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B012523 - INFORMATION THEORY
Main information
Course Content
Suggested readings
Learning Objectives
Further information
Type of Assessment
Course program
Academic Year 2013-14
Coorte 2012 - Second Cycle Degree in COMPUTER SCIENCE
Course year
Second year - Second Semester
Belonging Department
Mathematics and Computer Science "Ulisse Dini" (DIMAI)
Course Type
Single education field course
Scientific Area
FIS/02 - THEORETICAL PHYSICS, MATHEMATICAL MODELS AND METHODS
Credits
6
Teaching Hours
48
Teaching Term
03/03/2014 ⇒ 13/06/2014
Attendance required
No
Type of Evaluation
Final Grade
Course Content
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Course program
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Lectureship
Course Content
Signal and transmission theory. Metric space, linear space, Hilbert’s space. Dirac delta function and its properties. Periodic function and Fourier series. Non periodic function, Fourier’s integral. Convolution. Impulse signal. Sampling theore. Discrete Fourier transform and FFT. Analogic and digital filters. Definition of information and its measure. Entropy. Axiomatic formulation of the Information Theory. Elements of encoding theory. JPEG compression.
Suggested readings (Search our library's catalogue)
Lecture Notes.
D. J. C. MacKay "Information Theory, Inference, and Learning Algorithms". Cambridge University Press 2003.
D. J. C. MacKay "Information Theory, Inference, and Learning Algorithms". Cambridge University Press 2003.
Learning Objectives
Educational Objectives:
BASIC CONCEPTS ON INFORMATION THEORY.
ACQUIRED COMPETENCES:
KNOWLEDGE OF BASIC CONCEPTS OF SIGNAL THEORY, SAMPLING PROBLEM OF DATA AND THEIR RECONSTRUCTION.
ACQUIRED SKILLS. (AT THE END OF THE COURSE):
Handling of Fourier transform and Dirac delta function. Use of the sampling theorem and its applications.
BASIC CONCEPTS ON INFORMATION THEORY.
ACQUIRED COMPETENCES:
KNOWLEDGE OF BASIC CONCEPTS OF SIGNAL THEORY, SAMPLING PROBLEM OF DATA AND THEIR RECONSTRUCTION.
ACQUIRED SKILLS. (AT THE END OF THE COURSE):
Handling of Fourier transform and Dirac delta function. Use of the sampling theorem and its applications.
Further information
Frequency of lectures, practice and lab: Recommended
Teaching Tools
UniFi E-Learning: http://e-l.unifi.it
Office Hours:
At the end of the lecture or by appointment (contact professor via e-mail).
Dipartimento di Fisica e Astronomia
Via Sansone, 1
50019 - Sesto Fiorentino (FI)
Tel: 055 4572000 - 2307622 - 2307722 Fax: 055 4572121
E-Mail: gregorio.landi@unifi.it, landi@fi.infn.it
Teaching Tools
UniFi E-Learning: http://e-l.unifi.it
Office Hours:
At the end of the lecture or by appointment (contact professor via e-mail).
Dipartimento di Fisica e Astronomia
Via Sansone, 1
50019 - Sesto Fiorentino (FI)
Tel: 055 4572000 - 2307622 - 2307722 Fax: 055 4572121
E-Mail: gregorio.landi@unifi.it, landi@fi.infn.it
Type of Assessment
Oral
Course program
Signal and transmission theory. Signal energy. Metric space, linear space, Hilbert’s space. Dirac delta function and its properties. Periodic function and Fourier series. Non periodic function, Fourier’s integral. Convolution. Impulse signal. Sampling theorem. Discrete Fourier transform and FFT. Analogic and digital filters. Notes on complex variable integral. DSP digital filters, AD and DA. IIR filters and their stability. Definition of information and its measure. Entropy. Axiomatic formulation of the Information Theory. Elements of encoding theory. Fundamental theorem of sound and no-sound encoding. Continuous canal. Relative entropy. Gaussian noise. Continuous canal capability. JPEG and MPEG compression.