the method of empirical orthogonal function (EOF) analysis is a decomposition of a signal or data set in terms of orthogonal basis functions which are determined...

flow, the motion of liquid induced by an applied potential Empirical orthogonal functions, in statistics and signal processing Ethyl orthoformate, an...

Eckart–Young theorem (Harman, 1960), or empirical orthogonal functions (EOF) in meteorological science (Lorenz, 1956), empirical eigenfunction decomposition (Sirovich...

dimensions. The Hilbert–Huang empirical mode decomposition (EMD) process decomposes a signal into intrinsic mode functions combined with the Hilbert spectral...

differintegral Generalized Fourier series Orthogonal functions Orthogonal polynomials Empirical orthogonal functions Set of uniqueness Continuous Fourier transform...

the northwestern Pacific and compared the results to vector empirical orthogonal function results. Ocean engineering: Schlurmann [2002] introduced the...

an infinite linear combination of orthogonal functions, analogous to a Fourier series representation of a function on a bounded interval. The transformation...

number theory, the distribution of zeros of the Riemann zeta function (and other L-functions) is modeled by the distribution of eigenvalues of certain random...

processing Dimensionality reduction Eigendecomposition of a matrix Empirical orthogonal functions (EOFs) Fourier analysis Generalized singular value decomposition...

1997. The Pacific decadal oscillation index is the leading empirical orthogonal function (EOF) of monthly sea surface temperature anomalies (SST-A) over...

The proper orthogonal decomposition is a numerical method that enables a reduction in the complexity of computer intensive simulations such as computational...

distribution Empirical Empirical Bayes method Empirical distribution function Empirical likelihood Empirical measure Empirical orthogonal functions Empirical probability...

matrix C X {\displaystyle {\textbf {C}}_{X}} are called temporal empirical orthogonal functions (EOFs). The eigenvalues λ k {\displaystyle \lambda _{k}} of...

oscillation loading pattern, which is defined as the first empirical orthogonal function (EOF) of monthly mean 1000 hPa geopotential height during the...

available in PROC FACTOR using ROTATE = VARIMAX. Factor analysis Empirical orthogonal functions Q methodology Rotation matrix Henry F. Kaiser (September 1958)...

advantages over the conventional feature extraction methods such as Empirical Orthogonal Functions (EOF) or PCA. Additionally, researchers found that Clustering...

filter to remove unwanted noise Principal component analysis (or empirical orthogonal function analysis) Singular spectrum analysis "Structural" models: General...

over time in the spatial field of interest (defined as the empirical orthogonal functions, or EOFs) using both local relationships of the proxies to climate...

"A high-resolution model of field-aligned currents through empirical orthogonal functions analysis (MFACE)". Geophysical Research Letters. 39 (18). Bibcode:2012GeoRL...

method, to calculate approximate wave functions and energies for atoms and ions. Hartree sought to do away with empirical parameters and solve the many-body...

Orthogonal defect classification (ODC) turns semantic information in the software defect stream into a measurement on the process. The ideas were developed...

(1992). "Orthogonal arrays for computer experiments, integration and visualization". Statistica Sinica. 2: 439–452. Ye, K.Q. (1998). "Orthogonal column...

is defined as the spatial distribution of the second leading empirical orthogonal functions mode of monthly mean sea level pressure north of 70° N, where...

S2CID 254965361. Hannachi, A.; Jolliffe, I.; Stephenson, D. (2007). "Empirical orthogonal functions and related techniques in atmospheric science: A review". International...

by numerical weather prediction, is based on the principal empirical orthogonal function (EOF) of surface pressure. This definition has a high degree...

2013) proposed orthogonal initialization: initializing weight matrices as uniformly random (according to the Haar measure) semi-orthogonal matrices, multiplied...

of Fourier series, one learns that the functions {1} ∪ { sin(nx), cos(nx) : n = 1, 2, 3, ... } are an "orthogonal basis" of the (real or complex) vector...

between the hinge loss and these other loss functions is best stated in terms of target functions - the function that minimizes expected risk for a given...

combinatorics, two Latin squares of the same size (order) are said to be orthogonal if when superimposed the ordered paired entries in the positions are all...

and since it is used in many machine learning proofs on bounding empirical loss functions (including the proof of the VC inequality which is discussed in...