Articles dans des revues avec comité de lecture (115)
94.
Bersini, H., & Calenbuhr, V. V. (1997). Frustrated chaos in biological networks. Journal of theoretical biology, 188(2), 187-200. doi:10.1006/jtbi.1997.0468
95.
Bersini, H., & Bontempi, G. (1997). Now comes the time to defuzzify neuro-fuzzy models. Fuzzy sets and systems, 90(2), 161-169. doi:10.1016/S0165-0114(97)00082-1
96.
Renders, J.-M., Saerens, M., & Bersini, H. (1997). Fuzzy adaptive control of a certain class of SISO discrete-time processes. Fuzzy sets and systems, 85(1), 49-61.
97.
Bersini, H., & Gorrini, V. (1997). A simplification of the backpropagation-through-time algorithm for optimal neurocontrol. IEEE transactions on neural networks, 8(2), 437-441.
98.
Bradshaw, N., Duchateau, A., & Bersini, H. (1997). Global least-squares vs. EM training for the gaussian mixture of experts. Lecture notes in computer science, 1327, 295-300.
99.
Chatenet, N., & Bersini, H. (1997). Economical reinforcement learning for non stationary problems. Lecture notes in computer science, 1327, 284-288.
100.
Calenbuhr, V. V., Varela, F., & Bersini, H. (1996). Natural tolerance as a function of network connectivity. International journal of bifurcation and chaos in applied sciences and engineering, 6(9), 1691-1702. doi:10.1142/S0218127496001041
101.
Suykens, J., & Bersini, H. (1996). Neurocontrol: An overview. Journal of control A, 96(3), 4-10.
102.
Calenbuhr, V. V., Varela, F., & Bersini, H. (1996). Immune Idiotypic Network. International journal of bifurcation and chaos in applied sciences and engineering, 6(9), 1691-1702.
103.
Bersini, H., & Calenbuhr, V. V. (1995). Frustration induced chaos in a system of coupled ODE's. Chaos, solitons and fractals, 5(8), 1533-1549.
104.
Calenbuhr, V. V., Bersini, H., Stewart, J., & Varela, F. (1995). Natural tolerance in a simple immune network. Journal of theoretical biology, 177(3), 199-213. doi:10.1006/jtbi.1995.0239
105.
Bersini, H., Saerens, M., & Gonzalez Sotelino, L. L. (1994). Hopfield net generation, encoding and classification of temporal trajectories. IEEE transactions on neural networks, 5(6), 945-953. doi:10.1109/72.329692