Engineering topics

Ojalvo, Irving U.

Publications and source records attributed to Ojalvo, Irving U..

3 records

NASA NTRS1991

Improved solution for ill-conditioned algebraic equations by epsilon decomposition

Matrix eigenvalue theory is presently used to examine the source of ill-conditioning in linear algebraic equations; the approach highlights the critical role played by the zero and near-zero eigenvalues and corresponding eigenvectors of poorly-conditioned systems. Insights derived from this approach are used to improve the recently developed epsilon-decomposition (E-D) solution procedure. The efficiency of E-D is significant for large matrices possessing small rank deficiency.

Ojalvo, Irving U.↗

NASA NTRS1990

Improved solution for system identification equations by Epsilon-Decomposition

Matrix eigenvalue theory is used to examine the source of ill-conditioning in linear algebraic equations. This approach highlights the crucial role played by the zero and near-zero eigenvalues and corresponding eigenvectors of poorly conditioned systems. Insight gained from this approach is used to significantly improve a recently developed solution procedure called Epsilon-Decomposition (E-D). E-D is an efficient alternative to Singular Value Decomposition (SVD) for ill-conditioned systems arising in parameter estimation and system identification studies. The efficiency of the improved E-D over SVD resides in the need to only obtain the zero and near-zero eigenvalues of the coefficient matrix as opposed to all of its eigenvalues and vectors (as required by SVD). Thus, the efficiency of E-D is significant for large matrices with small rank deficiency.

Ojalvo, Irving U.↗

NASA NTRS1990

Simplified detection and correction of critical data for ill-conditioned systems

Ill-conditioned systems arising in analysis and optimization can display a high sensitivity to numerical precision for changes and errors in data input. Such data may be in the form of system parameter input or desired system response. The ill-conditioning referred to generally arises from the lack of sufficient independent data to define a complex system or the weak sensitivity of response to source input parameters. It is shown how small errors in data and assumed fixed and known parameters can lead to highly erroneous results in ill-conditioned linear algebraic equations. A simplified detection and correction of critical input data arising in the coefficient matrix and desired response (i.e., right hand side) is proposed.

Ojalvo, Irving U.↗