955 resultados para dynamic visual noise


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This paper presents a direct digital frequency synthesizer (DDFS) with a 16-bit accumulator, a fourth-order phase domain single-stage Delta Sigma interpolator, and a 300-MS/s 12-bit current-steering DAC based on the Q(2) Random Walk switching scheme. The Delta Sigma interpolator is used to reduce the phase truncation error and the ROM size. The implemented fourth-order single-stage Delta Sigma noise shaper reduces the effective phase bits by four and reduces the ROM size by 16 times. The DDFS prototype is fabricated in a 0.35-mu m CMOS technology with active area of 1.11 mm(2) including a 12-bit DAC. The measured DDFS spurious-free dynamic range (SFDR) is greater than 78 dB using a reduced ROM with 8-bit phase, 12-bit amplitude resolution and a size of 0.09 mm(2). The total power consumption of the DDFS is 200)mW with a 3.3-V power supply.

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This paper presents a direct digital frequency synthesizer (DDFS) with a 16-bit accumulator, a fourth-order phase domain single-stage Delta Sigma interpolator, and a 300-MS/s 12-bit current-steering DAC based on the Q(2) Random Walk switching scheme. The Delta Sigma interpolator is used to reduce the phase truncation error and the ROM size. The implemented fourth-order single-stage Delta Sigma noise shaper reduces the effective phase bits by four and reduces the ROM size by 16 times. The DDFS prototype is fabricated in a 0.35-mu m CMOS technology with active area of 1.11 mm(2) including a 12-bit DAC. The measured DDFS spurious-free dynamic range (SFDR) is greater than 78 dB using a reduced ROM with 8-bit phase, 12-bit amplitude resolution and a size of 0.09 mm(2). The total power consumption of the DDFS is 200)mW with a 3.3-V power supply.

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Recovering a volumetric model of a person, car, or other object of interest from a single snapshot would be useful for many computer graphics applications. 3D model estimation in general is hard, and currently requires active sensors, multiple views, or integration over time. For a known object class, however, 3D shape can be successfully inferred from a single snapshot. We present a method for generating a ``virtual visual hull''-- an estimate of the 3D shape of an object from a known class, given a single silhouette observed from an unknown viewpoint. For a given class, a large database of multi-view silhouette examples from calibrated, though possibly varied, camera rigs are collected. To infer a novel single view input silhouette's virtual visual hull, we search for 3D shapes in the database which are most consistent with the observed contour. The input is matched to component single views of the multi-view training examples. A set of viewpoint-aligned virtual views are generated from the visual hulls corresponding to these examples. The 3D shape estimate for the input is then found by interpolating between the contours of these aligned views. When the underlying shape is ambiguous given a single view silhouette, we produce multiple visual hull hypotheses; if a sequence of input images is available, a dynamic programming approach is applied to find the maximum likelihood path through the feasible hypotheses over time. We show results of our algorithm on real and synthetic images of people.

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We report a 75dB, 2.8mW, 100Hz-10kHz envelope detector in a 1.5mm 2.8V CMOS technology. The envelope detector performs input-dc-insensitive voltage-to-currentconverting rectification followed by novel nanopower current-mode peak detection. The use of a subthreshold wide- linear-range transconductor (WLR OTA) allows greater than 1.7Vpp input voltage swings. We show theoretically that this optimal performance is technology-independent for the given topology and may be improved only by spending more power. A novel circuit topology is used to perform 140nW peak detection with controllable attack and release time constants. The lower limits of envelope detection are determined by the more dominant of two effects: The first effect is caused by the inability of amplified high-frequency signals to exceed the deadzone created by exponential nonlinearities in the rectifier. The second effect is due to an output current caused by thermal noise rectification. We demonstrate good agreement of experimentally measured results with theory. The envelope detector is useful in low power bionic implants for the deaf, hearing aids, and speech-recognition front ends. Extension of the envelope detector to higher- frequency applications is straightforward if power consumption is inc

