Feature Vector Selection Method Using Mahalanobis Distance for Diagnostics of Analog Circuits Based on LS-SVM

2012 ◽  
Vol 28 (5) ◽  
pp. 745-755 ◽  
Author(s):  
Bing Long ◽  
Shulin Tian ◽  
Houjun Wang
Keyword(s):  
Analog Circuits ◽  
Mahalanobis Distance ◽  
Feature Vector ◽  
Selection Method

scholarly journals A Mahalanobis Distance Cumulant-Based Structural Damage Identification Method with IMFs and Fitting Residual of SHM Measurements

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Chuang Chen ◽  
Yinhui Wang ◽  
Tao Wang ◽  
Xiaoyan Yang
Keyword(s):  
Mahalanobis Distance ◽  
Structural Damage ◽  
Damage Identification ◽  
Feature Vector ◽  
Recursive Algorithm ◽  
Intrinsic Mode Functions ◽  
Data Set ◽  
Identification Method ◽  
Structural Damage Identification ◽  
Emd Method

Data-driven damage identification based on measurements of the structural health monitoring (SHM) system is a hot issue. In this study, based on the intrinsic mode functions (IMFs) decomposed by the empirical mode decomposition (EMD) method and the trend term fitting residual of measured data, a structural damage identification method based on Mahalanobis distance cumulant (MDC) was proposed. The damage feature vector is composed of the squared MDC values and is calculated by the segmentation data set. It makes the changes of monitoring points caused by damage accumulate as “amplification effect,” so as to obtain more damage information. The calculation method of the damage feature vector and the damage identification procedure were given. A mass-spring system with four mass points and four springs was used to simulate the damage cases. The results showed that the damage feature vector MDC can effectively identify the occurrence and location of the damage. The dynamic measurements of a prestress concrete continuous box-girder bridge were used for decomposing into IMFs and the trend term by the EMD method and the recursive algorithm autoregressive-moving average with the exogenous inputs (RARMX) method, which were used for fitting the trend term and to obtain the fitting residual. By using the first n-order IMFs and the fitting residual as the clusters for damage identification, the effectiveness of the method is also shown.

Oil Spills Identification in SAR Image Using Mahalanobis Distance

2012 ◽  
Vol 466-467 ◽  
pp. 246-250
Author(s):  
Peng Chen ◽  
Hui Zhou ◽  
Xiao Tian Wang
Keyword(s):  
High Resolution ◽  
Mahalanobis Distance ◽  
Oil Spills ◽  
Feature Vector ◽  
Weather Conditions ◽  
Target Object ◽  
The Other ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Accuracy Rate

This paper presents a method of oil spills identification in Synthetic Aperture Radar (SAR) image based on feature vector, it makes use of the advantages of SAR which can work on day and night and all weather conditions with high resolution monitoring for oil spills. Use the algorithm of Mahalanobis distance to identify the target object and gain the feature vector through evaluating SAR image of the dark area boundary. It is proved by experiment that the number of selected feature value is reasonable and more effective for estimating whether has oil spills than the traditional one. The accuracy rate can reach 96% or even more for using the algorithm of Mahalanobis distance and compare to the other methods of oil spills identification it is easy for programming implementation with less conditions .

scholarly journals Optimized Mahalanobis–Taguchi System for High-Dimensional Small Sample Data Classification

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xinping Xiao ◽  
Dian Fu ◽  
Yu Shi ◽  
Jianghui Wen
Keyword(s):  
Feature Selection ◽  
Mahalanobis Distance ◽  
Feature Selection Method ◽  
Selection Method ◽  
Small Sample ◽  
High Dimensional ◽  
Two Stage ◽  
Smoothing Techniques ◽  
Sample Data

The Mahalanobis–Taguchi system (MTS) is a multivariate data diagnosis and prediction technology, which is widely used to optimize large sample data or unbalanced data, but it is rarely used for high-dimensional small sample data. In this paper, the optimized MTS for the classification of high-dimensional small sample data is discussed from two aspects, namely, the inverse matrix instability of the covariance matrix and the instability of feature selection. Firstly, based on regularization and smoothing techniques, this paper proposes a modified Mahalanobis metric to calculate the Mahalanobis distance, which is aimed at reducing the influence of the inverse matrix instability under small sample conditions. Secondly, the minimum redundancy-maximum relevance (mRMR) algorithm is introduced into the MTS for the instability problem of feature selection. By using the mRMR algorithm and signal-to-noise ratio (SNR), a two-stage feature selection method is proposed: the mRMR algorithm is first used to remove noise and redundant variables; the orthogonal table and SNR are then used to screen the combination of variables that make great contribution to classification. Then, the feasibility and simplicity of the optimized MTS are shown in five datasets from the UCI database. The Mahalanobis distance based on regularization and smoothing techniques (RS-MD) is more robust than the traditional Mahalanobis distance. The two-stage feature selection method improves the effectiveness of feature selection for MTS. Finally, the optimized MTS is applied to email classification of the Spambase dataset. The results show that the optimized MTS outperforms the classical MTS and the other 3 machine learning algorithms.

НАРАТИВ ЯК КОНТЕНТНА ОСНОВА МІЖНАРОДНИХ СТРАТЕГІЧНИХ КОМУНІКАЦІЙ

2020 ◽  
pp. 4
Author(s):  
N. Zykun ◽  
A. Bessarab ◽  
L. Ponomarenko
Keyword(s):  
Selection Method ◽  
Historical Narrative ◽  
Neutral Position ◽  
Main Task ◽  
Grand Narrative ◽  
National Narrative ◽  
Strategic Communications ◽  
Analysis And Synthesis ◽  
The Media ◽  
International Interaction

<p><em>The article, basing on the analysis of selected media texts with reference to narrative from the leading Ukrainian newspapers «Dzerkalo Tyzhnia» (Weekly Mirror), «Den» (Day), «Ukraina Moloda» (Young Ukraine) for 2016–2020, the semantic and content characteristics of the «narrative», «strategic narrative», «small narratives» nominations has established; the directions of the semantic realization of the meaning of the narrative and its possibilities in the process of international strategic communications aimed at both external and internal audience, are outlined. It is proved that the main task of a strategic, or national, narrative is a reasoned explanation to the state population and interested audiences of specific realities, intentions, plans; justification of certain directions of state activity aimed at partners, at opponents and those occupying a neutral position.</em></p><p><em>There are divided the spheres of use of different narratological nominations: in international communications and in scientific discourse, the conceptual foundations of state identity and international interaction are referred to as strategic narrative or grand narrative, in publicistic discourse the narrative nomination is used, more rarely – historical narrative, national narrative.</em></p><p><em>The scientific novelty of the research is that the focus is on the media aspect of the use of one of the key concepts of strategic communications and the role of the media in its implementation.</em></p><p><em>The main general scientific methods used in this article are descriptive and comparative ones, as well as analysis and synthesis. The following empirical methods were also used: solid selection method (solid selection method for allocation texts with the «narrative» lexeme; quantitative method of content analysis with elements of qualitative one – for characterizing the semantic of the «narrative» term).</em></p><p><em>The results of the study can be used in the complex research of the technology of international strategic communications and in the practical activity of specialists in international strategic communications, a new trend in Ukraine, which is currently under active institutionalization.</em></p><strong><em>Key words:</em></strong><em> international strategic communications, propaganda, narrative, strategic narrative, grand narrative, «small narratives».</em>

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