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GTM neurolike structures provide solutions of such tasks as: pattern recognition, prediction tasks, classification, Principal Components Analysis, factor analysis, optimization, lost data renewal or its (data) compression, realization of information security methods, solution of algebraic equations systems (including underdetermined and overdetermined), high dimensional data visualization, etc.
To overcome the drawback of overly dependence on the input parameters in intelligence single particle optimization (ISPO), an improved algorithm, called simplified intelligence single particle optimization (SISPO), is proposed in this paper. While maintaining similar performance as ISPO, no special parameter settings are required by SISPO. The proposed SISPO was successfully applied to train neural...
Chaotic neural network has been proved to be a powerful tool to solve combinational optimization problems. A novel transiently chaotic neuron was presented by transferring sigmoid activation function into non-monotonous activation function composed of trigonometric function and sigmoid. The reversed bifurcation and the maximum Lyapunov exponent of the chaotic neuron were given and the dynamic system...
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