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A neural model is proposed of how laminar interactions in the visual cortex may learn and recognize object texture and form boundaries. The model brings together five interacting processes: region-based texture classification, contour-based boundary grouping, surface filling-in, spatial attention, and object attention. The model shows how form boundaries can determine regions in which surface filling-in occurs; how surface filling-in interacts with spatial attention to generate a form-fitting distribution of spatial attention, or attentional shroud; how the strongest shroud can inhibit weaker shrouds; and how the winning shroud regulates learning of texture categories, and thus the allocation of object attention. The model can discriminate abutted textures with blurred boundaries and is sensitive to texture boundary attributes like discontinuities in orientation and texture flow curvature as well as to relative orientations of texture elements. The model quantitatively fits a large set of human psychophysical data on orientation-based textures. Object boundar output of the model is compared to computer vision algorithms using a set of human segmented photographic images. The model classifies textures and suppresses noise using a multiple scale oriented filterbank and a distributed Adaptive Resonance Theory (dART) classifier. The matched signal between the bottom-up texture inputs and top-down learned texture categories is utilized by oriented competitive and cooperative grouping processes to generate texture boundaries that control surface filling-in and spatial attention. Topdown modulatory attentional feedback from boundary and surface representations to early filtering stages results in enhanced texture boundaries and more efficient learning of texture within attended surface regions. Surface-based attention also provides a self-supervising training signal for learning new textures. Importance of the surface-based attentional feedback in texture learning and classification is tested using a set of textured images from the Brodatz micro-texture album. Benchmark studies vary from 95.1% to 98.6% with attention, and from 90.6% to 93.2% without attention.

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All of us are taxed with juggling our inner mental lives with immediate external task demands. For many years, the temporary maintenance of internal information was considered to be handled by a dedicated working memory (WM) system. It has recently become increasingly clear, however, that such short-term internal activation interacts with attention focused on external stimuli. It is unclear, however, exactly why these two interact, at what level of processing, and to what degree. Because our internal maintenance and external attention processes co-occur with one another, the manner of their interaction has vast implications for functioning in daily life. The work described here has employed original experimental paradigms combining WM and attention task elements, functional magnetic resonance imaging (fMRI) to illuminate the associated neural processes, and transcranial magnetic stimulation (TMS) to clarify the causal substrates of attentional brain function. These studies have examined a mechanism that might explain why (and when) the content of WM can involuntarily capture visual attention. They have, furthermore, tested whether fundamental attentional selection processes operate within WM, and whether they are reciprocal with attention. Finally, they have illuminated the neural consequences of competing attentional demands. The findings indicate that WM shares representations, operating principles, and cognitive resources with externally-oriented attention.

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Each of our movements activates our own sensory receptors, and therefore keeping track of self-movement is a necessary part of analysing sensory input. One way in which the brain keeps track of self-movement is by monitoring an internal copy, or corollary discharge, of motor commands. This concept could explain why we perceive a stable visual world despite our frequent quick, or saccadic, eye movements: corollary discharge about each saccade would permit the visual system to ignore saccade-induced visual changes. The critical missing link has been the connection between corollary discharge and visual processing. Here we show that such a link is formed by a corollary discharge from the thalamus that targets the frontal cortex. In the thalamus, neurons in the mediodorsal nucleus relay a corollary discharge of saccades from the midbrain superior colliculus to the cortical frontal eye field. In the frontal eye field, neurons use corollary discharge to shift their visual receptive fields spatially before saccades. We tested the hypothesis that these two components-a pathway for corollary discharge and neurons with shifting receptive fields-form a circuit in which the corollary discharge drives the shift. First we showed that the known spatial and temporal properties of the corollary discharge predict the dynamic changes in spatial visual processing of cortical neurons when saccades are made. Then we moved from this correlation to causation by isolating single cortical neurons and showing that their spatial visual processing is impaired when corollary discharge from the thalamus is interrupted. Thus the visual processing of frontal neurons is spatiotemporally matched with, and functionally dependent on, corollary discharge input from the thalamus. These experiments establish the first link between corollary discharge and visual processing, delineate a brain circuit that is well suited for mediating visual stability, and provide a framework for studying corollary discharge in other sensory systems.

