Signals and Systems - Electrical Engineering

0.5 Soft Introduction to MATLAB 35

x1 =

Columns 1 through 10

1 1 1 1 1 1 1 1 1 1

Columns 11 through 15

0 0 0 0 0

A(2:5, 2:5) = zeros(4, 4) % zeros in rows 2−5, columns 2− 5

A =

1 1 1 1 1

1 0 0 0 0

1 0 0 0 0

1 0 0 0 0

1 0 0 0 0

y = rand(1,10) % row vector with 10 random values (uniformly

% distributed in [0,1]

y =

Columns 1 through 6

0.9501 0.2311 0.6068 0.4860 0.8913 0.7621

Columns 7 through 10

0.4565 0.0185 0.8214 0.4447

Notice that these values are between 0 and 1. When using the normal or Gaussian-distributed noise
the values can be positive or negative reals.

y1 = randn(1,10) % row vector with 10 random values

% (Gaussian distribution)

y1 =

Columns 1 through 6

−0.4326 −1.6656 0.1253 0.2877 −1.1465 1.1909

Columns 7 through 10

1.1892 −0.0376 0.3273 0.1746

Using Built-In Functions and Creating Your Own
MATLAB provides a large number of built-in functions. The following script uses some of them.

% using built-in functions

t = 0:0.01:1; % time vector from 0 to 1 with interval of 0.01

x = cos(2∗pi∗t/0.1); % cos processes each of the entries in

% vector t to get the corresponding value in vector x

% plotting the function x

figure(1) % numbers the figure

plot(t, x) % interpolated continuous plot

xlabel(’t (sec)’) % label of x-axis

ylabel(’x(t)’) % label of y-axis