Summer Term 2009 / 2010
Room A40: Wednesday 9:00-12:20
Assesment: 2 / 0 / 2   z, Zk
Prof. Aleš Procházka, CSc

Week Lectures Laboratories   Texts   M-files    Projects   
1 Basic MATLAB commands, matrix and vector opperations, data structures, graphics, file management, SIMULINK MATLAB
2 Matrix description of neural networks, transfer functions, classification of neural networks, selected applications
Basic computational algorithms, error surface, selected commands: HARDLIM, TANSIG, LOGSIG, PURELIN, ERRSURF
3 Fundamental model of a neuron (PERCEPTRON), network training, princple of classification
Perceptron learning process, selected commands: RANDS, INITP, LEARNP, TRAINP, PLOTPC, PLOTPV
4 Linear neural network (ADALINE), model of a neuron and network architecture, the learning proces
Adaptive linear network, selected commands: INITLIN, LEARNWH, TRAINWH, SOLVELIN, SIM, ADAPTWH
5 Project NN1: Adaptive rejection of signal components ProjectNN1
6 Multi-layer neural network, model of a neuron and network architecture, Levenberg-Marquardtova method, time-series prediction
Basic algorithms of the learning process, optimization of network coefficients, selected commands: INITFF, SIM, LEARNBP, TRANBP
7 Project NN2: Analysis and prediction of real-time series ProjectNN2
8 CASE STUDY: Adaptive Signal Processing and Adaptive Neural Networks (B. Widraw)
9 Functions of radial type, network model, selection of network structure
Network optimization, selected commands: RADBAS, SOLVERB
10 Associative learning methods, Hebb method, Kohonen method
Network traing, selected commands: LEARNH, LEARNK
11 Self-organizing networks, inicialization and training, self-organizing maps
Self-organizing maps, selected commands: NBDIST, NBGRID, COMPET
12 Project NN3: Classification of EEG signal segments ProjectNN3
13 Modelling of neural networks in the SIMULINK environment
Basic SIMULINK blocks for neural networks modelling, noise reduction
14 Conclusion

DATA FILES Data of gas consumption, biomedical signals (ECG, EEG), environmental data of air pollution, river flow data DATA

INFORMATIONS ABOUT EXAM Dates: http://student.vscht.cz Conditions: Examination system, sample test