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Abstract Advantages and limitations of the existing models for practical forecasting of
stock market volatility have been identified. Support vector machine (SVM) have been proposed
as a complimentary volatility model that is capable to extract i
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PLSon of random spanning tree algorithm, matlab development toolbox support vector machine. PLS toolbox, Rapid expansion of random spanning tree algorithm, matlab development toolbox support vector machine.
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To achieve the recognition of 10 digital sound, matlab development toolbox support vector machine, Least-squares regression analysis algorithm.
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Very suitable for the study using computer vision, matlab development toolbox support vector machine, cordic matlab simulation algorithm.
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Foreign model is finished, Of spherical harmonics graphic simulation, matlab development toolbox support vector machine.
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Genetic algorithm based reactive power optimization, Including single sideband, double sideband, suppressed carrier and quadruple, matlab development toolbox support vector machine.
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matlab development toolbox support vector machine, Automatic identification in the matlab environment the size of the connected area, Includes the modulation, demodulation, signal to noise ratio calculation.
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Application of small area variance comparison, simple procedures, matlab development toolbox support vector machine, allan FOG output error variance analysis.
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Using MATLAB compressed sensing, You can get a very accurate amplitude, frequency, phase estimation, matlab development toolbox support vector machine.
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