Besides the recognition of audible speech, there is currently an increasing interest in the recognition of silent speech, which has a range of novel applications. A major obstacle for a wide spread of silent-speech technology is the lack of measurement methods for speech movements that are convenient, non-invasive, portable, and robust at the same time. Therefore, as an alternative to established methods, we examined to what extent different phonemes can be discriminated from the electromagnetic transmission and reflection properties of the vocal tract. To this end, we attached two Vivaldi antennas on the cheek and below the chin of two subjects. While the subjects produced 25 phonemes in multiple phonetic contexts each, we measured the electromagnetic transmission spectra from one antenna to the other, and the reflection spectra for each antenna (radar), in a frequency band from 2-12 GHz. Two classification methods (k-nearest neighbors and linear discriminant analysis) were trained to predict the phoneme identity from the spectral data. With linear discriminant analysis, cross-validated phoneme recognition rates of 93% and 85% were achieved for the two subjects. Although these results are speaker- and session-dependent, they suggest that electromagnetic transmission and reflection measurements of the vocal tract have great potential for future silent-speech interfaces.

This work presents results for wireless outdoor MIMO transmission experiments at 2.68 GHz, which were conducted in an urban residential area, using realistic handset and base station antennas. Characteristic parameters of MIMO systems, obtained from measurements, were compared to theoretical results. From the comparison it could be concluded that the transmission of two spatial streams was well supported in the investigated 2 × 2 MIMO system, even with receive antenna element spacings as small as a quarter of the wave length. Comparing different receive antennas, the MIMO performance was found to be dominated by the received signal power rather than the spatial correlation.

An optimised schedule is vital for the operation of an interplanetary space mission. The scheduling problem of a mission with the scientific objective of reaching global coverage with more than one instrument is complex and highly restricted. Evolutionary algorithms can be an efficient method in solving scheduling problems and generating pareto-optimal alternatives. The application of an algorithm combining evolutionary strategy, genetic algorithm and differential evolution is demonstrated for a reference scenario of a low-orbit Moon mapping mission. A reduced set of restrictions is taken into account for creating a master schedule for the operation of three different instruments for the whole mission time. An optimal set of short term operation time lines for one orbit is generated, which can be combined to a complete mission schedule. The results show that more than one year mission time can be saved with an optimised schedule.