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Using a speed-matching task, we measured the speed tuning of the dynamic motion aftereVect (MAE). The results of our Wrst experiment, in which we co-varied dot speed in the adaptation and test stimuli, revealed a speed tuning function. We sought to tease apart what contribution, if any, the test stimulus makes towards the observed speed tuning. This was examined by independently manipulating dot speed in the adaptation and test stimuli, and measuring the eVect this had on the perceived speed of the dynamic MAE. The results revealed that the speed tuning of the dynamic MAE is determined, not by the speed of the adaptation stimulus, but by the local motion characteristics of the dynamic test stimulus. The role of the test stimulus in determining the perceived speed of the dynamic MAE was conWrmed by showing that, if one uses a test stimulus containing two sources of local speed information, observers report seeing a transparent MAE; this is despite the fact that adaptation is induced using a single-speed stimulus. Thus while the adaptation stimulus necessarily determines perceived direction of the dynamic MAE, its perceived speed is determined by the test stimulus. This dissociation of speed and direction supports the notion that the processing of these two visual attributes may be partially independent.

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Our understanding of how the visual system processes motion transparency, the phenomenon by which multiple directions of motion are perceived to co-exist in the same spatial region, has grown considerably in the past decade. There is compelling evidence that the process is driven by global-motion mechanisms. Consequently, although transparently moving surfaces are readily segmented over an extended space, the visual system cannot separate two motion signals that co-exist in the same local region. A related issue is whether the visual system can detect transparently moving surfaces simultaneously, or whether the component signals encounter a serial â??bottleneckâ?? during their processing? Our initial results show that, at sufficiently short stimulus durations, observers cannot accurately detect two superimposed directions; yet they have no difficulty in detecting one pattern direction in noise, supporting the serial-bottleneck scenario. However, in a second experiment, the difference in performance between the two tasks disappears when the component patterns are segregated. This discrepancy between the processing of transparent and non-overlapping patterns may be a consequence of suppressed activity of global-motion mechanisms when the transparent surfaces are presented in the same depth plane. To test this explanation, we repeated our initial experiment while separating the motion components in depth. The marked improvement in performance leads us to conclude that transparent motion signals are represented simultaneously.

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In this experiment, we examined the extent to which the spatiotemporal reorganization of muscle synergies mediates skill acquisition on a two degree-of-freedom (df) target-acquisition task. Eight participants completed five practice sessions on consecutive days. During each session they practiced movements to eight target positions presented by a visual display. The movements required combinations of flexion/extension and pronation/supination of the elbow joint complex. During practice sessions, eight targets displaced 5.4 cm from the start position ( representing joint excursions of 54) were presented 16 times. During pre- and posttests, participants acquired the targets at two distances (3.6 cm [36 degrees] and 7.2 cm [72 degrees]). EMG data were recorded from eight muscles contributing to the movements during the pre- and posttests. Most targets were acquired more rapidly after the practice period. Performance improvements were, in most target directions, accompanied by increases in the smoothness of the movement trajectories. When target acquisition required movement in both dfs, there were also practice-related decreases in the extent to which the trajectories deviated from a direct path to the target. The contribution of monofunctional muscles ( those producing torque in a single df) increased with practice during movements in which they acted as agonists. The activity in bifunctional muscles ( those contributing torque in both dfs) remained at pretest levels in most movements. The results suggest that performance gains were mediated primarily by changes in the spatial organization of muscles synergies. These changes were expressed most prominently in terms of the magnitude of activation of the monofunctional muscles.

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This paper introduces a novel channel inversion (CI) precoding scheme for the downlink of phase shift keying (PSK)-based multiple input multiple output (MIMO) systems. In contrast to common practice where knowledge of the interference is used to eliminate it, the main idea proposed here is to use this knowledge to glean benefit from the interference. It will be shown that the system performance can be enhanced by exploiting some of the existent inter-channel interference (ICI). This is achieved by applying partial channel inversion such that the constructive part of ICI is preserved and exploited while the destructive part is eliminated by means of CI precoding. By doing so, the effective signal to interference-plus-noise ratio (SINR) delivered to the mobile unit (MU) receivers is enhanced without the need to invest additional transmitted signal power at the MIMO base station (BS). It is shown that the trade-off to this benefit is a minor increase in the complexity of the BS processing. The presented theoretical analysis and simulations demonstrate that due to the SINR enhancement, significant performance and throughput gains are offered by the proposed MIMO precoding technique compared to its conventional counterparts.

