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Closed-loop operation of a brain-machine interface (BMI) relies on the subject's ability to learn an inverse transformation of the plant to be controlled. In this paper, we propose a model of the learning process that undergoes closed-loop BMI operation. We first explore the properties of the model and show that it is able to learn an inverse model of the controlled plant. Then, we compare the model...
This paper presents a model of the learning process occurring during operation of a closed-loop brain-machine interface. The model consists of a population of simulated cortical neurons, a decoder that transforms neural activity into motor output, a feedback controller whose role is to reduce the error based on an error-descent algorithm, and an open-loop controller whose parameters are updated based...
The continued increase of the integration density of systems on chip (SoCs) and the number of embedded memory blocks in them, together with the continued technology scaling, increases their sensitivity to a variety of potential manufacturing (new) defects. Standard march tests are usually used to achieve a good fault/defect coverage. This paper presents an experiment in diagnosing defects in the circuitry...
The standardization of train communications protocols, train communication network (TCN), has created a need to design new electronic devices which can communicate according to them. Up to date, several solutions have been suggested, but every one needs additional circuits. In this article we present a novel flexible architecture which allows the materialization of slave nodes for multifunction vehicle...
Networks in trains are mobile communication systems which require, above all, safety and reliability. So, the electronic creation flow should ensure that the designed line controller (mainly coder and decoder) is secure. However, verifying the behavior and performance of such an electronic circuit is not a simple task. Most times, the receiver must accept a certain minimum distortion, so some imperfect...
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