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Effective robotic grasping and manipulation requires knowledge about the surface properties of an object and the environment in which it is located. Physical contact with materials using tactile sensors can enable the retrieval of detailed information about the material, i.e. compressibility, surface texture and thermal properties. This paper describes a system used to classify a wide range of materials...
Independent Component Analysis (ICA) is a statistical method used for separating nongaussian independent components of a mixture signal. In this study, by separating the signal into its possible independent components, the simplification and comprehension of analysis of EEG signals was aimed. Through such an analysis it was thought that early diagnosis of some neurological disease such as epilepsy,...
The problem of detecting clusters in high-dimensional data is increasingly common in machine learning applications, for instance in computer vision and bioinformatics. Recently, a number of approaches in the field of subspace clustering have been proposed which search for clusters in subspaces of unknown dimensions. Learning the number of clusters, the dimension of each subspace, and the correct assignments...
In order to improve the identification and distribution performance of the detector, this paper proposes Principal Component Weighted Real-valued Negative Selection Algorithm(PCW-RNS) which is based on principal component weighting. The similarity between this algorithm and the classical real-valued detector generating algorithm based on generation-and-elimination lies in the fact that neither adopt...
Texture synthesis is a core process of computer graphics applications, which can enhance the realistic rendering greatly. With the rapidly increasing demands of realistic rendering, single texture synthesis cannot meet the needs. Multi-exemplars synthesis is a challenging research topic to increase the richness of texture details. In this paper, we use exemplar graph to realize Multi-exemplars texture...
This article is about the method on how to extract character recognition of vehicle brand by the combinition of EMD and nonlineary PCA. The main idea is to identify the image of the object which contains character recognition technology in BP neural network that momentum factor has been added in advance. After that compared with the improved neural network performance in different parameter occasions,...
In the industrial energy monitoring domain, several platforms are offered to acquire real-time power data and monitor energy consumption at tool, component, machine and system levels. The motivations of employing such platforms are majorly cost-effective purposes or environmental issues. This paper proposes and applies a power-based approach with non-intrusive sensing technique to evaluating machine...
The method of kernel data analysis is now a standard tool in modern data mining. An implicit mapping into a high-dimensional feature space is assumed in this method, in other words, an explicit form of the mapping is unknown but their inner product should be known instead. Contrary to this common assumption, we propose a method of explicit mappings. The reason why we use explicit mappings is as follows...
Firstly the function of principal component analysis (PCA)and back propagation(BP) neural network are analyzed in this paper, the fusion method of PCA and BP neural network is proposed for face representation and recognition. Experiments are done on ORL face databases and compare the average recognition rate and training time. Experimental results show that the method achieves the higher recognition...
The high temperature damage index series of 25 stations were calculated from 1960 to 2007, and these series were consisted of a matrix. After doing EOF to the matrix, two meaningful eigenvector fields were got, and therefore two main patterns about the spatial distribution of the high temperature damage to Rice in Jiangsu were found: the whole distribution pattern and the south-north distribution...
With the help of principal component analysis, by constructing the index system of regional cultural competition, the regional cultural competition in Henan Province is analyzed. The results show that the model of regional culture competition can fully reflect the cultural competition of urban area, which reflects the input level and consumption level on culture. It is conducive to fully reflect and...
This paper uses Principal Component Analysis to analyze the financial performance of high-tech listed companies in 2009. The result reveals that the financial performance of high-tech listed companies is not very well; relatively the profit ability is better and the growth ability is worse; the growth ability can improve the financial performance very clearly, but the operation ability not very well,...
Regional economy is a comprehensive economic concept which is forming from the economic development internal factors and external interaction of a certain area. It is restricted by the region's natural conditions, resources development and utilization, socio-economic conditions and various factors such as economic policy. If we want to improve the living standards and development level of a certain...
In this paper we present methods of selecting the optimum number of principal component analysis (PCA). The optimal number of PCs can be selected via the most valuable singular value or PRESS method and the performance of fault detection can be improved. These methods are applied to data of a power plant drum-type boiler. The m-file results demonstrate its good performance.
Based on the principle of spectral responses of remote sensing, using multi-phases TM data and measured points as basic data, the main methods are correlation analysis on spectral data, regression analysis and fitting inversion in the study area of Zhabuye salt lake that lies in Tibet autonomous region. This paper had achieved distributions of the salt content in the lake, meanwhile, generated their...
There are large differences in economic growth and employment because of the different advantage in different regions, different times and different stages of economic development, so the region should develop services according to their own situation, determine the internal service for the order of priority development sectors. Through the quantitative analysis of service industry for Heilongjiang...
In this paper we present a new subspace clustering algorithm TGSCA for large dataset with noise. Experiments show that TGSCA can discover clusters both on entire space and subspace; the computation complexity is proximate linear with object's number, space dimension, and clusters' dimension respectively; it is not sensitive to noise; it can find both disjoint clusters or overlap clusters; it can find...
Non-wood forest is a kind of important forest resource. This paper focused on the information extraction of non-wood forest based on Advanced Land Observation Satellite (ALOS) data. Band characteristics were analyzed to get understanding of this data wholly by information content, correlation coefficient and Optimum Index Factor (OIF). A new set of data with eight bands were obtained by the fusion...
Under the guidance of scientific development concept, Henan's economy and society has entered a new stage of development. Take the example of economic statistics of 2004-2008, in this paper, the economic and social indexes system is designed using principal component analysis. And based on the comprehensive evaluation on the economic statistics, this paper puts forward some policy suggestions on economic...
Principal component analysis (PCA) is often used for general feature generation and linear orthogonalization or compression by dimensionality reduction of correlated multivariate data, see Jolliffe for a comprehensive description of PCA and related techniques. Schölkopf et al. introduce kernel PCA. Shawe-Taylor and Cristianini is an excellent reference for kernel methods in general. Bishop and Press...
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