• Honam Mathematical Journal
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• v.33 no.4
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• pp.487-493
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• 2011

The Fisher information matrix plays a significant role in statistical inference in connection with estimation and properties of variance of estimators. In this paper, we define the parameter space of the t-manifold using its Fisher's matrix and characterize the t-manifold from the viewpoint of information geometry. The ${\alpha}$-scalar curvatures to the t-manifold are calculated.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.39-43
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• 1999

We consider generalized exponential regression model with randomly censored data and propose a modified Fisher scoring method which estimates the model parameters. For this, the likelihood equations are derived and then the estimating algorithm is developed. We illustrate the proposed method using a real data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.3
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• pp.522-538
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• 2013

Content based image retrieval has become an increasingly important research topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The retrieval systems rely on a key component, the predefined or learned similarity measures over images. We note that, the similarity measures can be potential improved if the data distribution information is exploited using a more sophisticated way. In this paper, we propose a similarity measure learning approach for image retrieval. The similarity measure, so called Fisher kernel, is derived from the probabilistic distribution of images and is the function over observed data, hidden variable and model parameters, where the hidden variables encode high level information which are powerful in discrimination and are failed to be exploited in previous methods. We further propose a discriminative learning method for the similarity measure, i.e., encouraging the learned similarity to take a large value for a pair of images with the same label and to take a small value for a pair of images with distinct labels. The learned similarity measure, fully exploiting the data distribution, is well adapted to dataset and would improve the retrieval system. We evaluate the proposed method on Corel-1000, Corel5k, Caltech101 and MIRFlickr 25,000 databases. The results show the competitive performance of the proposed method.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.295-302
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• 2013

Many reported methods assume that the people in an image or an image sequence have been identified and localization. People detection is one of very important variable to affect for the system's performance as the basis technology about the detection of other objects and interacting with people and computers, motion recognition. In this paper, we present an efficient linear discriminant for multi-view people detection. Our approaches are based on linear discriminant. We define training data with fisher Linear discriminant to efficient learning method. People detection is considerably difficult because it will be influenced by poses of people and changes in illumination. This idea can solve the multi-view scale and people detection problem quickly and efficiently, which fits for detecting people automatically. In this paper, we extract people using fisher linear discriminant that is hierarchical models invariant pose and background. We estimation the pose in detected people. The purpose of this paper is to classify people and non-people using fisher linear discriminant.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.19-26
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• 2008

Gene set enrichment analysis (GSEA) is a computational method to identify statistically significant gene sets showing significant differences between two groups of microarray expression profiles and simultaneously uncover their biological meanings in an elegant way by employing gene annotation databases, such as Cytogenetic Band, KEGG pathways, gene ontology, and etc. For the gone set enrichment analysis, all the genes in a given dataset are first ordered by the signal-to-noise ratio between the groups and then further analyses are proceeded. Despite of its impressive results in several previous studies, however, gene ranking by the signal-to-noise ratio makes it difficult to consider highly up-regulated genes and highly down-regulated genes at the same time as the candidates of significant genes, which possibly reflect certain situations incurred in metabolic and signaling pathways. To deal with this problem, in this article, we investigate the gene set enrichment analysis method with Fisher criterion for gene ranking and also evaluate its effects in Leukemia related pathway analyses.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.487-494
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• 2015

A calculation of the Kullback-Leibler information of consecutive order statistics is complicated because it depends on a multi-dimensional integral. Park (2014) discussed a representation of the Kullback-Leibler information of the first r order statistics in terms of the hazard function and simplified the r-fold integral to a single integral. In this paper, we first express the Kullback-Leibler information in terms of the reversed hazard function. Then we establish a generalized result of Park (2014) to an arbitrary consecutive order statistics. We derive a single integral form of the Kullback-Leibler information of an arbitrary block of order statistics; in addition, its relation to the Fisher information of order statistics is discussed with numerical examples provided.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.6
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• pp.35-46
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• 2011

In this paper, we proposed the method of emotion recognition using staged classification model and Fisher's linear discriminant. By organizing the staged classification model, the proposed method improves the classification rate on the Fisher's feature space with high complexity. The staged classification model is achieved by the successive combining of binary classification model which has simple structure and high performance. On each stage, it forms Fisher's linear discriminant according to the two groups which contain each emotion class, and generates the binary classification model by using Adaboost method on the Fisher's space. Whole learning process is repeatedly performed until all the separations of emotion classes are finished. In experimental results, the proposed method provides about 72% classification rate on 8 classes of emotion and about 93% classification rate on specific 3 classes of emotion.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.393-399
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• 1993

When we compute the maximum likelihood estimators of the parameters for the logistic regression models, which are useful in studying the relationship between the binary response variable and the explanatory variable, the standard error calculations are usually based on the second derivative of log-likelihood function. On the other hand, an estimator of the Fisher information motivated from the fact that the expectation of the cross-product of the first derivative of the log-likelihood function gives the Fisher information is expected to have similar asymptotic properties. These estimators of Fisher information are closely related with the iterative algorithm to get the maximum likelihood estimator. The average numbers of iterations to achieve the maximum likelihood estimator are compared to find out which method is more efficient, and the estimators of the variance from each method are compared as estimators of the asymptotic variance.

• Journal of Astronomy and Space Sciences
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• v.22 no.2
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• pp.89-112
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• 2005

We determine the rotation velocities of 108 spiral and irregular galaxies (XV-Sample) from first-order rotation curves from position-velocity maps, based on short 21-cm observations with the Westerbork Synthesis Radio Telescope (WSRT). To test the usual random motion corrections, we compare the global HI linewidths and the rotation velocities, obtained from kinematical fits to two-dimensional velocity fields for a sample of 28 galaxies (RC-Sample), and find that the most frequently used correction formulae (Tully & Fouque 1985) are not very satisfactory. The rotation velocity parameter (the random-motion corrected HI linewidth: W?), derived with these corrections, may be statistically equal to two times the true rotation velocity, but in individual cases the differences can be large. We analyse, for both RC- and XV-Samples, the dependence of the slope of, and scatter in the Tully-Fisher relation on the definition of the rotation velocity parameters- For the RC-Sample, we find that the scatter in the Tully-Fisher relation can be reduced considerably when the rotation velocities derived from rotation curves are used instead of the random-motion corrected global H I linewidths. No such reduction in the scatter is seen for XV-Sample. We conclude that the reduction of the scatter in the Tully-Fisher relation seems to be related to the use of two-dimensional velocity information: accurate rotation velocity and kinematical inclination.

• Journal of Fisheries and Marine Sciences Education
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• v.25 no.3
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• pp.580-586
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• 2013

For telecommunication system construction to minimize the casualty of fisher, we investigated the usability of TRS communication system and performance of GPS automatic position transmitter (APT) which can be utilized for the survival, search and rescue of the victims. The trial experiments were conducted at sea with TRS and CDMA in the East, West and South Sea of Korea from October to December. As a result, the usability of the TRS as an emergency communication system device was verified since it provided stable position and voice information to the boundary of 50km far from the coast. Therefore the system is expected to contribute to minimization of victims.