88 resultados para STOP SIGNAL

em Deakin Research Online - Australia


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Impulsivity is considered a core feature of problem gambling, however, self-reported impulsivity and inhibitory control may reflect disparate constructs. We examined self-reported impulsivity and inhibitory control in 39 treatment-seeking problem gamblers and 41 matched controls using a range of self-report questionnaires and laboratory inhibitory control tasks. We also investigated differences between treatment-seeking problem gamblers who prefer strategic (e.g., sports-betting) and non-strategic (e.g., electronic gaming machines) gambling activities. Treatment-seeking problem gamblers demonstrated elevated self-reported impulsivity, more go errors on the Stop Signal Task and a lower gap score on the Random Number Generation task than matched controls. However, overall we did not find strong evidence that treatment-seeking problem gamblers are more impulsive on laboratory inhibitory control measures. Furthermore, strategic and non-strategic problem gamblers did not differ from their respective controls on either self-reported impulsivity questionnaires or laboratory inhibitory control measures. Contrary to expectations, our results suggest that inhibitory dyscontrol may not be a key component for some treatment-seeking problem gamblers.

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Twomultidimensional HPLC separations of an Australian red wine are presented, >70% of the available separation space was used. A porous graphitic carbon (PGC) stationary phase was used as the first dimension in both separations with both RP core–shell and hydrophilic interaction chromatography fully porous columns used separately in the second dimension. To overcome peak analysis problems caused by signal noise and low detection limits, the data were pre-processed with penalised least-squares smoothing. The PGC × RP combination separated 85 peaks with a spreading angle of 71 and the PGC × hydrophilic interaction chromatography separated 207 peaks with a spreading angle of 80. Both 2D-HPLC steps were completed in 76 min using a comprehensive stop-and-go approach. A smoothing step was added to peak-picking processes and was able to greatly reduce the number of false peaks present due to noise in the chromatograms. The required thresholds were not able to ignore the noise because of the small magnitude of the peaks; 1874 peaks were located in the non-smoothed PGC × RP separation that reduced to 227 peaks after smoothing was included.

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This paper presents a new approach to separate colored stationary signals mixed by convolutive channels. A cost function is proposed by employing linear constraint to the demixing vectors. The linear constraint is shown to be sufficient for avoiding trivial solution. The minimization of the cost function is performed using the Lagrangian method. Simulation results demonstrate the performance of the algorithm.


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This paper presents a new approach to separate colored signals mixed by FIR (finite impulse response) and MIMO (multiple-input multiple-output) channels. A cost function is proposed by employing linear constrainit to the de mixing vectors. The linear constraint is shown to be sufficient for avoiding trivial solution. The minimization of the cost function is performed using the Lagrangian method. Simulation results demonstrate the performance of the algorithm.

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We address the problem of adaptive blind source separation (BSS) from instantaneous multi-input multi-output (MIMO) channels. It is known that the constant modulus (CM) criterion can be used to extract unknown source signals. However, the existing CM based algorithms normally extract the source signals in a serial manner. Consequently, the accuracy in extracting each source signal, except for the first one, depends on the accuracy of previous source extraction. This estimation error propagation (accumulation) causes severe performance degradation. In this paper, we propose a new adaptive separation algorithm that can separate all source signals simultaneously by directly updating the separation matrix. The superior performance of the new algorithm is demonstrated by simulation examples

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In this paper, we propose a new adaptive algorithm for the blind equalization of an FIR (finite impulse response) channel excited by an M-ary phase shift keying (MPSK) signal. Different from the conventional constant modulus algorithm (CMA), which exploits the amplitude information of the input signal, the proposed algorithm exploits the full constellation information of the input signal. Theoretical analysis shows that the new algorithm has less mean square error (MSE), namely better equalization performance, in steady state than the CMA. Numerical simulations show the effectiveness of the new algorithm

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We address the problem of adaptive blind source separation (BSS) from instantaneous multi-input multi-output (MIMO) channels. In this paper, we propose a new constant modulus (CM)-based algorithm which employ nonlinear function as the de-correlation term. Moreover, it is shown by theoretical analysis that the proposed algorithm has less mean square error (MSE), i.e., better separation performance, in steady state than the cross-correlation and constant modulus algorithm (CC-CMA). Numerical simulations show the effectiveness of the proposed result.

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This correspondence first shows that the global convergence analysis of the method proposed in the above paper is incomplete. Then we provide a counter example to show that the sufficient condition for global convergence is incorrect.

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We consider the problem of blind equalization of a finite impulse response and single-input multiple-output system driven by an M-ary phase-shift-keying signal. The existing single-mode algorithms for this problem include the constant modulus algorithm (CMA) and the multimodulus algorithm (MMA). It has been shown that the MMA outperforms the CMA when the input signal has no more than four constellation points, i.e., Mles4. In this brief, we present a new adaptive equalization algorithm that jointly exploits the amplitude and phase information of the input signal. Theoretical analysis shows that the proposed algorithm has less mean square error, i.e., better equalization performance, at steady state than the CMA regardless of the value of M. The superior performance of our algorithm to the CMA and the MMA is validated by simulation examples

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A series of digital frequency filters (DFFs) were designed to screen diverse noises and the spectrographic analysis was conducted to isolate complex boundary reflection, which obscures the damage-induced signals. The scale-averaged wavelet power (SAP) technique was applied to enhance
the measurement accuracy of Time of Flight (TOF). As an example, the propagation characteristics of elastic wave in a structural beam of square cross-section were analyzed using such an approach and verified experimentally and numerically, with the consideration of the complicated wave scatter caused by the non-ignorable section dimensions.

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I remember when I was young, an advertising billboard poster proudly proclaimed: Coke Adds Life. An anti-advertising group were always at the ready to delete a D and graffiti a cross over the F to create the more believable slogan: Coke Ads Lie. Take the ‘f’ out of Life and we are left with a lie. This ad-busting was not only a reminder that Coke ads lie, but that all advertisements lie.