Transcript Lecture3
Engineering Analysis – Fall 2009
Dan C. Marinescu
Office: HEC 439 B
Office hours: Tu-Th 11:00-12:00
Lecture 3
Last time
- Analytical and Numerical Methods for Model Solving
Today:
- Overview of Matlab
- Laplace Transform
- Solving differential equations using the Laplace Transform
- Example
Next Time
- Arrays in Matlab
- Graphics
- Number representation and roundoff errors
Lecture 2
2
Matlab
The workspace The environment (address space)
where all variables reside.
After carrying out a calculation, MATLAB assigns the
result to the built-in variable called ans;
A “%” character marks the beginning of a comment line.
Three windows:
Command window – used to enter commands and data
Edit window - used to create and edit M-files (programs) such as
the factor. For example, we can use the editor to create factor.m
Graphics window(s) - used to display plots and graphics
Lecture 2
3
Command window
Used to enter commands and data. The prompt is
“>>” ;
Allows the use of Matlab as a calculator when
commands are typed in line by line, e.g.,
>> a = 77 -1
ans = 61
>> b = a * 10
ans =610
Lecture 2
4
System commands
who/whos
clear
computer
version
list all variables in the workspace
removes all variables from the workspace
lists the system MATLAB is running on
lists the toolboxes (utilities) available
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Variables
Scalar and arrays; numerical data and text.
You do not need to pre-initialize a variable; if
it does not exist, MATLAB will create it for you.
Variable names
Variable names up to 31 alphanumeric characters (letters, numbers)
and the underscore (_) symbol; must start with a letter.
Reserved names for variables and constants.
ans
- Most recent answer.
eps
- Floating point relative accuracy.
realmax - Largest positive floating point number.
realmin - Smallest positive floating point number.
pi
- 3.1415926535897....
i
- Imaginary unit.
j
- Imaginary unit.
inf
- Infinity.
nan
- Not-a-Number.
isnan
- True for Not-a-Number.
isinf
- True for infinite elements.
isfinite
- True for finite elements.
why
- Succinct answer.
Lecture 2
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Variable names (cont’d)
To report the value of variable kiki type its name:
>> kiki
kiki =
13
To prevent the system from reporting the value of
variable kiki append the semi-solon (;) at the end of a
line:
>> kiki = 13;
Lecture 2
8
Data display
The format command allows you to display real numbers
short - scaled fixed-point format with 5 digits
long - scaled fixed-point format with 15 digits for double and 7
digits for single
short eng - engineering format with at least 5 digits and a
power that is a multiple of 3 (useful for SI prefixes)
The format does not affect the way data is stored
internally
Format Examples
>> format short; pi
ans =
3.1416
>> format long; pi
ans =
3.14159265358979
>> format short eng; pi
ans =
3.1416e+000
>> pi*10000
ans =
31.4159e+003
Note - the format remains the same unless another
format command is issued.
Script file - set of MATLAB commands
Example: the script factor.m:
function fact = factor(n)
x=1;
for i=1:n
x=x*i;
end
fact=x;
%fprintf('Factor %6.3f %6.3f \n' n, fact);
end
Scripts can be executed by:
(i) typing their name (without the .m) in the command window;
(ii) selecting the Debug, Run (or Save and Run) command in the editing
window; or
(iii) hitting the F5 key while in the editing window.
Option (i) will run the file as it exists on the drive, options (ii) and (iii)
save any edits to the file. Example:
>> factor(12)
ans =
479001600
Lecture 2
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Transform Methods
Basic idea: find a convenient representation of the
equations describing a physical phenomena.
For example, in signal analysis rather than analyzing a
function of time, s(t), study the spectrum of the signal
S(f), in other words carry out the analysis in the
frequency domain rather than the time domain.
Advantage of Fourier (spectral analysis):
More intuitive physical representation
Instead of correlation (an intensive numerically problem) use
multiplication.
Lecture 2
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Properties of the Laplace Transform
Linearity
Scaling
Frequency shifting
Time shifting
Frequency differentiation
Frequency integration
Differentiation
Integration
Convolution
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Lecture 2
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