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Recent studies suggested that the control of hand movements in catching involves continuous vision-based adjustments. More insight into these adjustments may be gained by examining the effects of occluding different parts of the ball trajectory. Here, we examined the effects of such occlusion on lateral hand movements when catching balls approaching from different directions, with the occlusion conditions presented in blocks or in randomized order. The analyses showed that late occlusion only had an effect during the blocked presentation, and early occlusion only during the randomized presentation. During the randomized presentation movement biases were more leftward if the preceding trial was an early occlusion trial. The effect of early occlusion during the randomized presentation suggests that the observed leftward movement bias relates to the rightward visual acceleration inherent to the ball trajectories used, while its absence during the blocked presentation seems to reflect trial-by-trial adaptations in the visuomotor gain, reminiscent of dynamic gain control in the smooth pursuit system. The movement biases during the late occlusion block were interpreted in terms of an incomplete motion extrapolation--a reduction of the velocity gain--caused by the fact that participants never saw the to-be-extrapolated part of the ball trajectory. These results underscore that continuous movement adjustments for catching do not only depend on visual information, but also on visuomotor adaptations based on non-visual information.

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Bridge structures are continuously subject to degradation due to the environment, ageing and excess loading. Periodic monitoring of bridges is therefore a key part of any maintenance strategy as it can give early warning if a bridge becomes unsafe. This article investigates an alternative method for the monitoring of bridge dynamic behaviour: a truck-trailer vehicle system, with accelerometers fitted to the axles of the trailer. The method aims to detect changes in the damping of a bridge, which may indicate the existence of damage. A simplified vehicle-bridge interaction model is used in theoretical simulations to assess the effectiveness of the method in detecting those changes. The influence of road profile roughness on the vehicle vibration is overcome by recording accelerations from both axles of a trailer and then analysing the spectra of the difference in the accelerations between the two axles. The effectiveness of the approach in detecting damage simulated as a loss in stiffness is also investigated. In addition, the sensitivity of the approach to the vehicle speed, road roughness class, bridge span length, changes in the equal axle properties and noise is investigated.

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In this paper, we propose a novel visual tracking framework, based on a decision-theoretic online learning algorithm namely NormalHedge. To make NormalHedge more robust against noise, we propose an adaptive NormalHedge algorithm, which exploits the historic information of each expert to perform more accurate prediction than the standard NormalHedge. Technically, we use a set of weighted experts to predict the state of the target to be tracked over time. The weight of each expert is online learned by pushing the cumulative regret of the learner towards that of the expert. Our simulation experiments demonstrate the effectiveness of the proposed adaptive NormalHedge, compared to the standard NormalHedge method. Furthermore, the experimental results of several challenging video sequences show that the proposed tracking method outperforms several state-of-the-art methods.

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Purpose Previously, it has been reported that molecular mobility determines the rate of molecular approach to crystal surfaces, while entropy relates to the probability of that approaching molecule having the desirable configuration for further growth of the existing crystal; and the free energy dictates the probability of that molecule not returning to the liquid phase1. If we plot the crystal growth rate and viscosity of a supercooled liquid in a log-log format, the relationship between the two is linear, indicating the influence viscosity has upon crystal growth rate. However, such approximation has been derived from pure drug compounds and it is apparent that further understanding of crystallization from drug-polymer solid dispersion is required in order to stabilise drugs embedded within amorphous polymeric solid dispersions. Methods Mixtures of felodipine and polymer (HPMCAS-HF, PVPK15 and Soluplus®) at specified compositions were prepared using a Restch MM200 ball mill. To examine crystal growth within amorphous solid dispersions, samples were prepared by melting 5-10 mg of ball milled mixture at 150°C for 3-5 minutes on a glass slip pre-cleaned with methanol and acetone. All prepared samples were confirmed to be crystal free by visual observation using a polarised light microscope (Olympus BX50). Prepared samples were stored at 0% RH (P2O5), inside desiccators, maintained in ovens at 80°C. For the dynamic viscosity measurement, approximately 100-200mg ball milled mixture was heated on the base plate of a rotational rheometer at 150°C for 5 minutes and the top plate was lowered to a defined gap to form a good contact with the material. The sandwiched amorphous material was heated to 80°C and the viscosity was measured. Results The equation was used to probe the correlation of viscosity to crystal growth rate. In comparison to the value of xi in log-log equation reported from pure drug compound, a value of 1.63 was obtained for FD-polymer solid dispersions irrespective of the polymer involved. &#8733 Conclusion The high xi value suggests stronger viscosity dependence may exist for amorphous FD once incorporated with amorphous polymer.