Course details

Neural Networks, Adaptive and Optimum Filtering

QB4 Acad. year 2014/2015 Summer semester

Current academic year

In its first part, the course is devoted to providing an overview of types of architecture of neural networks and to a detailed analysis of their properties. Applications of neural networks in signal and image processing and recognition are included in this treatment. In the second part, the course deals with the theory of optimum detection and restoration of signals in its classical and generalised forms, emphasising the common base of this whole area. The subject highlights the common view-points in the area of neural networks and in the area of optimised signal processing.

Guarantor

Jan Jiří, prof. Ing., CSc. (UBMI)

Language of instruction

Czech, English

Completion

Examination

Department

Department of Biomedical Engineering (UBMI)

Subject specific learning outcomes and competences

Theoretical knowledge of areas of neural networks and optimum signal processing, ability to apply and, if necessary, to modify these methods for concrete problems.

Learning objectives

Gaining knowledge of theory of neural networks and theory of adaptive and optimum filtering, showing common view-points of both areas

Prerequisite knowledge and skills

signal and system theory, digital signal processing (e.g. the subjects BCZA, MMZS)

Study literature

  • J.Jan: Digital Signal Filtering, Analysis and Restoration. IEE Publishing, London, UK, 2000
  • B. Kosko (ed.): Neural Networks for signal processing. Prentice Hall 1992
  • Jan, J,: Číslicová filtrace, analýza a restaurace signálů. 2. rozš. vydání. VUTIUM Brno 2003

Fundamental literature

  • B. Kosko: Neural Networks and fuzzy systems. Prentice Hall 1992
  • B. Kosko (ed.): Neural Networks for signal processing. Prentice Hall 1992
  • S. Haykin: Neural Networks. Prentice Hall 1994
  • J.G.Proakis, et al.: Advanced digital signal processing. McMillan Publ. 1992
  • J.Jan: Digital Signal Filtering, Analysis and Restoration. IEE Publishing, London, UK, 2000
  • P.M.Clarkson: Optimal and Adaptive Signal Processing. CRC Press, 1993
  • S. Haykin: Adaptive Filter Theory. Prentice-Hall Int. 1991
  • V.K.Madisetti, D.B.Williams (eds.): The Digital Signal Processing Handbook. CRC Press & IEEE Press, 1998

Syllabus of seminars

Progress assessment

Study evaluation is based on marks obtained for specified items. Minimimum number of marks to pass is 50.

Controlled instruction

There are no checked study.

Back to top