974 resultados para Feedback visual


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The Effective Exponential SNR Mapping (EESM) is an indispensable tool for analyzing and simulating next generation orthogonal frequency division multiplexing (OFDM) based wireless systems. It converts the different gains of multiple subchannels, over which a codeword is transmitted, into a single effective flat-fading gain with the same codeword error rate. It facilitates link adaptation by helping each user to compute an accurate channel quality indicator (CQI), which is fed back to the base station to enable downlink rate adaptation and scheduling. However, the highly non-linear nature of EESM makes a performance analysis of adaptation and scheduling difficult; even the probability distribution of EESM is not known in closed-form. This paper shows that EESM can be accurately modeled as a lognormal random variable when the subchannel gains are Rayleigh distributed. The model is also valid when the subchannel gains are correlated in frequency or space. With some simplifying assumptions, the paper then develops a novel analysis of the performance of LTE's two CQI feedback schemes that use EESM to generate CQI. The comprehensive model and analysis quantify the joint effect of several critical components such as scheduler, multiple antenna mode, CQI feedback scheme, and EESM-based feedback averaging on the overall system throughput.

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Frequency-domain scheduling and rate adaptation enable next-generation orthogonal frequency-division multiple access (OFDMA) cellular systems such as Long-Term Evolution (LTE) to achieve significantly higher spectral efficiencies. LTE uses a pragmatic combination of several techniques to reduce the channel-state feedback that is required by a frequency-domain scheduler. In the subband-level feedback and user-selected subband feedback schemes specified in LTE, the user reduces feedback by reporting only the channel quality that is averaged over groups of resource blocks called subbands. This approach leads to an occasional incorrect determination of rate by the scheduler for some resource blocks. In this paper, we develop closed-form expressions for the throughput achieved by the feedback schemes of LTE. The analysis quantifies the joint effects of three critical components on the overall system throughput-scheduler, multiple-antenna mode, and the feedback scheme-and brings out its dependence on system parameters such as the number of resource blocks per subband and the rate adaptation thresholds. The effect of the coarse subband-level frequency granularity of feedback is captured. The analysis provides an independent theoretical reference and a quick system parameter optimization tool to an LTE system designer and theoretically helps in understanding the behavior of OFDMA feedback reduction techniques when operated under practical system constraints.

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The problem of developing L2-stability criteria for feedback systems with a single time-varying gain, which impose average variation constraints on the gain is treated. A unified approach is presented which facilitates the development of such average variation criteria for both linear and nonlinear systems. The stability criteria derived here are shown to be more general than the existing results.

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Frequency-domain scheduling and rate adaptation enable next generation wireless cellular systems such as Long Term Evolution (LTE) to achieve significantly higher downlink throughput. LTE assigns subcarriers in chunks, called physical resource blocks (PRBs), to users to reduce control signaling overhead. To reduce the enormous feedback overhead, the channel quality indicator (CQI) report that is used to feed back channel state information is averaged over a subband, which, in turn, is a group of multiple PRBs. In this paper, we develop closed-form expressions for the throughput achieved by the subband-level CQI feedback mechanism of LTE. We show that the coarse frequency resolution of the CQI incurs a significant loss in throughput and limits the multi-user gains achievable by the system. We then show that the performance can be improved by means of an offset mechanism that effectively makes the users more conservative in reporting their CQI.

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Evaluation of the probability of error in decision feedback equalizers is difficult due to the presence of a hard limiter in the feedback path. This paper derives the upper and lower bounds on the probability of a single error and multiple error patterns. The bounds are fairly tight. The bounds can also be used to select proper tap gains of the equalizer.

