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Time series that composed of disperse observation like climatic time series have nonlinear and nonstationary features. Because of the superiority of Support Vector Machine in solving nonlinear problem and the advantage of Empirical Mode Decomposition in handling nonstationary signal, this paper combined the two methods in the research on chaotic time series prediction, and applied it to the seasonal...
In this paper, we propose a modification to Belief Propagation (BP) decoding algorithm for LDPC codes. The modification is to attenuate the check to bit extrinsic logarithm likelihood ratio by a factor α, when sudden sign change happens. This modification can be applied to both the standard BP algorithm and the joint row and column (JRC) BP algorithm. Simulation results show that the BER and WER performance...
Climate is a nonlinear system, and the BP neural network algorithm or the Support Vector Machine (SVM) algorithm which is superior in dealing with nonlinear problems is usually used in the climate forecast. Meanwhile, the climatic time series also include nonstationary feature, so this paper introduces a new method of signal processing-the Empirical Mode Decomposition (EMD) algorithm for making climatic...
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