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Prediction on complex time series has received much attention during the last decades. Global model is the main tool for time series predicting during the last decades, but it suffers low prediction efficiency, low prediction accuracy and high computation complexity for model training and updating. In recent years, local model for time series prediction draws widely attention for its more accuracy...
Based on local audio feature and support vector regression (SVR), an adaptive blind audio watermarking algorithm in wavelet domain is proposed in this paper. The audio signal is partitioned into audio frames, and the watermark is embedded in wavelet domain. For each audio frame, the energy and the maximal peaks of its all sub-bands are extracted as the local features, and SVR is used to model the...
A new least squares support vector regression model based on scaling reproducing kernel for black-box system identification is presented in this paper. The scaling reproducing kernel, which is a reproducing kernel in reproducing kernel Hilbert space (RKHS), is generated from the set of scaling basis function of some subspace of L 2(R). The support vector regression model incorporated the advantage...
A novel support vector kernel, namely the multiresolution kernel, is presented based on the theory of multiresolution analysis of wavelet transform. The multi-resolution kernel is composed by the scaling function at some scale and wavelets with different resolution. Based on multi-resolution kernel and support vector machine, a new regression model that is called multi-resolution support vector regression...
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