Skip to content

Diagnostics and Decision Processes (DR)

Credits: 6 ( Lectures: 3, Practical lessons: 2)
Semester: ZS
Ending: zp; zk
Guarantor: Müller Luděk
Lecturer: Müller Luděk
Practical lesson lecturer: Müller Luděk, Chýlek Adam


Mathematical diagnostic methods: statistical decision problems, classification, feature selection, estimation, approximation. Artificial intelligence methods applicable to diagnostics - pattern recognition, introduction to neural networks and expert systems and their use in diagnostic and decision making processes. Engineering approach to the implementation of technical and medical diagnostic systems, feasibility studies, implementation of diagnostic systems in industry, life cycle of diagnostic systems with regard to their development and maintenance. Examples of technical and medical diagnostic systems.