Open AccessResolution analysis for discrete systems
Author(s) -
Kennett Brian,
Nolet Guust
Publication year - 1978
Publication title -
geophysical journal of the royal astronomical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.302
H-Index - 168
eISSN - 1365-246X
pISSN - 0016-8009
DOI - 10.1111/j.1365-246x.1978.tb03749.x
Subject(s) - discretization , piecewise linear function , inverse theory , inversion (geology) , monte carlo method , resolution (logic) , inverse problem , mathematics , inverse , piecewise , algorithm , estimation theory , set (abstract data type) , computer science , mathematical optimization , mathematical analysis , geology , statistics , geometry , telecommunications , paleontology , structural basin , artificial intelligence , surface wave , programming language
summary . Treatments of geophysical inverse problems have tended to polarize into approaches intended to generate models either described by piecewise continuous functions or with some prior discretization. The two approaches are here developed in parallel, and the ideas of a trade‐off between the anticipated error and the attainable level of detail in the model estimate are extended to the discrete case, either with even or uneven discretization. An alternative approach to specifying the potential resolution of a model is to establish upper and lower bounds on parameter values. Linear programming methods are extended to determine bounds which allow for subjective limits on parameter values. For a non‐linear system the possible resolution may be investigated by estimation procedures based on the full set of successful solutions obtained by Monte‐Carlo inversion.