ECE 542 Neural Networks 
Introduction to neural networks and other basic machine learning methods including radial basis functions, kernel methods, support vector machines. The course introduces regularization theory and principle component analysis. The relationships to filtering, pattern recognition and estimation theory are emphasized. 3 credit hours. 

• Prerequisite  

ECE301 (Signals and Systems), ST371 or MA421 (Probability and Statistics), The course will use elementary matrix algebra, includes matrix/vector multiplication, matrix inverses, matrix description of the solution to linear equations, eigenvalues and eigenvectors. This material is covered in ECE220. The course will heavily utilize MATLAB for homework and examples in class. MATLAB is required for ECE220 and many other courses at NCSU. The course will use elementary probability theory: means, variance, covariance, expected values/moments of linear functions, stationarity. 

• Course Objectives  
Upon completion of the course, the student will be able to


• Course Requirements  
Homework will be submitted via Wolfware in pdf format. The student should have a scanner available to scan any handwritten solutions. 

• Textbook  
Neural Networks and Learning Machines, Simon Haykin, Pearson/PrenticeHall, 2008, ISBN 9780136032199 

• Computer and Internet Requirements  
NCSU and Engineering Online have recommended minimum specifications for computers. For details, click here. MATLAB is available for free at download.eos.ncsu.edu to students registered for at least one NCSU engineering class. (Unity ID required) Students must carefully follow instructions for installing MATLAB, and need to download Virtual CloneDrive only if they are using Windows. When trying to access MATLAB or other software from off campus you’ll need to use VPN. If you have problems with the download or installation process, contact the Help Desk located in Daniels Hall at eoshelp@ncsu.edu. Another option for accessing software such as MATLAB, SolidWorks and several other engineering applications is through the Virtual Computing Lab (VCL) at: http://vcl.ncsu.edu/. 

• Instructor  
Dr. Joel Trussell, Professor Electrical & Computer Engineering Engineering Building II (Eb2) 2058, Box 7911 Raleigh, NC 27695 
Phone: 9195155126 Fax: 9195155523 Email: hjt@ncsu.edu Website: http://www.ece.ncsu.edu/people/hjt 
