搜索结果: 121-135 共查到“代数几何学”相关记录451条 . 查询时间(0.559 秒)
This brief paper introduces an algorithm for smooth interpolation of a
multivariate function. The input data for the algorithm consists of a set of function
values and derivatives up to order r on a...
Asymptotic Analysis of Subcritical Hopf-Homoclinic Bifurcation
Hopf-Homoclinic Bifurcation Asymptotic
2015/8/25
termined by the coincidence of a subcritical Hopf bifurcation with a homoclinic orbit
of the Hopf equilibrium. Our work is motivated by our previous analysis of a
Hodgkin-Huxley neuron model which p...
The Hodgkin–Huxley model was developed to characterize the action potential of a squid axon. It has
served as an archetype for compartmental models of the electrophysiology of biological membranes.
...
Fast Slant Stack: A notion of Radon Transform for Data in a Cartesian Grid which is Rapidly Computible, Algebraically Exact, Geometrically Faithful and Invertible
Radon Transform Projection-slice theorem Sinc-Interpolation,
2015/8/21
We define a notion of Radon Transform for data in an n by n grid. It is based on summation
along lines of absolute slope less than 1 (as a function either of x or of y), with values at non-Cart...
Adapting to Unknown Sparsity by controlling the False Discovery Rate
Thresholding Wavelet Denoising Minimax Estimation
2015/8/21
We attempt to recover a high-dimensional vector observed in white noise, where
the vector is known to be sparse, but the degree of sparsity is unknown. We consider
three di®erent ways of deˉnin...
We describe a frameworkfor multiscale image analysis in which line
segments play a role analogous to the role played by points in wavelet analysis.
The frameworkhas 5 key components.
Grouping tasks and data display items via the non-negative matrix factorization
Grouping tasks non-negative matrix factorization
2015/8/21
Analyzing work functions and the IO variables they
need is an important component of designing and evaluating
complex systems. We develop a biclustering method for jointly
grouping work functions a...
ON THE DISTRIBUTION OF THE LARGEST EIGENVALUE IN PRINCIPAL COMPONENTS ANALYSIS
LARGEST EIGENVALUE PRINCIPAL COMPONENTS
2015/8/20
Let x1 denote the square of the largest singular value of an n × p
matrix X, all of whose entries are independent standard Gaussian varates. Equivalently, x1 is the largest principal component vari...
Given data from a spherical Gaussian distribution with unknown mean
vector θ, estimates of quadratic functionals are constructed by thresholding. Mean
squared error bounds are derived via a comparis...
Modern scientific technology is providing a new class of large-scale simultaneous
inference problems, with hundreds or thousands of hypothesis tests to consider at the
same time. Microarrays e...
Large-Scale Simultaneous Hypothesis Testing: The Choice of a Null Hypothesis
Null Hypothesis Simultaneous Hypothesis Testing
2015/8/20
Current scientific techniques in genomics and image processing routinely produce hypothesis testing problems with hundreds or thousands of cases to consider simultaneously.
This poses new di...
False Discovery Rates and Copy Number Variation
False discovery rate multiple testing grouped hypotheses
2015/8/20
Copy number changes, the gains and losses of chromosome segments, are a common type
of genetic variation among healthy individuals as well as an important feature in tumor
genomes. Microarray techno...
GRANULOMETRIC SMOOTHING
SMOOTHING GRANULOMETRIC
2015/8/20
A new method for smoothing a multivariate data set is introduced
that is based on a simple geometric operation. This method is applied to
the problem of estimating level sets of a density and minimu...
Discussion of ‘Maximum likelihood estimation of a multi-dimensional log-concave density’ by M. Cule, R. Samworth and M. Stewart
likelihood estimation multi-dimensional log-concave density
2015/8/20
I started looking at log-concave distributions when I was searching for an appropriate model
for subpopulations of multivariate flow cytometry data about ten years ago. The use of log-concave
...
The Block Criterion for Multiscale Inference About a Density, With Applications to Other Multiscale Problems
Fast algorithm Local increase in a density Multiscale test.
2015/8/20
The use of multiscale statistics, that is, the simultaneous inference about various
stretches of data via multiple localized statistics, is a natural and popular method for
inference about, for exam...