Multilayer feedforward networks are universal approximators
Neural Networks
Time-invariant orthonormal wavelet representations
IEEE Transactions on Signal Processing
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The aim of this paper is to find a model to forecast 1-month ahead monthly anchovy catches using un-decimated multi-scale stationary wavelet transform (USWT) combined with linear autoregressive (AR) method. The original monthly anchovy catches are decomposed into various sub-series employing USWT and then appropriate sub-series are used as inputs to the multi-scale autoregressive (MAR) model. The MAR's parameters are estimated using the regularized least squares (RLS) method. RLS based forecasting performance was evaluated using determination coefficient and shown that a 99% of the explained variance was captured with a reduced parsimony and high accuracy.