TY - GEN
T1 - Dynamic grid self-organizing map for clustering of visual evoked potential single trials
AU - Stavrinou, Maria
AU - Papadimitriou, Stergios
AU - Bezerianos, Anastasios
AU - Papathanasopottlos, P.
PY - 2002/1/1
Y1 - 2002/1/1
N2 - The paper develops a novel learning model of clustering for Evoked Potential Single Trials, called Dynamic Grid Self- Organized Map (DG-SOM) designed according to the peculiarities of evoked potential data. The DG-SOM determines adaptively the number of clusters with a dynamic extension process which is able to exploit class information whenever exists. Specifically, it accepts available class information to control a dynamical extension process with an entropy criterion. In the case that there is no classification available, a similar dynamical extension is controlled with criteria based on the computation of local variances or resource counts. The results indicate that dynamic expansion can reveal (to a large extent) The many possible routes each of which leads from the input to the final "compulation". We employ these techniques in order to discriminate patterns from evoked potentials single trial data between alcoholic and non-alcoholic patients. From the classes provided, characteristic patterns for each class are extracted which can be valuable in studying the underlying brain dynamics.
AB - The paper develops a novel learning model of clustering for Evoked Potential Single Trials, called Dynamic Grid Self- Organized Map (DG-SOM) designed according to the peculiarities of evoked potential data. The DG-SOM determines adaptively the number of clusters with a dynamic extension process which is able to exploit class information whenever exists. Specifically, it accepts available class information to control a dynamical extension process with an entropy criterion. In the case that there is no classification available, a similar dynamical extension is controlled with criteria based on the computation of local variances or resource counts. The results indicate that dynamic expansion can reveal (to a large extent) The many possible routes each of which leads from the input to the final "compulation". We employ these techniques in order to discriminate patterns from evoked potentials single trial data between alcoholic and non-alcoholic patients. From the classes provided, characteristic patterns for each class are extracted which can be valuable in studying the underlying brain dynamics.
UR - http://www.scopus.com/inward/record.url?scp=84948682243&partnerID=8YFLogxK
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U2 - 10.1109/ICDSP.2002.1028290
DO - 10.1109/ICDSP.2002.1028290
M3 - Conference contribution
AN - SCOPUS:84948682243
T3 - International Conference on Digital Signal Processing, DSP
SP - 1125
EP - 1128
BT - 2002 14th International Conference on Digital Signal Processing Proceedings, DSP 2002
A2 - Skodras, A.N.
A2 - Constantinides, A.G.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Conference on Digital Signal Processing, DSP 2002
Y2 - 1 July 2002 through 3 July 2002
ER -