Course
Materials
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Lecture
set
1 |
Introduction
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part
1 part 2
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Tutorial
1
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answer
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Tutorial
2
The jupyter nb html
is extra only for
those interested. It
is NOT as complete
as, and not a
substitute for as
the Mathematica nb.
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answer
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Tutorial
2.5
see the html
jupyter nb for
the sound exercise
(section 3)
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answer
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Tutorial
3 (if the html is too
slow to load, visit
each sub-page)
page
1 page
2 page 3
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answer
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Student-individual-interest
project example: dipole
array far-field
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Student-individual-interest
project example:
classification
(discussed in class)
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Lecture
set 2 |
Intro
to computer capability
and limitation -
precision and accuracy
concept
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Lecture
set 3 |
Binary
number representation
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Tutorial
4 |
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Lecture
set 4
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Polynomials,
Zeros, and Roots
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Supplementary
note: polynomials
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Lecture
set 8
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Fourier
and Application in
Linear Time Invariant
System
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Lecture
segment 1: concept of
spectrum
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Lecture
segment 2: review
Fourier transform and
Fourier analysis
concept-Part 1
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html
version of .nb for
file error check
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pdf
version for .nb file
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Lecture
segment 2: review
Fourier transform and
Fourier analysis
concept-Part 2 |
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html
version of .nb for
file error check |
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Lecture
segment 2: review
Fourier transform and
Fourier analysis
concept-Part 3
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html
version of .nb for
file error check
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pdf
version for .nb file
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Lecture
segment 3: discrete
Fourier transform
(FFT)-Part 1
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Lecture
segment 3: discrete
Fourier transform
(FFT)-Part 2
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Fourier
analysis and
techniques (cont.)
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Supplementary
note:
Fourier tutorial
series - segment 1
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Supplementary
note:
Fourier tutorial
series - segment 2
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Supplementary
note:
Fourier tutorial
series - segment 3:
the programming
nitty-gritty
practicals of doing
numerical Fourier
transform and
applications to HW.
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Additional
Fourier demos
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Laplace
transform
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Lecture
set 9
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Part A:
Numerical Fitting/
Regression
note: ppt/pdf file
is only a summary,
main lecture is in
the Mathematica file
->
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check html version for
potential .nb download
error
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Use
this app (Sect. 3)
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fortune100
Advertising
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Auto
Credit
Bodystat |
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mixed
Tutorial Data Analysis
and lecture
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Part A
- continued.
Introduction to Data
Clusters and
Classification.
Lecture and demo only
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Lecture
set 9
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Part B:
Interpolation/approximation,
Spline (smoothing)
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Lecture
set 10
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Stochastic
Phenomena,
Probability, Monte
Carlo Methods
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Intro
to Monte Carlo concept
(segment 1) - Examples
on shot noise and
thermal noise
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Intro
to Monte Carlo concept
(segment 2) - Types of
stochastic process and
common distributions
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Intro
to probability and
Bayes' rule (segment
1)- Probability and
descriptive statistics
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DJIA |
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Intro
to probability and
Bayes' rule (segment
2)- Bayes' rule,
Bayesian decision, BBN
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Data
clusters and
classification
revisited.
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Intro
to stochastic calculus
and financial
applications
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Lecture
set 11
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Numerical
methods for
differential equations
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Diff
Eq. (segment 1) -basic
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Diff
Eq. (segment 2)
-system of equations |
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Diff
Eq. (segment 3)
-additional
illustrations,
examples
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Supplementary
materials
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A note
about programming and
Mathematica syntax
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Python-Mathematica
introductory "rosetta" |
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Sound
recording problem
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Style
Sheet
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ECE3340
Mathematica notebook
stylesheet. (See
explanation in class
how to install).
Download the file to
the right.
For Windows, first,
delete old stylesheet
of the same name
ECE3340 if exists,
then put the
downloaded file into
folder:
ProgramData\Mathematica\SytemFiles\FrontEnd\StyleSheets
For Mac OS:
~/Library/Mathematica/SytemFiles/FrontEnd/StyleSheets
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