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We present global multidimensional numerical simulations of the plasma that pervades the dark matter haloes of clusters, groups and massive galaxies (the intracluster medium; ICM). Observations of clusters and groups imply that such haloes are roughly in global thermal equilibrium, with heating balancing cooling when averaged over sufficiently long time- and length-scales; the ICM is, however, very likely to be locally thermally unstable. Using simple observationally motivated heating prescriptions, we show that local thermal instability (TI) can produce a multiphase medium with similar to 104 K cold filaments condensing out of the hot ICM only when the ratio of the TI time-scale in the hot plasma (tTI) to the free-fall time-scale (tff) satisfies tTI/tff? 10. This criterion quantitatively explains why cold gas and star formation are preferentially observed in low-entropy clusters and groups. In addition, the interplay among heating, cooling and TI reduces the net cooling rate and the mass accretion rate at small radii by factors of similar to 100 relative to cooling-flow models. This dramatic reduction is in line with observations. The feedback efficiency required to prevent a cooling flow is similar to 10-3 for clusters and decreases for lower mass haloes; supernova heating may be energetically sufficient to balance cooling in galactic haloes. We further argue that the ICM self-adjusts so that tTI/tff? 10 at all radii. When this criterion is not satisfied, cold filaments condense out of the hot phase and reduce the density of the ICM. These cold filaments can power the black hole and/or stellar feedback required for global thermal balance, which drives tTI/tff? 10. In comparison to clusters, groups have central cores with lower densities and larger radii. This can account for the deviations from self-similarity in the X-ray luminositytemperature () relation. The high-velocity clouds observed in the Galactic halo can be due to local TI producing multiphase gas close to the virial radius if the density of the hot plasma in the Galactic halo is >rsim 10-5 cm-3 at large radii.

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Multiwavelength data indicate that the X-ray-emitting plasma in the cores of galaxy clusters is not cooling catastrophically. To a large extent, cooling is offset by heating due to active galactic nuclei (AGNs) via jets. The cool-core clusters, with cooler/denser plasmas, show multiphase gas and signs of some cooling in their cores. These observations suggest that the cool core is locally thermally unstable while maintaining global thermal equilibrium. Using high-resolution, three-dimensional simulations we study the formation of multiphase gas in cluster cores heated by collimated bipolar AGN jets. Our key conclusion is that spatially extended multiphase filaments form only when the instantaneous ratio of the thermal instability and free-fall timescales (t(TI)/t(ff)) falls below a critical threshold of approximate to 10. When this happens, dense cold gas decouples from the hot intracluster medium (ICM) phase and generates inhomogeneous and spatially extended Ha filaments. These cold gas clumps and filaments ``rain'' down onto the central regions of the core, forming a cold rotating torus and in part feeding the supermassive black hole. Consequently, the self-regulated feedback enhances AGN heating and the core returns to a higher entropy level with t(TI)/t(ff) > 10. Eventually, the core reaches quasi-stable global thermal equilibrium, and cold filaments condense out of the hot ICM whenever t(TI)/t(ff) less than or similar to 10. This occurs despite the fact that the energy from AGN jets is supplied to the core in a highly anisotropic fashion. The effective spatial redistribution of heat is enabled in part by the turbulent motions in the wake of freely falling cold filaments. Increased AGN activity can locally reverse the cold gas flow, launching cold filamentary gas away from the cluster center. Our criterion for the condensation of spatially extended cold gas is in agreement with observations and previous idealized simulations.

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A new phenanthrene based chemosensor has been synthesized and investigated to act as highly selective fluorescence and visual sensor for Cu2+ ion with very low detection limit of 1.58 nM: this has also been used to image Cu2+ in human cervical HeLa cancer cells. (C) 2012 Elsevier B.V. All rights reserved.

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In a communication system in which K nodes communicate with a central sink node, the following problem of selection often occurs. Each node maintains a preference number called a metric, which is not known to other nodes. The sink node must find the `best' node with the largest metric. The local nature of the metrics requires the selection process to be distributed. Further, the selection needs to be fast in order to increase the fraction of time available for data transmission using the selected node and to handle time-varying environments. While several selection schemes have been proposed in the literature, each has its own shortcomings. We propose a novel, distributed selection scheme that generalizes the best features of the timer scheme, which requires minimal feedback but does not guarantee successful selection, and the splitting scheme, which requires more feedback but guarantees successful selection. The proposed scheme introduces several new ideas into the design of the timer and splitting schemes. It explicitly accounts for feedback overheads and guarantees selection of the best node. We analyze and optimize the performance of the scheme and show that it is scalable, reliable, and fast. We also present new insights about the optimal timer scheme.

