Electronic devices exposed to high level electromagnetic interference with certain amplitude will fail with a certain probability. Knowing this failure probability is essential when a system is being designed to withstand intentional electromagnetic interference (IEMI). Based on this knowledge additional redundancy can be included in order to reduce the risk. In previous investigations [1] failure probability was analyzed for the case where a device was illuminated from one direction only. If the device is illuminated from other (random) directions, then the failure probability will change. In this contribution it is discussed how the failure probability determined for one direction can be extended in order to include a random angle of incidence of the interference. The main focus of this contribution is on failure probability caused by pulsed wideband signals. However, the approach presented here can also be extended to narrowband signals.

The determination of a radiation pattern for an unintentional emitter is very time-consuming. Therefore, approaches are needed to reduce the costs of such measurements. In previous research, stochastic approaches have been developed to describe the distribution of the directivity and to predict the maximum directivity for continuous wave signals. However, if the radiation pattern needs to be known for a large frequency band, the characteristics of the emitter vary with the frequency. In this paper, the radiation patterns of unintentional emitters are examined for a large frequency band. Based on a simulation model, the similarity of the radiation patterns at different frequencies is determined by calculating the correlation coefficient. It is shown that radiation patterns of close frequencies are correlated up to a correlation distance which is dependent on the electrical size of the emitter.

Temporal subtraction techniques using 2D image registration improve the detectability of interval changes from chest radiographs. Although such methods are well known for some time they are not widely used in radiologic practice. The reason is the occurrence of strong pose differences between two acquisitions with a time interval of months to years in between. Such strong perspective differences occur in a reasonable number of cases. They cannot be compensated by available image registration methods and thus mask interval changes to be undetectable. In this paper a method is proposed to estimate a 3D pose difference by the adaptation of a 3D rib cage model to both projections. The difference between both is then compensated for, thus producing a subtraction image with virtually no change in pose. The method generally assumes that no 3D image data is available from the patient. The accuracy of pose estimation is validated with chest phantom images acquired under controlled geometric conditions. A subtle interval change simulated by a piece of plastic foam attached to the phantom becomes visible in subtraction images generated with this technique even at strong angular pose differences like an anterior-posterior inclination of 13 degrees.

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