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Angel, E.

Publications and source records attributed to Angel, E..

A dimensionality reducing model for distributed filtering.

An approach is made to filtering of two-dimensional steady-state problems based on the notion of nearest neighbor interaction, i.e., at a given point in the spatial grid, the value at the variable of interest can be assumed to depend only on the values at adjacent grid points. It is shown that for linear steady-state problems significant dimensionality reductions can be accomplished. It was possible to achieve the desired results using a small amount of computer time and without getting into stability difficulties.

Angel, E.

A nearest neighbors approach to multidimensional filtering.

The concept of nearest neighbor interaction is applied as a basis for data filtering in two-dimensional steady state problems. A steady state process represented by a potential equation with additive white noise is used to illustrate the application of this concept. It is demonstrated that significant dimensionality reductions can be achieved by applying this concept to various linear steady state problems.

Angel, E.