a given vector (1:8 and
1:2:8 in the examples).
We may also use for loops of the type

64. Matlab Graphics
x = 0:pi/100:2*pi;
y = sin(x);
plot(x,y)
xlabel('x=0:2\pi')
ylabel('Sine of x')
title('Plot of the Sine Function')

65. Multiple Graphs t = 0:pi/100:2*pi; y1=sin(t); y2=sin(t+pi/2);
plot(t,y1,t,y2)
grid on

66. Multiple Plots t = 0:pi/100:2*pi; y1=sin(t); y2=sin(t+pi/2);
subplot(2,2,1)
plot(t,y1)
subplot(2,2,2)
plot(t,y2)

67. x=1:10;
y=1:10;
Z=x'*y;
surf(x,y,z);

68. >> [X,Y] = meshgrid(2:.2:4, 1:.2:3);
>> Z = (X-3).^2-(Y-2).^2;
>> mesh(X,Y,Z)
>> title('Saddle'), xlabel('x'),ylabel('y')

69. >>t=0:0.1:0.5
t =
>>y=sin(2*pi*t)
y =
>>w=y'*y;
>>surf(w)

70. Coin Tosses Simulate the outcomes of 100 fair coin tosses
x=rand(100,1);
p=sum(x<0.5)/100
p =
0.5400
Simulate the outcomes of 1000 fair coin tosses
x=rand(1000,1);
p=sum(x<0.5)/1000
0.5110

71. Coin Tosses
Simulate the outcomes of 1000 biased coin tosses with p[Head]=0.4
x=rand(1000,1);
p=sum(x<0.4)/1000
p =
0.4160