Statistical Analysis and Processing of Experimental Data
Description: The course studies various methods for processing biomedical signals and data, including data representation techniques and statistical methods for analyzing experimental data. It examines the classification of multidimensional observations and pattern recognition tasks, providing a detailed overview of different recognition methods and their applications in automatic analysis of biomedical signals. Additionally, the course covers different classes of biomedical signals and their processing methods at various stages: preprocessing, digital filtering, pattern recognition, and syntactic classification of biosignals.
Amount of credits: 6
Course Workload:
Types of classes | hours |
---|---|
Lectures | 30 |
Practical works | 30 |
Laboratory works | |
SAWTG (Student Autonomous Work under Teacher Guidance) | 30 |
SAW (Student autonomous work) | 90 |
Form of final control | Exam |
Final assessment method |
Component: University component
Cycle: Profiling disciplines