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Sheet music has long been regarded as one of the most effective medias for musicians, music players, and amateurs to communicate with each other. It is also an intuitive way for non-professionals to learn how to play a musical instrument or sing a song. However, not all composers have willingness to share their own sheet music, especially those protected by strict copyright regulations. For amateurs...
In this letter, a novel deep-leaming-based feature selection method based on Poisson Gamma Belief Network (PGBN), is proposed to extract multi-layer feature from SAR images data. As a deep Bayesian generative network, PGBN has the ability to extract a multilayer structured representation from the complex SAR images owing to the existence of Poisson likelihood and multilayer gamma hidden variables,...
This paper investigates a new voice conversion technique using phone-aware Long Short-Term Memory Recurrent Neural Networks (LSTM-RNNs). Most existing voice conversion methods, including Joint Density Gaussian Mixture Models (JDGMMs), Deep Neural Networks (DNNs) and Bidirectional Long Short-Term Memory Recurrent Neural Networks (BLSTM-RNNs), only take acoustic information of speech as features to...
In this paper, we develop the max-margin similarity preserving factor analysis (MMSPFA) model. MMSPFA utilizes the latent variable support vector machine (LVSVM) as the classification criterion in the latent space to learn a discriminative subspace with max-margin constraint. It jointly learns factor analysis (FA) model, similarity preserving (SP) term and max-margin classifier in a united Bayesian...
The rate of wheel load reduction used for assessment the safety degree of wheels due to wheel load reduction caused by the heavy and suspended the derailment, Which is one of the important indexes about the Vehicle running safety assessment. The paper presents a forecasting method about the rate of wheel load reduction based on NARX neural network, Which use NARX neural network to realize accurate...
In this paper, simplified parameter-extraction process is presented for digital predistortion (DPD) design. The predistorter identification is based on the indirect learning architecture. In the proposed parameter-extraction procedure, the feedback data from PA output is normalized by its own peak value instead of expected gain of PA, and then this data is used for parameters extraction. The estimated...
Dataset shift from the training data in a source domain to the data in a target domain poses a great challenge for many statistical learning methods. Most algorithms can be viewed as exploiting only the first-order statistics, namely, the empirical mean discrepancy to evaluate the distribution gap. Intuitively, considering only the empirical mean may not be statistically efficient. In this paper,...
Water-jet cutting machine is one of the high-tech products setting of ultra-high pressure technology, numerical control technology, computer application technology as a whole, make use of the kinetic energy of abrasive water-jet cutting of various materials to achieve the purpose of cutting. It has advantages such as no chemical changes, no heat distortion, thin cutting gap, high accuracy, aspect...
In this study, we provide a direct comparison of the Stochastic Maximum Likelihood algorithm and Contrastive Divergence for training Restricted Boltzmann Machines using the MNIST data set. We demonstrate that Stochastic Maximum Likelihood is superior when using the Restricted Boltzmann Machine as a classifier, and that the algorithm can be greatly improved using the technique of iterate averaging...
How to use the POLSAR data to classify and interpret the conditions of the earth is a very important research field of POLSAR. In this paper, we propose an improved algorithm on the basis of studying and analyzing some common algorithms. This technique introduces the fisher criterion in the feature selection and the hierarchical method in the classification of POLSAR image, which can improve Lee's...
In order to analyze the innovation capability in the complex multiple-attribute environment, a novel approach, used to evaluate the innovation capability of home appliance manufacturers, is presented. Furthermore, based on the assumption of a relationship between specific resources managed by manufacturers and their innovation capability, the authors suggested a reasonable evaluation indicator system,...
This paper proposes a self-constructed Mercer kernel based subspace LDA approach for face recognition. Our self-constructed Mercer (SM) kernel function is constructed from a given block diagonal matrix. The entries of all its block diagonal sub-matrices are equal to 1. It shows that this kind of matrix is a symmetric, positive semi-definite matrix and thus can serve as a kernel matrix. Based on such...
Any formation change of swarms in the natural environment is one of basic problems of coordination. A new transformation scheme for a man-made swarm formation is proposed, in this paper, by using the algorithms of affine transformation with respect to generalized ant colony optimization (GACO). The affine transformation algorithm can pre-determine target positions for each member of the swarm, while...
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