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Comparing aircraft agility using Mahalanobis distances
1994
Journal of Aircraft
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If there are four aircraft and a calculated distance between each pair, the results can be similarly shown on a tetrahedron, which makes an interesting and revealing visual display. ...
The purpose of this Note is to show that such notions of distance can be quantified by use of the Mahalanobis generalized distance measure. ...
doi:10.2514/3.46599
fatcat:ents36w7tbbmnehjarhossj3d4
Effect of a fuselage on delta wing vortex breakdown
1994
Journal of Aircraft
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If there are four aircraft and a calculated distance between each pair, the results can be similarly shown on a tetrahedron, which makes an interesting and revealing visual display. ...
References
‘Mahalanobis, P. C., “On the Generalized Distance in Statistics,”
Proceedings of the National Institute of Sciences of India, Vol. 12, 1936, pp. 49-55.
ENGINEERING NOTES
*Kramer, C. ...
doi:10.2514/3.46600
fatcat:jkn6st74hnhm5ev76buokw76di
iButton Enrolment and Verification Requirements for the Pressure Sequence Smartcard Biometric
[chapter]
2001
Lecture Notes in Computer Science
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In this paper we consider a number of on-card verification schemes, the best of which offers an equal error rate of 2.3%. ...
In previous work we proposed the pressure sequence biometric, within which a biometric sensor is integrated onto the card in a low-cost and mechanically compliant manner. ...
Equation (7) now offers a route to the direct computation of the Mahalanobis distance verifier. ...
doi:10.1007/3-540-45418-7_11
fatcat:mzytotc3n5g3fhbwdaje3cwtjq
An Integrated Approach to Emotion Recognition for Advanced Emotional Intelligence
[chapter]
2009
Lecture Notes in Computer Science
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A feature extraction procedure is used to discriminate between four affective states by means of a Mahalanobis distance classifier. The average classifications rate (74.11%) was encouraging. ...
However, most of the studies are mainly focused on facial expression classifications and speech recognition and not much attention has been paid until recently to physiological pattern recognition. ...
The Mahalanobis distance is a minimum-distance classifier since a small value indicates a higher potential membership of the vector x in the emotional group under consideration. ...
doi:10.1007/978-3-642-02580-8_62
fatcat:k5wbe65dozgefd5pntno6foy2a
Deep Divergence Learning
[article]
2020
arXiv
pre-print
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In this paper, we introduce deep Bregman divergences, which are based on learning and parameterizing functional Bregman divergences using neural networks, and which unify and extend these existing lines ...
We show in particular how deep metric learning formulations, kernel metric learning, Mahalanobis metric learning, and moment-matching functions for comparing distributions arise as special cases of these ...
Further experiments were performed on real datasets, the results of which are enumerated in Appendix C. ...
arXiv:2005.02612v1
fatcat:d4zwdlkw5ffnbjbx776jpikgou
Metric Embedding for Nearest Neighbor Classification
[article]
2007
arXiv
pre-print
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Usually the Euclidean distance metric is assumed or a Mahalanobis distance metric is optimized to improve the NN performance. ...
The embedding function is then determined by solving a semidefinite program which has an interesting connection to the soft-margin linear binary support vector machine classifier. ...
Mean (µ) and standard deviation (σ) of the leave-one-out (LOO) and test (generalization) errors are reported. ...
arXiv:0706.3499v1
fatcat:gxjnnuukanav3j2rmqgl6hyklu
Spectral Analysis of EEG in Familial Alzheimer's Disease with E280A Presenilin-1 Mutation Gene
2014
International Journal of Alzheimer's Disease
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In order to reveal significant differences in the spectral parameter, the Mahalanobis distance (D2) was calculated between groups. ...
any clinical symptoms of dementia, and a normal group of 18 healthy subjects. ...
Acknowledgments This project was funded partially by the Sustainability Agenda 2009-2010 of the Code and the University of Antioquia to the Group of Neuroscience of Antioquia. ...
doi:10.1155/2014/180741
pmid:24551475
pmcid:PMC3914466
fatcat:xwxp3ss455cl7lvy2x73xic5o4
Computing committors via Mahalanobis diffusion maps with enhanced sampling data
2022
Journal of Chemical Physics
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The resulting algorithm, which we call the target measure Mahalanobis diffusion map (tm-mmap), is suitable for a moderate number of collective variables in which one can approximate the diffusion tensor ...
Imposing appropriate boundary conditions allows use of the approximated BKO to solve for the committor function and utilization of transition path theory to find the reactive current delineating the transition ...
