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Orthogonal transformations of digital data

Conference ·
OSTI ID:5364550
The application of orthogonal transformations to digital data is somewhat analogous to the use of Fourier and Laplace transforms with analog data. Some motivations for making transformations are to emphasize or suppress features and to code or mask the data. Two families of transformations and their possible application are discussed. One of these is derived from the relatively well-known Walsh functions; the other is an apparently new transformation technique based on matrix algebra. Certain Walsh functions have patterns similar to those caused by sinusoidal noise sources. A method is described for identifying the appropriate Walsh functions, and then for resolving phase-shifted patterns into sums of pairs of Walsh functions. This procedure is analogous to the resolution of a phase-shifted sinusoidal signal into the sum of a sine and a cosine signal. This technique is useful when periodic perturbations must be filtered out from the data or enhanced. An application for these modified Walsh transforms is described for identifying features in radar return from the ground; and an application for the new matrix algebra technique used for masking data is presented. 1 figure, 1 table.
Research Organization:
Sandia Labs., Albuquerque, N.Mex. (USA)
DOE Contract Number:
EY-76-C-04-0789
OSTI ID:
5364550
Report Number(s):
SAND-77-1605C; CONF-771206-17
Country of Publication:
United States
Language:
English

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