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Template-Based Gait Authentication Through bayesian Thresholding

IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 209-219页

作者： Ebenezer R.H.P.Isaac Susan Elias Srinivasan Rajagopalan K.S.Easwarakumar IEEE the Department of Computer Science and Engineering Indian Institute of Technology Madras the School of Electronics Engineering VIT University the Department of Physiology and Biomedical Engineering Mayo Clinic the Department of Computer Science and Engineering Anna University

While gait recognition is the mapping of a gait sequence to an identity known to the system, gait authentication refers to the problem of identifying whether a given gait sequence belongs to the claimed identity. A typical gait authentication system starts with a feature representation such as a gait template, then proceeds to extract its features, and a transformation is ultimately applied to obtain a discriminant feature set. Almost every authentication approach in literature favours the use of Euclidean distance as a threshold to mark the boundary between a legitimate subject and an impostor. This article proposes a method that uses the posterior probability of a bayes' classifier in place of the Euclidean distance. The proposed framework is applied to template-based gait feature representations and is evaluated using the standard CASIA-B gait database. Our study experimentally demonstrates that the bayesian posterior probability performs significantly better than the de facto Euclidean distance approach and the cosine distance which is established in research to be the current state of the art.

关键词： bayes’ rule biometrics gait recognition linear discriminant analysis verification

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Monty Hall Problem and the Principle of Equal Probability in Measurement Theory

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Applied Mathematics 2012年第7期3卷 788-794页

作者： Shiro Ishikawa Department of Mathematics Faculty of Science and Technology Keio University Yokohama Japan

In this paper, we study the principle of equal probability (i.e., unless we have sufficient reason to regard one possible case as more probable than another, we treat them as equally probable) in measurement theory (i.e., the theory of quantum mechanical world view), which is characterized as the linguistic turn of quantum mechanics with the Copenhagen interpretation. This turn from physics to language does not only realize theremarkable extensionof quantum mechanicsbut alsoestablish the method of science. Our study will be executed in the easy example of the Monty Hall problem. Although our argument is simple, we believe that it is worth pointing out the fact that the principle of equal probability can be, for the first time, clarified in measurement theory (based on the dualism) and not the conventional statistics (based on Kolmogorov’s probability theory).

关键词： Linguistic Interpretation Quantum and Classical Measurement Theory Philosophy of Statistics Fisher Maximum Likelihood Method bayes’ Theorem

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Analytical and Numerical Investigations of Probabilistic Monochromatic Problem

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Journal of Applied Mathematics and Physics 2019年第4期7卷 793-808页

作者： Stefan Schmuck Jakob Svensson Istituto di Fisica del Plasma CNR Milan Italy Max-Planck-Institut für Plasmaphysik Teilinstitut Greifswald Greifswald Germany

A probabilistic formalism, relying on bayes’ theorem and linear Gaussian inversion, is adapted, so that a monochromatic problem can be investigated. The formalism enables an objective test in probabilistic terms of the quantities and model concepts involved in the problem at hand. With this formalism, an amplitude (linear parameter), a frequency (non-linear parameter) and a hyperparameter of the Gaussian amplitude prior are inferred jointly given simulated data sets with Gaussian noise contributions. For the amplitude, an analytical normal posterior follows which is conditional on the frequency and the hyperparameter. The remaining posterior estimates the frequency with an uncertainty of MHz, while the convolution of a standard approach would achieve an uncertainty of some GHz. This improvement in the estimation is investigated analytically and numerically, revealing for instance the positive effect of a high signal-to-noise ratio and/or a large number of data points. As a fixed choice of the hyperparameter imposes certain results on the amplitude and frequency, this parameter is estimated and, thus, tested for plausibility as well. From abstract point of view, the model posterior is investigated as well.

关键词： bayes’ Theorem Linear Inversion Uncertainty Monochromatic Spectral Limitation

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Descriptively probabilistic relationship between mutated primary structure of von Hippel-Lindau protein and its clinical outcome

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Journal of Biomedical Science and Engineering 2009年第3期2卷 190-199页

作者： Shao-Min Yan Guang Wu Computational Mutation Project DreamSciTech Consulting 301 Building 12 Nanyou A-zone Jiannan Road Shenzhen Guangdong Province CN-518054 China National Engineering Research Center for Non-food Biorefinery Guangxi Academy of Sciences 98 Daling Road Nanning Guangxi Province CN-530007 China

In this study, we use the cross-impact analysis to build a descriptively probabilistic relationship between mutant von Hippel-Lindau protein and its clinical outcome after quantifying mutant von Hippel-Lindau proteins with the amino-acid distribution probability, then we use the bayes-ian equation to determine the probability that the von Hippel-Lindau disease occurs under a mutation, and finally we attempt to distinguish the classifications of clinical outcomes as well as the endocrine and nonendocrine neoplasia induced by mutations of von Hippel-Lindau protein. The results show that a patient has 9/10 chance of being von Hippel-Lindau disease when a new mutation occurs in von Hippel- Lindau protein, the possible distinguishing of classifications of clinical outcomes using mod-eling, and the explanation of the endocrine and nonendocrine neoplasia in modeling view.

关键词： Amino Acid bayes’ Law Cross-Impact Analysis Distribution Probability Mutation Von Hip-pel-Lindau Disease

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