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Control and Digital Signal Processing II(4040047)
The course is divided into four modules: Robotics, Image Processing, Pattern Recognition and
Neural Networks. The first and fourth modules are taught by Professor Juan Bernardo Gómez Mendoza;
I teach the second and third modules. This page is dedicated to the modules I teach. Since the second semester of 2007, I am in charge of the
module on Neural Networks instead of the lectures about Image Processing. See below also for the materials and homeworks about Neural Networks.
Course material and references:
- Module II: Image Processing.
- Chapters 23 to 25 of Smith's book (see below).
- Database of Faces.
- Fingerprint Database.
- M. Egmont-Petersen, D. de Ridder, H. Handels, "Image processing with neural networks - a review,"
Pattern Recognition, vol. 35, no. 10, pp. 2279-2301, 2002.
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- Module III: Pattern Recognition.
- Duda's book (see below).
- Michie's book (see below).
- Databases from the UCI Machine Learning Repository.
- A.K. Jain, R.P.W. Duin and J. Mao, "Statistical pattern recognition: a review,"
IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 1, pp. 4-37, 2000.
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- Module IV: Neural Networks.
- Chapter 26 of the Smith's book (see below).
- Chapter 6 of the Duda's book (see below).
Recommended compilers and IDEs:
Programming assignments can only be done in C/C++, Fortran77, Pascal, or BASIC.
Matlab can only be used for display purposes.
See the Software section for available compilers and manuals.
Routines from Smith's book are written in BASIC. If you use them with Just BASIC,
be sure to use parenthesis instead of square brackets for arrays. In addition, be sure to eliminate the
percent sign at the end of variables.
Homework assignments (In spanish only!):
- Homework 01 [pdf].
- Homework 02 [pdf].
- Homework 03 [pdf].
- Homework 04 [pdf].
- Homework 05 [pdf].
- Homework 06 [pdf].
- Homework 07 [pdf].
Recommended books:
- S. W. Smith, The Scientist and Engineer's Guide to Digital Signal Processing, 2nd ed.
San Diego, CA: California Technical Publishing, 1999.
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- R. O. Duda, P. E. Hart and D. G. Stork, Pattern Classification, 2nd ed. New York: Wiley-Interscience, 2001.
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- D. Michie, D.J. Spiegelhalter and C.C. Taylor (eds), Machine Learning, Neural and Statistical Classification.
UK: University of Leeds, 1994.
[ps.gz][pdf][zip][ps.gz (chapters)][zip (chapters)]
- Richard Lowry, Concepts and Applications of Inferential Statistics, Poughkeepsie, NY, USA: Vassar College, 1999.
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