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The pattern recognition in the sparse representation (SR) framework has been very successful. In this model, the test sample can be represented as a sparse linear combination of training samples by solving a norm-regularized least squares problem. However, the value of regularization parameter is always indiscriminating for the whole dictionary. To enhance the group concentration of the coefficients...
The performance conditions of steam turbine regenerative system have important influence on the safety and economy of the units. It is of great significance to doing the research on the performance monitoring of the regenerative system to ensure the safe and economical operation of the whole coal-fired power plants. In view of the shortcomings of the complexity of traditional performance monitoring...
To solve the problem of gradient descent (GD) method which has low accuracy and easily falling into local optimum, the radial basis function (RBF) based on immune algorithm system (IAS-RBF) is proposed. In this method, each antibody is a RBF neural network and the optimal affinity is calculated by immune algorithm system (IAS) to get the best antibody, then the optimal parameter of RBF neural network...
An important and widespread topic in cloud computing is text analyzing. People often use topic model which is a popular and effective technology to deal with related tasks. Among all the topic models, sLDA is acknowledged as a popular supervised topic model, which adds a response variable or category label with each document, so that the model can uncover the latent structure of a text dataset as...
In order to make the smart home system to have the ability of learning user behavior actively and provide services spontaneously, this paper introduced user behavior prediction model which combined back propagation neural network (BPNN) with Hadoop parallel computing to the traditional smart home system, numerous user-generated behavior and environmental parameters data are packaged in particular...
The continuously deepening of higher education reform and rapid development of information and communication technology (ICT) brings an urgent requirement for engineering education in China. Excellent Engineer Training Program (EETP) is an important engineering education plan to explore novel university-enterprise cooperation based cultivation method. This paper presents a comprehensive study on the...
The plight of ethnic medical technology, education, and industry in ethnic minorities was examined, and the combined “industry-education-research” experience of Jiangxi University of Traditional Chinese Medicine was analyzed. Facing key scientific issues and technological demands, the development of an innovative collaborative model for ethnic medical technology, education, and industry was examined,...
Image tagging plays a critical role in image indexing and retrieval and it has gained more and more attention along with the increasing availability of large quantities of web images. However, most of current tagging methods only utilize single feature type, while combining multiple types of features has been proved to be effective for image analysis. In this paper, we propose a multi-feature late...
Every user has a distinct background and a specific goal when searching for information on the Web. The goal of Web search personalization is to tailor search results to a particular user based on that user's interests and preferences. This paper presents an approach of search engine optimization based on algorithm of BP neural networks aiming at meeting the increasing requirements of modern people...
Object-based image retrieval has been an active research topic in recent years, in which user only pays his attention to some object in the images. As one promising approach, multiple-instance learning has attracted many researchers. Most of recently proposed methods either need additional restrictions for instance selection or lead to heavy computational load, so that they are often inconvenient...
It's still in search that how to apply SVM in muti-classify. Directed Acyclic Graph is easier to be computed and has better learning effect than other arithmetic. Experimental platform is used to simulate typical faults of circumrotate machines. Based on the frequency domain feature, energy eigenvector of frequency domain is presented using wavelet packet analysis method. DAGSVM is applied in classification,...
The key of advancing radial basis function neural network (RBFNN) is how to choose the data center and the number of cluster perfectly. In this paper fuzzy C-means clustering is used as K-means clustering ameliorated algorithm to determine the data center of RBF neural networks hidden nodes. Combined pseudo-inverse method RBF network model is constructed. Simulation test on the dimension predicting...
fMRI is one of the fundamental tools for functional human brain research. However, fMRI data are often in a high dimensional feature space and suffer greatly from large and complex dataset. To relieve the curse of dimensionality in fMRI image, PCA combines with SVM to form a feature-based classification method in this work. PCA is employed to find a more compact and reasonable representation of the...
In this paper, an analog current mode implementation of a neuron circuit capable of performing real Gaussian neighborhood taper learning is presented. The neuron cell is compacted with a reusable multiplier that can function as squarer and multiplier for Euclidean and topological distances calculation as well as for Gaussian function characteristics with adjustable learning rate. A four-neuron self-organizing...
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