Robustness of Logical Depth

Parallel Computational Complexity and Logical Depth in Statistical Physics

Polynomial Depth, Highness and Lowness for E

We study the relations between the notions of highness, lowness and logical depth in the setting of complexity theory. We introduce a new notion of polynomial depth based on time bounded Kolmogorov complexity. We show our polynomial depth notion satisfies all basic logical depth properties, namely neither sets in P nor sets random for EXP are polynomial deep, and only polynomial deep sets can p...

Fractured Processes: Adaptive, Fine-Grained Process Abstractions

We introduce Fracture, a novel framework that transforms and modernizes the basic process abstraction. By “fracturing” an application into logical modules, Fracture enables powerful and novel run-time configurations that improve run-time testing, application availability, and general robustness, all in a generic and incremental manner. We demonstrate the utility of fracturing via in-depth case ...

Robustness of image-based visual servoing with respect to depth distribution error

This paper concerns the stability analysis of image-based visual servoing methods with respect to uncertainties on the depths of the observed object. In the recent past, research on image-based visual servoing has been concentrated on potential problems of stability and on robustness with respect to camera calibration errors. Only little attention, if any, has been devoted to the robustness of ...

Image information content characterization and classification by physical complexity

We present a method for estimating the complexity of an image based on the concept of logical depth. Unlike the application of the concept of algorithmic complexity by itself, the addition of the concept of logical depth results in a characterization of objects by organizational (physical) complexity. We use this measure to classify images by their information content. The method provides a mea...