Nonlinear directed acyclic structure learning with weakly additive noise models Peter Spirtes Arthur Gretton Robert E. Tillman

Source URL: select.cs.cmu.edu

• Statistics
• Analysis
• Data
• Statistical models
• Multivariate statistics
• Signal processing
• Data analysis
• Independent component analysis
• Time series analysis
• Additive white Gaussian noise
• Gaussian function
• Positive-definite kernel

Perception, 2002, volume 31, pages 1211 ^ 1219 DOI:p3254 Blur discrimination and its relation to blur-mediated depth perception

Source URL: www.georgemather.com

• Science of photography
• Geometrical optics
• Vision
• Image processing
• Gaussian blur
• Gaussian function
• Blur
• Depth perception
• Depth of field
• Focus

Spread-Spectrum Multiple-Access Performance of Orthogonal Codes: Linear Receivers PER K. ENGE, MEMBER, IEEE, AND

Source URL: www.ifp.illinois.edu

• Data transmission
• Signal processing
• Central limit theorem
• Additive white Gaussian noise
• Gaussian function
• Phase-shift keying
• Discrete Fourier transform
• KarhunenLove theorem
• Kalman filter

9. Gaussian random sequences We start with recalling of the definition for Gaussian random variable which is completely defined by a density f (x) of its distribution function F (x): (x−m)2 1

Source URL: www.eng.tau.ac.il

Gaussian Process-based Feature Selection for Wavelet Parameters: Predicting Acute Hypotensive Episodes from Physiological Signals Franck Dernoncourt, Kalyan Veeramachaneni, Una-May O’Reilly MIT CSAIL ALFA Cambridge, MA

Source URL: groups.csail.mit.edu

• Signal processing
• Functional analysis
• Time series analysis
• Timefrequency analysis
• Wavelet
• Numerical analysis
• Continuous wavelet transform
• Gaussian process
• Continuous wavelet
• Kernel
• Window function

Yang_Bo_Scientific_Report

Source URL: fellowship.ercim.eu

• Orthogonal polynomials
• Computer vision
• Hermite polynomials
• Polynomials
• Image moment
• Gaussian function
• Charles Hermite
• Hermite
• Invariant

HW #2 (221B), due Feb 2, 4pm 1. Use the solution for ψ(x) from the Lippmann–Schwinger equation in the case of the one-dimentional delta function potential you studied in HW #1. Form a Gaussian wave packet of the solut

Source URL: hitoshi.berkeley.edu

Inverse Kernels for Fast Spatial Deconvolution Li Xu† † Xin Tao‡

Source URL: www.cse.cuhk.edu.hk

• Image processing
• Signal processing
• Gaussian function
• Feature detection
• Estimation theory
• Deconvolution
• Wiener deconvolution
• Convolution
• Deblurring
• Kernel
• Gaussian blur
• Gaussian filter

1 Derivation of Band-Limited Expressions Given a shader function f (x) and a band-limiting kernel k(x, w) where w describes the width of the kernel, we wish to determine the convolution function

Source URL: www.connellybarnes.com

• Mathematical analysis
• Mathematics
• Special functions
• Fourier analysis
• Exponentials
• Gaussian function
• Periodic function
• Integral transform
• Sine
• Fourier series

GAUSSIAN FIELDS Notes for Lectures Ofer Zeitouni Department of Mathematics Weizmann Institute, Rehovot 76100, Israel and

Source URL: www.wisdom.weizmann.ac.il

• Stochastic processes
• Algebra of random variables
• Hilbert space
• Estimation theory
• KarhunenLove theorem
• Signal processing
• Gaussian free field
• Multivariate random variable
• Reproducing kernel Hilbert space
• Covariance
• Normal distribution
• Gaussian function