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Our everyday visual experience frequently involves searching for objects in clutter. Why are some searches easy and others hard? It is generally believed that the time taken to find a target increases as it becomes similar to its surrounding distractors. Here, I show that while this is qualitatively true, the exact relationship is in fact not linear. In a simple search experiment, when subjects searched for a bar differing in orientation from its distractors, search time was inversely proportional to the angular difference in orientation. Thus, rather than taking search reaction time (RT) to be a measure of target-distractor similarity, we can literally turn search time on its head (i.e. take its reciprocal 1/RT) to obtain a measure of search dissimilarity that varies linearly over a large range of target-distractor differences. I show that this dissimilarity measure has the properties of a distance metric, and report two interesting insights come from this measure: First, for a large number of searches, search asymmetries are relatively rare and when they do occur, differ by a fixed distance. Second, search distances can be used to elucidate object representations that underlie search - for example, these representations are roughly invariant to three-dimensional view. Finally, search distance has a straightforward interpretation in the context of accumulator models of search, where it is proportional to the discriminative signal that is integrated to produce a response. This is consistent with recent studies that have linked this distance to neuronal discriminability in visual cortex. Thus, while search time remains the more direct measure of visual search, its reciprocal also has the potential for interesting and novel insights. (C) 2012 Elsevier Ltd. All rights reserved.

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Bhutani N, Ray S, Murthy A. Is saccade averaging determined by visual processing or movement planning? J Neurophysiol 108: 3161-3171, 2012. First published September 26, 2012; doi:10.1152/jn.00344.2012.-Saccadic averaging that causes subjects' gaze to land between the location of two targets when faced with simultaneously or sequentially presented stimuli has been often used as a probe to investigate the nature of computations that transform sensory representations into an oculomotor plan. Since saccadic movements involve at least two processing stages-a visual stage that selects a target and a movement stage that prepares the response-saccade averaging can either occur due to interference in visual processing or movement planning. By having human subjects perform two versions of a saccadic double-step task, in which the stimuli remained the same, but different instructions were provided (REDIRECT gaze to the later-appearing target vs. FOLLOW the sequence of targets in their order of appearance), we tested two alternative hypotheses. If saccade averaging were due to visual processing alone, the pattern of saccade averaging is expected to remain the same across task conditions. However, whereas subjects produced averaged saccades between two targets in the FOLLOW condition, they produced hypometric saccades in the direction of the initial target in the REDIRECT condition, suggesting that the interaction between competing movement plans produces saccade averaging.

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We consider a visual search problem studied by Sripati and Olson where the objective is to identify an oddball image embedded among multiple distractor images as quickly as possible. We model this visual search task as an active sequential hypothesis testing problem (ASHT problem). Chernoff in 1959 proposed a policy in which the expected delay to decision is asymptotically optimal. The asymptotics is under vanishing error probabilities. We first prove a stronger property on the moments of the delay until a decision, under the same asymptotics. Applying the result to the visual search problem, we then propose a ``neuronal metric'' on the measured neuronal responses that captures the discriminability between images. From empirical study we obtain a remarkable correlation (r = 0.90) between the proposed neuronal metric and speed of discrimination between the images. Although this correlation is lower than with the L-1 metric used by Sripati and Olson, this metric has the advantage of being firmly grounded in formal decision theory.

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How do we perform rapid visual categorization?It is widely thought that categorization involves evaluating the similarity of an object to other category items, but the underlying features and similarity relations remain unknown. Here, we hypothesized that categorization performance is based on perceived similarity relations between items within and outside the category. To this end, we measured the categorization performance of human subjects on three diverse visual categories (animals, vehicles, and tools) and across three hierarchical levels (superordinate, basic, and subordinate levels among animals). For the same subjects, we measured their perceived pair-wise similarities between objects using a visual search task. Regardless of category and hierarchical level, we found that the time taken to categorize an object could be predicted using its similarity to members within and outside its category. We were able to account for several classic categorization phenomena, such as (a) the longer times required to reject category membership; (b) the longer times to categorize atypical objects; and (c) differences in performance across tasks and across hierarchical levels. These categorization times were also accounted for by a model that extracts coarse structure from an image. The striking agreement observed between categorization and visual search suggests that these two disparate tasks depend on a shared coarse object representation.