859 resultados para Joint attention
Resumo:
We investigated whether it is possible to control the temporal window of attention used to rapidly integrate visual information. To study the underlying neural mechanisms, we recorded ERPs in an attentional blink task, known to elicit Lag-1 sparing. Lag-1 sparing fosters joint integration of the two targets, evidenced by increased order errors. Short versus long integration windows were induced by showing participants mostly fast or slow stimuli. Participants expecting slow speed used a longer integration window, increasing joint integration. Difference waves showed an early (200 ms post-T2) negative and a late positive modulation (390 ms) in the fast group, but not in the slow group. The modulations suggest the creation of a separate event for T2, which is not needed in the slow group, where targets were often jointly integrated. This suggests that attention can be guided by global expectations of presentation speed within tens of milliseconds.
Resumo:
This paper proposes a new iterative algorithm for OFDM joint data detection and phase noise (PHN) cancellation based on minimum mean square prediction error. We particularly highlight the problem of "overfitting" such that the iterative approach may converge to a trivial solution. Although it is essential for this joint approach, the overfitting problem was relatively less studied in existing algorithms. In this paper, specifically, we apply a hard decision procedure at every iterative step to overcome the overfitting. Moreover, compared with existing algorithms, a more accurate Pade approximation is used to represent the phase noise, and finally a more robust and compact fast process based on Givens rotation is proposed to reduce the complexity to a practical level. Numerical simulations are also given to verify the proposed algorithm.
Resumo:
Improving admittance of robotic joints is the key issue for making rehabilitation robots safe. This paper describes a design of Redundant Drive Joint (RD-Joint) which allows greater flexibility in the design of robotic mechanisms. The design strategy of the RD-Joint employs a systematic approach which consists of 1) adopting a redundant joint mechanism with internal kinematical redundancy to reduce effective joint inertia, and 2) adopting an adjustable admittance mechanism with a novel Cross link Reduction Mechanism and mechanical springs and dampers as a passive second actuator. First, the basic concepts used to construct the redundant drive joint mechanism are explained, in particular the method that allows a reduction in effective inertia at the output joint. The basic structure of the RD-Joint is introduced based on the idea of reduced inertia along with a method to include effective stiffness and damping. Then, the basic design of the adjustable admittance mechanism is described. Finally, a prototype of RD-joint is described and its expected characteristics are discussed.
Resumo:
This paper describes a proposed admittance enhanced redundant joint mechanism (AERJM) which allows greater flexibility in the design of robotic joints. First, the basic concept of a redundant joint mechanism that reduces joint inertia is explained. Second, the AERJM structure is discussed. AERJM consists of a redundancy introducing mechanism (RIM), the adjustable admittance mechanism (AAM) and an admittance enhancing actuator. The working principles of the AERJM concept are analysed. The design and a working prototype, consisting of a variable reduction mechanism, along with a spring and a damper with constant coefficients, are described.
OFDM joint data detection and phase noise cancellation based on minimum mean square prediction error
Resumo:
This paper proposes a new iterative algorithm for orthogonal frequency division multiplexing (OFDM) joint data detection and phase noise (PHN) cancellation based on minimum mean square prediction error. We particularly highlight the relatively less studied problem of "overfitting" such that the iterative approach may converge to a trivial solution. Specifically, we apply a hard-decision procedure at every iterative step to overcome the overfitting. Moreover, compared with existing algorithms, a more accurate Pade approximation is used to represent the PHN, and finally a more robust and compact fast process based on Givens rotation is proposed to reduce the complexity to a practical level. Numerical Simulations are also given to verify the proposed algorithm. (C) 2008 Elsevier B.V. All rights reserved.
Resumo:
This correspondence proposes a new algorithm for the OFDM joint data detection and phase noise (PHN) cancellation for constant modulus modulations. We highlight that it is important to address the overfitting problem since this is a major detrimental factor impairing the joint detection process. In order to attack the overfitting problem we propose an iterative approach based on minimum mean square prediction error (MMSPE) subject to the constraint that the estimated data symbols have constant power. The proposed constrained MMSPE algorithm (C-MMSPE) significantly improves the performance of existing approaches with little extra complexity being imposed. Simulation results are also given to verify the proposed algorithm.
Resumo:
Listeners can attend to one of several simultaneous messages by tracking one speaker’s voice characteristics. Using differences in the location of sounds in a room, we ask how well cues arising from spatial position compete with these characteristics. Listeners decided which of two simultaneous target words belonged in an attended “context” phrase when it was played simultaneously with a different “distracter” context. Talker difference was in competition with position difference, so the response indicates which cue‐type the listener was tracking. Spatial position was found to override talker difference in dichotic conditions when the talkers are similar (male). The salience of cues associated with differences in sounds, bearings decreased with distance between listener and sources. These cues are more effective binaurally. However, there appear to be other cues that increase in salience with distance between sounds. This increase is more prominent in diotic conditions, indicating that these cues are largely monaural. Distances between spectra calculated using a gammatone filterbank (with ERB‐spaced CFs) of the room’s impulse responses at different locations were computed, and comparison with listeners’ responses suggested some slight monaural loudness cues, but also monaural “timbre” cues arising from the temporal‐ and spectral‐envelope differences in the speech from different locations.
Resumo:
Knowledge about the functional status of the frontal cortex in infancy is limited. This study investigated the effects of polymorphisms in four dopamine system genes on performance in a task developed to assess such functioning, the Freeze-Frame task, at 9 months of age. Polymorphisms in the catechol-O-methyltransferase (COMT) and the dopamine D4 receptor (DRD4) genes are likely to impact directly on the functioning of the frontal cortex, whereas polymorphisms in the dopamine D2 receptor (DRD2) and dopamine transporter (DAT1) genes might influence frontal cortex functioning indirectly via strong frontostriatal connections. A significant effect of the COMT valine158methionine (Val158Met) polymorphism was found. Infants with the Met/Met genotype were significantly less distractible than infants with the Val/Val genotype in Freeze-Frame trials presenting an engaging central stimulus. In addition, there was an interaction with the DAT1 3′ variable number of tandem repeats polymorphism; the COMT effect was present only in infants who did not have two copies of the DAT1 10-repeat allele. These findings indicate that dopaminergic polymorphisms affect selective aspects of attention as early as infancy and further validate the Freeze-Frame task as a frontal cortex task.
Resumo:
Obstacles considerably influence boundary layer processes. Their influences have been included in mesoscale models (MeM) for a long time. Methods used to parameterise obstacle effects in a MeM are summarised in this paper using results of the mesoscale model METRAS as examples. Besides the parameterisation of obstacle influences it is also possible to use a joint modelling approach to describe obstacle induced and mesoscale changes. Three different methods may be used for joint modelling approaches: The first method is a time-slice approach, where steady basic state profiles are used in an obstacle resolving microscale model (MiM, example model MITRAS) and diurnal cycles are derived by joining steady-state MITRAS results. The second joint modelling approach is one-way nesting, where the MeM results are used to initialise the MiM and to drive the boundary values of the MiM dependent on time. The third joint modelling approach is to apply multi-scale models or two-way nesting approaches, which include feedbacks from the MiM to the MeM. The advantages and disadvantages of the different approaches and remaining problems with joint Reynolds-averaged Navier–Stokes modelling approaches are summarised in the paper.