Mạng thần kinh thường xuyên cho dự đoán P12

Mạng thần kinh thường xuyên cho dự đoán P12

Mạng thần kinh thường xuyên cho dự đoán P12

... type. 12.2 Introduction When using neural networks, many of their parameters are chosen empirically. Apart from the choice of topology, architecture and interconnection, the parameters that 208 ... between a network with arbitrarily chosen parameters β and η and the referent network, so as the outputs of the networks are identical for every time instant. An obvious choice for the referent net...

Ngày tải lên: 20/10/2013, 15:15

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Mạng thần kinh thường xuyên cho dự đoán P11

Mạng thần kinh thường xuyên cho dự đoán P11

... and Davis 1991). Penalised likelihood methods such as AIC or BIC (Box and Jenkins 1976) exist for choosing the order of the autoregressive model to be fitted to the data; or the point where the autocorrelation ... simulated, simulated deseasonalised and deseasonalised In the experiments the logistic function was chosen as the nonlinear activation func- tion of a dynamical neuron (Figure 2.6)....

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Tài liệu Mạng thần kinh thường xuyên cho dự đoán P1 docx

Tài liệu Mạng thần kinh thường xuyên cho dự đoán P1 docx

... statistical and optimisation theories 2 SOME IMPORTANT DATES IN THE HISTORY OF CONNECTIONISM (Cichocki and Unbehauen 1993; Zhang and Constantinides 1992), neural networks are becoming one of the ... rigorous analysis of the perceptron. The work of Grossberg in 1976 was based on biological and psychological evidence. He proposed several new architectures of nonlinear dynamical systems (Grossbe...

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Tài liệu Mạng thần kinh thường xuyên cho dự đoán P2 docx

Tài liệu Mạng thần kinh thường xuyên cho dự đoán P2 docx

... network or a penalty term for excessive increase in the weights of the adaptive system or some other chosen function (Tikhonov et al. 1998). An example of such an objective function for online learning is J(k)= 1 N N  i=1 (e 2 (k ... weights based upon the instantaneous error • Stop if some prescribed error performance is reached The choice of the type of learning is very much dependent upon...

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Tài liệu Mạng thần kinh thường xuyên cho dự đoán P3 pptx

Tài liệu Mạng thần kinh thường xuyên cho dự đoán P3 pptx

... and ˜y µ,j (0) = 0, for all j  0. The form of the equation is, moreover, a convex mixture. The choice of µ controls the trade-off between depth and resolution; small µ provides low-depth and high-resolution ... ,q. A taxonomy of recurrent neural networks architectures is presented by Tsoi and Back (1997). The choice of structure depends upon the dynamics of the signal, learning algorithm and...

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Tài liệu Mạng thần kinh thường xuyên cho dự đoán P4 docx

Tài liệu Mạng thần kinh thường xuyên cho dự đoán P4 docx

... tables, samples of a chosen sigmoid are put into a ROM or RAM to store the desired activation function. Alternatively, we use simplified activation functions that approximate the chosen activation ... sigmoidal functions are a typical choice for MLPs, several other functions have been considered. Recently, the use of polynomial activation functions has been proposed (Chon and Cohen 1997; Piazz...

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Tài liệu Mạng thần kinh thường xuyên cho dự đoán P5 doc

Tài liệu Mạng thần kinh thường xuyên cho dự đoán P5 doc

... are described by nonlinear difference equations, have been introduced (Billings 1980; Chon and Cohen 1997; Chon et al. 1999; Connor 1994). Unlike the Volterra–Wiener representation, the NARMAX ... therefore modelling is based upon a chosen set of known functions. In addition, if the model is to approximate the system with an arbitrary accuracy, the set of chosen nonlinear continuous functions...

Ngày tải lên: 26/01/2014, 13:20

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Tài liệu Mạng thần kinh thường xuyên cho dự đoán P6 pdf

Tài liệu Mạng thần kinh thường xuyên cho dự đoán P6 pdf

... developed for neural adaptive system identifiers and predictors. Finally, issues concerning the choice of a neural architecture with respect to the bias and variance of the prediction performance ... would provide a compromise between the bias and the variance of the prediction error achieved by a chosen model. An analogy with 112 LEARNING ALGORITHMS AND THE BIAS/VARIANCE DILEMMA Table 6.1 Ter...

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Tài liệu Mạng thần kinh thường xuyên cho dự đoán P7 ppt

Tài liệu Mạng thần kinh thường xuyên cho dự đoán P7 ppt

... three neurons and six external input signals and a logistic activation function. Solution. Let us choose the initial values X 0 = rand(10, 1)∗1, W = rand(10, 3)∗2−1, using the notation of MATLAB, ... theory. The study of probabilistic operator theory and its applications was initiated by the Prague school under the direction of Antonin Spacek, in the 1950s (Bharucha-Reid 1976). They recognise...

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Tài liệu Mạng thần kinh thường xuyên cho dự đoán P8 ppt

Tài liệu Mạng thần kinh thường xuyên cho dự đoán P8 ppt

... samples, as described in Mandic et al. (1998) and Bal- tersee and Chambers (1998). The network chosen for the analysis was with N =2 neurons and one external input signal to the network. Such ... Convergence curves for such a reiterated LMS algorithm for a data-reusing FIR filter applied to echo cancellation are shown in Fig- ure 8.1. The averaged squared prediction error becomes smaller ... p...

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