178 resultados para Space representations


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High-power (more than 500 mW) and high-speed (more than 1 Gbps) tapered lasers at 1060 nm are required in free-space optical communications and (at lower frequencies of around 100 MHz) display applications for frequency doubling to the green. On a 3 mm long tapered laser, we have obtained an open eye diagram at 1 Gbps, together with a high extinction ratio of 11 dB, an optical modulation amplitude of 530 mW, and a high modulation efficiency of 13 W/A. On a 4 mm-long tapered laser, we have obtained an open eye diagram at 700 Mbps, together with a high extinction ratio of 19 dB, a high optical modulation amplitude of 1.6 W, and a very high modulation efficiency of 19 W/A. On a 6 mm-long tapered laser, we have obtained a very high power of 5W CW and a very high static modulation efficiency of 59.8 W/A. © 2011 SPIE.

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RoFSO links are found to be susceptible to high-order laser distortion making conventional SFDR ineffective as a performance indicator. For the first time, peak input power is demonstrated as a service-independent bound on dynamic range. © 2011 OSA.

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Rhythmic and discrete arm movements occur ubiquitously in everyday life, and there is a debate as to whether these two classes of movements arise from the same or different underlying neural mechanisms. Here we examine interference in a motor-learning paradigm to test whether rhythmic and discrete movements employ at least partially separate neural representations. Subjects were required to make circular movements of their right hand while they were exposed to a velocity-dependent force field that perturbed the circularity of the movement path. The direction of the force-field perturbation reversed at the end of each block of 20 revolutions. When subjects made only rhythmic or only discrete circular movements, interference was observed when switching between the two opposing force fields. However, when subjects alternated between blocks of rhythmic and discrete movements, such that each was uniquely associated with one of the perturbation directions, interference was significantly reduced. Only in this case did subjects learn to corepresent the two opposing perturbations, suggesting that different neural resources were employed for the two movement types. Our results provide further evidence that rhythmic and discrete movements employ at least partially separate control mechanisms in the motor system.

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Uncertainty is ubiquitous in our sensorimotor interactions, arising from factors such as sensory and motor noise and ambiguity about the environment. Setting it apart from previous theories, a quintessential property of the Bayesian framework for making inference about the state of world so as to select actions, is the requirement to represent the uncertainty associated with inferences in the form of probability distributions. In the context of sensorimotor control and learning, the Bayesian framework suggests that to respond optimally to environmental stimuli the central nervous system needs to construct estimates of the sensorimotor transformations, in the form of internal models, as well as represent the structure of the uncertainty in the inputs, outputs and in the transformations themselves. Here we review Bayesian inference and learning models that have been successful in demonstrating the sensitivity of the sensorimotor system to different forms of uncertainty as well as recent studies aimed at characterizing the representation of the uncertainty at different computational levels.