Titlebook: Nahost Jahrbuch 1989; Politik, Wirtschaft Thomas Koszinowski,Hanspeter Mattes Book 1990 Leske Verlag + Budrich GmbH, Opladen 1990 Beziehun

馆长

Thomas Koszinowski,Hanspeter Mattesrement, an actuator in the system, and a setpoint or reference—the measurement is compared with the reference and an actuator action is derived from the difference between them. This simple but powerful structure is responsible for providing the system with robustness against external influences. Fo

attenuate

lving from nature (such as redundancy, granularity, adaptatiOur time recognizes robustness as an important, all-pervading feature in the world around us. Despite its omnipresence, robustness is not entirely understood, rather dif?cult to de?ne, and, despite its obvious value in many situations, rath

Decongestant

Thomas Koszinowskirement, an actuator in the system, and a setpoint or reference—the measurement is compared with the reference and an actuator action is derived from the difference between them. This simple but powerful structure is responsible for providing the system with robustness against external influences. Fo

训诫

fixed-joint

Hanspeter Mattesnly at discrete sampling instants. Hence, we are motivated to consider“hybrid” problems of problems of state estimation and model validation in which the underlying process model is continuous but the available measured data are available at discrete sampling times. Furthermore, we extend this probl

APNEA

Aziz Alkazazowever, in the design of feedback control systems, robustness is a critical issue. These facts led to great activity in the research area of robust control theory. One of the major developments of modern control theory was the Kalman Filter and hence the development of a robust version of the Kalman

战役

妈妈不开心

Udo Steinbachsportation, cloud computing, and so on. It is of great significance to analyze them for mining rich and valuable knowledge and patterns. Latent feature analysis (LFA) is one of the most popular representation learning methods tailored for incomplete big data due to its high accuracy, computational e

刺激

Erhard Franzrity of) adversarial nodes. Basically, we saw that upon replacing the simple averaging operation at the server by an aggregation scheme that satisfies the property of .-robust averaging, the resulting . method can tolerate up to . adversarial nodes. We formalized the notion of robustness against adv

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