Title:

Neural Networks, Adaptive and Optimum Filtering

Code:QB4
Ac.Year:2017/2018
Term:Summer
Curriculums:
ProgrammeBranchYearDuty
CSE-PHD-4DVI4-Elective
Language:Czech
Completion:examination (verbal)
Type of
instruction:
Hour/semLecturesSem. ExercisesLab. exercisesComp. exercisesOther
Hours:390000
 ExaminationTestsExercisesLaboratoriesOther
Points:1000000
Guarantee:Jan Jiří, prof. Ing., CSc., DBME
Lecturer:Jan Jiří, prof. Ing., CSc., DBME
Faculty:Faculty of Electrical Engineering and Communication BUT
Department:Department of Biomedical Engineering FEEC BUT
 
Learning objectives:
  Gaining knowledge of theory of neural networks and theory of adaptive and optimum filtering, showing common view-points of both areas
Description:
  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.
Knowledge and skills required for the course:
  signal and system theory, digital signal processing (e.g. the subjects BCZA, MMZS)
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.