Engineering topics

Lynn, M. S.

Publications and source records attributed to Lynn, M. S..

5 records

NASA NTRS1976

The use of the Winograd matrix multiplication algorithm in digital multispectral processing

The Winograd procedure for matrix multiplication provides a method whereby general matrix products may be computed more efficiently than the normal method. The algorithm and the time savings that can be effected are described. A FORTRAN program is provided which performs a general matrix multiply according to this algorithm. A variation of this procedure that may be used to calculate Gaussian probability density functions is also described. It is shown how a time savings can be effected in this calculation. The extension of this method to other similar calculations should yield similar savings.

Vanrooy, D. L.↗

NASA NTRS1974

An Analysis of Applications Development Systems for Remotely Sensed, Multispectral Data for the Earth Observations Division of the NASA Lyndon B. Johnson Space Center

An application development system (ADS) is examined for remotely sensed, multispectral data at the Earth Observations Division (EOD) at Johnson Space Center. Design goals are detailed, along with design objectives that an ideal system should contain. The design objectives were arranged according to the priorities of EOD's program objectives. Four systems available to EOD were then measured against the ideal ADS as defined by the design objectives and their associated priorities. This was accomplished by rating each of the systems on each of the design objectives. Utilizing the established priorities, it was determined how each system stood up as an ADS. Recommendations were made as to possible courses of action for EOD to pursue to obtain a more efficient ADS.

Vanrooy, D. L.↗

NASA NTRS1973

Use of spatial information in classification of remotely sensed data

The use is discussed of spatial information for improving classification accuracy of remotely sensed data. In particular a simple example (the unanimous four nearest neighbor rule) is discussed and its results are presented. This algorithm results in improved classifications accuracy (one to five percentage points) and costs little in execution time. Other schemes for improving classification accuracy are also discussed.

Vanroony, D. L.↗

NASA NTRS1973

The use of the modified Cholesky decomposition in divergence and classification calculations

The use of the Cholesky decomposition technique is analyzed as applied to the feature selection and classification algorithms used in the analysis of remote sensing data (e.g. as in LARSYS). This technique is approximately 30% faster in classification and a factor of 2-3 faster in divergence, as compared with LARSYS. Also numerical stability and accuracy are slightly improved. Other methods necessary to deal with numerical stablity problems are briefly discussed.

Vanroony, D. L.↗

NASA NTRS1973

The use of the modified Cholesky decomposition in divergence and classification calculations

This report analyzes the use of the modified Cholesky decomposition technique as applied to the feature selection and classification algorithms used in the analysis of remote sensing data (e.g., as in LARSYS). This technique is approximately 30% faster in classification and a factor of 2-3 faster in divergence, as compared with LARSYS. Also numerical stability and accuracy are slightly improved. Other methods necessary to deal with numerical stability problems are briefly discussed.

Van Rooy, D. L.↗