M. Cottrell, E. de Bodt, M. Verleysen, "Kohonen maps versus vector quantization for data analysis", in Proc. of ESANN'97, Bruges (Belgium) , D-Facto pub. (Brussels), pp. 187-193, 1997. Home/Search Document Details and Download
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M. Cottrell, E. de Bodt, M. Verleysen, "Kohonen maps versus vector quantization for data analysis", in Proc. of ESANN'97, Bruges (Belgium) , D-Facto pub. (Brussels), pp. 187-193, 1997.
Special Issue - Double Quantization Of Self-citation (Cottrell Verleysen) (Correct)
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Cottrell, M., de Bodt, E., & Verleysen, M. (1997). Kohonen maps versus vector quantization for data analysis. In: Proceedings of the European symposium on artificial neural networks, Bruges, Belgium (pp. 187-- 193). D-Facto pub.
Long-Term Time Series Forecasting Using Self-Organizing.. - Simon, Lendasse, al. (2003) Self-citation (Cottrell Verleysen) (Correct)
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Cottrell M., de Bodt E., Verleysen M., Kohonen maps versus vector quantization for data analysis, in Proc of ESANN, M. Verleysen Ed., D Facto, Brussels, 1997.
Using the Kohonen Algorithm for Quick Initialization.. - de Bodt, Cottrell.. (1999) (1 citation) Self-citation (De bodt Verleysen Cottrell) (Correct)
....Doyens, B 1348 Louvain la Neuve, Belgium and Universit Lille 2, ESA, Place Deliot, BP 381, F 59020 Lille, France 2 Universit Paris I, SAMaS MATISSE, 90 rue de Tolbiac, F 75634 Pads Cedex 13, France 3 Universitd Catholique de Louvain, DICE, 3 pl. du Levant, Abstract. In a previous paper ([1], ESANN 97) we compared the Kohonen algorithm (SAM) to Simple Competitive Learning Algorithm (SCL) when the goal is to reconstruct an unknown density. We showed that for that purpose, the SaM algorithm quickly provides an excellent approximation of the initial density, when the frequencies of ....
....followed by the classical SCL. We compare the value of the error measure after the same number of iterations for KSCL and SCL. For example, let us fix a total number of iterations T, the initial ordered points q(0) q2(0) qn(O) a constant and various probability functions (J(x) 2x on [0,1], 3x 2 on [0,1] e x on [0, oo [ Let us also consider the 2 neighbors SOM algorithm, v = 2. In Figures 4, 5, 6, we represent for the three probability densities that we took as examples, the variations of the error measure for different KSCL algorithms. We consider 4 cases where the 2 neighbors ....
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de Bodt E., Verleysen M., Cottrell M., Kohonen maps versus vector quantization for data analysis, ESANN'97, M.Verleysen Ed., D Facto, Bruxelles, 211-218, 1997.
Forecasting Time-Series by Kohonen Classification - Lendasse, Verleysen, de Bodt, .. (1998) (1 citation) Self-citation (Cottrell De bodt Verleysen) (Correct)
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Cottrell M., de Bodt E., Verleysen M., Kohonen maps versus vector quantization for data analysis, in Proc of ESANN, M. Verleysen ED., D Facto, Brussels, 1997.
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