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A Generalized Fisher Discriminant Analysis with Adaptive Entropic Regularization for Cross-Model Vibration State Monitoring in Wind Tunnels. [PDF]
Sensors (Basel)Li Z, Li Z, Chen X, Lin H.
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Texture Analysis of Kidney MRI Using Diffusion-Weighted Imaging and Intravoxel Incoherent Motion for Classifying the Severity of Chronic Kidney Diseases. [PDF]
CureusShimizu H +7 more
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Correlation synthetic discriminant functions
Applied Optics, 1986Advanced filters are described for distortion-invariant space-invariant object identification and location in clutter using correlators. These correlation synthetic discriminant functions (SDFs) are extensions of earlier projection SDFs. They provide control of the sidelobe levels and the shape of the output correlation function as well as its peak ...
D P, Casasent, W T, Chang
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Discriminative Learning Quadratic Discriminant Function for Handwriting Recognition
IEEE Transactions on Neural Networks, 2004In character string recognition integrating segmentation and classification, high classification accuracy and resistance to noncharacters are desired to the underlying classifier. In a previous evaluation study, the modified quadratic discriminant function (MQDF) proposed by Kimura et al. was shown to be superior in noncharacter resistance but inferior
Cheng-Lin, Liu +2 more
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Journal of the London Mathematical Society, 1984
In what follows k denotes the field of real or complex numbers. If \(D,0\subset k^ p\), 0 is the discriminant variety of the versal unfolding of an analytic function germ \(f: k^ n,0\to k,0\), it is of some interest to classify smooth functions h: D,0\(\to k,0.\) In Commun. Pure Appl. Math. 29, 557-582 (1976; Zbl 0343.58003), \textit{V. I.
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In what follows k denotes the field of real or complex numbers. If \(D,0\subset k^ p\), 0 is the discriminant variety of the versal unfolding of an analytic function germ \(f: k^ n,0\to k,0\), it is of some interest to classify smooth functions h: D,0\(\to k,0.\) In Commun. Pure Appl. Math. 29, 557-582 (1976; Zbl 0343.58003), \textit{V. I.
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Discriminant Function Analysis
2001The aim of cluster analysis, the subject of the previous chapter, is to discover whether multivariate data contains relatively distinct groups of observations. A further aspect of the classification of multivariate data concerns the derivation of rules and procedures for allocating individuals to one of a set of a priori defined groups in some optimal ...
Brian Everitt, Sophia Rabe-Hesketh
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Functional Discriminant Coordinates
Communications in Statistics - Theory and Methods, 2014In this article we propose a new method of construction of discriminant coordinates and their kernel variant based on the regularization (ridge regression). Moreover, we compare the case of discriminant coordinates, functional discriminant coordinates and the kernel version of functional discriminant coordinates on 20 data sets from a wide variety of ...
Tomasz Górecki +2 more
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2002
In the previous lectures we have pointed out several times that linear discriminant functions deserve some special attention. First, some statistical models are known to have the Bayesian or non-Bayesian strategy implemented, namely, by means of linear discriminant functions.
Michail I. Schlesinger, Václav Hlaváč
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In the previous lectures we have pointed out several times that linear discriminant functions deserve some special attention. First, some statistical models are known to have the Bayesian or non-Bayesian strategy implemented, namely, by means of linear discriminant functions.
Michail I. Schlesinger, Václav Hlaváč
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Psychometric functions for level discrimination
The Journal of the Acoustical Society of America, 1991To determine the form of psychometric functions for 2I,2AFC level discrimination (commonly called intensity discrimination), ten increment levels were presented in random order within blocks of 100 trials. Stimuli were chosen to encompass a wide range of conditions and difference limens: eight 10-ms tones had frequencies of 0.25, 1, 8, or 14 kHz and ...
S, Buus, M, Florentine
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