Bodhi Vani for valuable discussion on MD simulations of alanine dipeptide and Mr. Zachary Smith for advice on reweighting with WTMETAD. ...
doi:10.1063/5.0122990
pmid:36511548
fatcat:brtua74zsvcj3gaosqamylooxy
Determination of Plasmid pSN1216-29 Host Range and the Similarity in Oligonucleotide Composition Between Plasmid and Host Chromosomes
2020
Frontiers in Microbiology
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However, there are no complementary studies to assess the consistency between the predicted evolutionary host range and experimentally determined replication/transfer host range of a plasmid. ...
The results showed that oligonucleotide compositions of the plasmid pSN1216-29 had more similarities to those of hosts (transconjugants genera) than those of non-hosts (other genera). ...
This is a suitable feature for the prediction of a host range because accessory genes are usually located on other mobile genetic elements, including transposons and/or integrons, which might influence ...
doi:10.3389/fmicb.2020.01187
pmid:32582111
pmcid:PMC7296055
fatcat:4oeisaoirzh5dgyqqygie7q2xm
ICGE: an R package for detecting relevant clusters and atypical units in gene expression
2012
BMC Bioinformatics
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There are two key aspects to classification: the estimation of the number of clusters, and the decision as to whether a new unit (gene, tumor sample...) belongs to one of these previously identified clusters ...
Clustering algorithms are a useful approach with which to analyze genome expression data. They attempt to partition the genes into groups exhibiting similar patterns of variation in expression level. ...
The authors are very grateful to the anonymous reviewers whose helpful comments have greatly improved the clarity of this article. ...
doi:10.1186/1471-2105-13-30
pmid:22330431
pmcid:PMC3364157
fatcat:h426xv6nhvh55odvzcmrgutubu
Gamma band directional interactions between basal forebrain and visual cortex during wake and sleep states
2016
Journal of Physiology - Paris
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During SWS but not REM, there was also a robust directional gamma band influence of BF on VC. ...
While the impact of BF on cortical EEG or LFP signals has been extensively documented, surprisingly little is known about LFP activity within BF. ...
Acknowledgements This work was supported by Swiss National Science Foundation grant 143390, 141786, 168602, a EURYI award to GR and by the University of Fribourg. ...
doi:10.1016/j.jphysparis.2016.11.011
pmid:27913167
fatcat:gvwf6g34ufa37mxxz252obczha
Anomaly detection in Skin Model Shapes using machine learning classifiers
2019
The International Journal of Advanced Manufacturing Technology
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The concept of Skin Model Shapes has been proposed as a method to generate digital twins of manufactured parts and is a new paradigm in the design and manufacturing industry. ...
Moreover, the existing geometric variation inspection techniques do not detect unfamiliar changes within tolerance, which could be the precursors to the onset of the manufacturing of out of tolerance part ...
Open Access This article is distributed under the terms of the Creative Comm ons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution ...
doi:10.1007/s00170-019-03794-z
fatcat:x4u63hqxjbbp7gusom2mngr7ra
Dimensionality reduction of the enhanced feature set for the HMM-based speech recognizer
1992
Digital signal processing (Print)
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Some of these figures of merit are F-ratio (ratio of between-class and within-class variances), Mahalanobis distance, Bhattacharya distance, Matusita distance, Patrick-Fisher distance, divergence measure ...
In Section 5, these results are discussed. In Section 6, conclusions are reported. ...
Here, C stands for the cepstral coefficients, DC for the delta cepstral coefficients, and DDC for the delta-delta cepstral coefficients.
ACKNOWLEDGMENTS ...
doi:10.1016/1051-2004(92)90005-j
fatcat:ggblr3olnbh53lttxjsd2yrzym
Alignment-Free Genome Tree Inference by Learning Group-Specific Distance Metrics
2013
Genome Biology and Evolution
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Specifically, our method learns a Mahalanobis metric for a set of genomes and a reference taxonomy to guide the learning process. ...
Understanding the evolutionary relationships between organisms is vital for their in-depth study. Gene-based methods are often used to infer such relationships, which are not without drawbacks. ...
Acknowledgments The authors thank Lars Steinbrü ck (MPI Informatik, HHU) for critical reading of the manuscript and useful comments. ...
doi:10.1093/gbe/evt105
pmid:23843191
pmcid:PMC3762195
fatcat:5ow74suvefbxvgthiyzna3rpji
Computing committors via Mahalanobis diffusion maps with enhanced sampling data
[article]
2022
arXiv
pre-print
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Other Versions
The resulting algorithm, which we call the "target measure Mahalanobis diffusion map" (tm-mmap), is suitable for a moderate number of collective variables in which one can approximate the diffusion tensor ...
Imposing appropriate boundary conditions allows use of the approximated BKO to solve for the committor function and utilization of transition path theory to find the reactive current delineating the transition ...
Note that C depends on the distance function in the kernel and the volume of Ω that is assumed to be finite, but is independent of ε. ...
arXiv:2208.13772v2
fatcat:3l2nsnwfsvdelmicnn4ztazsla
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