Principles of pattern recognition and machine learning and electrical and computer engineering applications in signal estimation, detection and classification, detection of patterns in engineering systems and communications networks, assessment of normality and abnormality patterns in biomedical engineering applications and cyber security of power systems. Prerequisites: Grade of C or better in ECEN 314; grade of C or better in ECEN 303 or STAT 211; junior or senior classification Credits 3. 3 Lecture Hours.
Principles of pattern recognition and machine learning and electrical and computer engineering applications in signal estimation, detection and classification, detection of patterns in engineering systems and communications networks, assessment of normality and abnormality patterns in biomedical engineering applications and cyber security of power systems. Prerequisites: Grade of C or better in ECEN 314; grade of C or better in ECEN 303 or STAT 211; junior or senior classification Credits 3. 3 Lecture Hours.
