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In Brain Machine Interface (BMI), movement direction can be decoded using intra-cortical recordings such as Local Field Potentials (LFP). Due to the natural instability and non-stationarity of these recordings, it is difficult to develop decoders that remain consistent over time and are not affected by learning. This paper uses qualitative information based on the temporal and spatial distribution...
We present a robust probabilistic method to classify targets based on their tracks. As is customary in supervised learning problems, it is assumed that example tracks from various classes are available to train a classifier. We present an optimal but computationally intensive sequential solution, and show that a computationally feasible naive Bayes approximation works better than ignoring sequential...
We implement and evaluate a method infer position from Doppler measurements in a multistatic sonar scenario and present a likelihood approach for doing so. Doppler measurements are used to create likelihood surfaces for each of the transmitter-receiver pairs. The likelihood surfaces are combined and can then be used as-is or combined with additional position measurements. The final likelihood surface...
In order to attain near-single user performance in uplink multicarrier code division multiple access (MC-CDMA) systems, multiuser detection (MUD) methods may be employed which rely on simultaneous estimation of the channel frequency response of multiple users. In this paper, performance of a MC-CDMA system employing minimum mean-square error (MMSE) MUD at receiver, is evaluated using two pilot symbol...
In order to attain near-single user performance in uplink multicarrier code division multiple access (MC-CDMA) systems, multiuser detection (MUD) methods may be employed. However, most of MUD methods rely on simultaneous estimation of the channel frequency response of multiple users. In this paper, performance of a MC-CDMA system employing minimum mean-square error (MMSE) MUD at receiver is evaluated...
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