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In this paper, we carry out a study on classification of musical instr uments using a small set of features selected from a broad range of extracted ones by sequential forward feature selection method. Firstly, we extract 58 features for each record in the music database of 351 sound files. Then, the sequential forward selection method is adopted to choose(More)
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A new inverse synthetic aperture radar (ISAR) imaging approach is presented for application in situations where the maneuverability of noncooperative target is not too severe and the Doppler variation of subechoes from scatterers can be approximated as a first-order polynomial. The proposed algorithm is referred to as the range centroid Doppler (RCD) ISAR(More)
A method which we call support vector machine with graded resolution (SVM-GR) is proposed in this paper. During the training of the SVM-GR, we first form data granules to train the SVM-GR and remove those data granules that are not support vectors. We then use the remaining training samples to train the SVM-GR. Compared with the traditional SVM, our SVM-GR(More)
In this paper, we attempt to answer the following question with systematic computer simulations: for the same validation error rate, does the size of a feedforward neural network matter? This is related to the so-called Occam's Razor, that is, with all things being equal, the simplest solution is likely to work the best. Our simulation results indicate that(More)