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To summarize so far, these data indicate the extensive insights that might be available when studying movement models under the enriched ecological constraints of sport Degenerate brains and indeterminate behavior support functioning in complex, dynamically changing environments There is a need to examine processes of perception and action under dynamic task constraints to understand how people actively explore information to guide functional behaviors Most important, individual and environmental constraints should be explicitly considered in studies of movement coordination and control The constraints-based framework signals the need to carefully distinguish variability in movement organization, a healthy sign of adaptive behavior in indeterminate, biological movement systems, from variability in movement output, which is less functional (Davids et al, 2006) The latter is often caused by the use of task constraints that are unrepresentative, as data reported from studies of hitting actions have shown.

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wavemeter to characterize a source in 256 wavelength bands with seven or fewer measurements. The source in this case is a slit or pinhole; the goal is to identify the wavelength of the source in logd N measurements. The collimator and frontend grating map the source onto the spectral encoding mask such that each color channel occupies a different transverse column; for instance, if the source power spectrum is S(l), then the power spectrum illuminating the mask is f (x, y) S(x al). Section 9.2 describes how a dispersive spectrograph implements this transformation. For the present purposes it is suf cient to note that if the mask transmission t(x, y) is described by one of the codes of Fig. 7.21, then the spectral density on the plane immediately after the mask can be represented discretely as tij f j , where f j % S(l jD=a) is the signal in the jth spectral channel. Optical components following the mask decollimate the light to focus on an output slit, which in this case is occupied by a detector array distributed along the y axis. The effect of the backend optics is to sum the spectral channels transmitted by the mask along the rows such P that the measured irradiance on the ith detector is gi j tij f j .

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Sports and many apparently frivolous pastimes provide a plethora of tasks that lend themselves to representative design for studying ubiquitous actions such as interceptions They exemplify how a process-oriented, time-continuous approach motivated by the study of adaptive behavior can be achieved in the analysis of complex movement models (Cordo & Gurfinkel, 2004; Sch llhorn, 2003) Sports and physical activities are replete with an extensive range of task constraints to experimentally manipulate, including clothing, equipment, rules, targets, boundaries, surfaces, and the presence of other individuals (Davids, Button, & Bennett, in press) Compelling arguments exist for empirical work to adequately reflect enriched action environments based on a broad range of task constraints (Cordo & Gurfinkel, 2004; Newell, 1991).

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We observe that the numerical results on queueing delay and PDU dropping probability obtained from the analytical model are close to those obtained from simulations. This validates the accuracy of the analytical model. 21.7.2.2 Relative Performances of the Different Subchannel Allocation Algorithms. Figure 21.10 shows typical variations in average transmission rate in the subchannels allocated to the tagged connection for both the optimal and the iterative algorithms. In this case, when the average SNR for the relay connections is 20 dB, we set Tr = 30, and the number of relay connections is one third of the total number of connections. As expected, for both the algorithms the transmission rate decreases as the number of connections increases. The optimal algorithm performs slightly better when the number of connections is relatively small (e.g., 10 15 connections). However, when the number of connections is relatively large (e.g., 16 22 connections), both the algorithms achieve similar transmission rate. In addition, the computational time4 for the optimal algorithm is much larger than that for the iterative

In this section we study linear second-order hyperbolic problems. A model equation with appropriate boundary and initial conditions is formulated in Paragraph 1.4.1. In Paragraph 1.4.2 we derive its weak formulation and present a basic existence and uniqueness result. In Paragraph 1.4.3 we show the link between the second-order hyperbolic equations and first-order hyperbolic systems. 1.4.1 Initial and boundary conditions The notion of hyperbolicity was first introduced in Definition 1 . 1 . Consider the model equation

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