On Sampling Errors in Empirical Orthogonal Functions

Modeling impulse response using Empirical Orthogonal Functions

There is a growing need for acoustic channel simulators. Among the reasons for this is the increased interest in underwater acoustic communications, but also the fact that measuring the characteristics of the underwater channel is very expensive. A channel simulator provides access to realistic channels, and allows us to compare algorithms and modulations under identical conditions. Channel sim...

Quasi-orthogonal expansions for functions in BMO

For {φ_n(x)}, x ε [0,1] an orthonormalsystem of uniformly bounded functions, ||φ_n||_{∞}≤ M

Ensemble inference in terms of empirical orthogonal functions

Many geophysical problems involve inverting data in order to obtain meaningful descriptions of the Earth‘s interior. One of the basic characteristics of these inverse problems is their non-uniqueness. Since computation power has increased enormously in the last few years, it has become possible to deal with this non-uniqueness by generating and selecting a number of models that all fit the data...

Effect of Sampling Errors On

Charles R. Baker Department of Statistics University of North Carolina Chapel Hill, North Carolina 27514 Louis R. Chow Department of Computer Science Tamkang College Taipei, Taiwan The "Bryn Processor" is a well-known array processor; its design depends on spectral densities of the signal and noise processes. Array output signal-to-noise ratio can be decreased because of errors in sampling time...

Reconstructing Sea Level Using Cyclostationary Empirical Orthogonal Functions