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SUMMARY AND OUTLOOK
B Parameters oftheSunspot Models
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A. S. Weigend Architecture autoregressive model average relative variance B. A. Huberman back-propagation behavior bootstrap sample chaotic systems choice complexity cost complexity term computational ecosystem connectionist networks correlation coefficient cost function currency exchange rate D. E. Rumelhart data set David Rumelhart day DM dissertation distribution Doctor of Philosophy dynamical systems epochs error model evaluation example exchange rate prediction Gaussian given hidden units input dimension input lag input units internal validation interpreted Iterated predictions lag space learning rate linear autoregression Lyapunov exponent measure multi-step predictions Neil Gershenfeld network performance network solutions noise nonlinear systems number of input out-of-sample performance output unit overfitting prediction error prediction set prior probability projection pursuit random Santa Fe Institute series prediction sigmoid specific squared error statistics Stochastic Processes stopping point strong model sunspot data sunspot series threshold autoregressive model Tong and Lim training data training set values weak models weight-eliminated network weight-elimination weights and biases zero