The method of conjugate gradients provides a very effective way to optimize large, deterministic systems by gradient descent. In its standard form, however, it is not amenable to ...
We propose a general-purpose stochastic optimization algorithm, the so-called annealing stochastic approximation Monte Carlo (ASAMC) algorithm, for neural network training. ASAMC c...
In this paper, evolution strategy is applied in order to improve the time series prediction accuracy of a Sugeno and Takagi type fuzzy inference system FIS. The presented approach...
Laparoscopic surgical training is a challenging task due to the complexity of instrument control and demand on manual dexterity and hand-eye coordination. Currently, training and ...
Rachel C. King, Louis Atallah, Ara Darzi, Guang-Zh...
Most computational engineering based loosely on biology uses continuous variables to represent neural activity. Yet most neurons communicate with action potentials. The engineerin...