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TIME ESTIMATION AND HAND PREFERENCE
Title
TIME ESTIMATION AND HAND PREFERENCE.
Creator
Rodriguez, Maria, Hancock, Peter, University of Central Florida
Abstract / Description
This work examines the effect of participants' gender and handedness on the perception of short intervals of time. The time estimation task consisted of an empty production procedure with forty trials at each of four intervals of one, three, seven, and twenty seconds. The four target intervals represent a natural logarithmic progression and a series that bracket important temporal thresholds. The order of presentation of those intervals was randomized across participants but yoked across the...
Show moreThis work examines the effect of participants' gender and handedness on the perception of short intervals of time. The time estimation task consisted of an empty production procedure with forty trials at each of four intervals of one, three, seven, and twenty seconds. The four target intervals represent a natural logarithmic progression and a series that bracket important temporal thresholds. The order of presentation of those intervals was randomized across participants but yoked across the sexes in each of the respective dominant hand groups. The two between-subject factors, with two levels each, were sex and handedness. Participants produced forty estimates at each of the required intervals, which was the first within-subject factor, estimated interval being the other. T-tests were conducted on the dependent measures, the time estimates in terms of their variability and their central tendency with respect to the target duration. If handedness plays a significant role in timing, this may indicate differences between hemispheric functioning as a possible causal mechanism. If there is cerebral asymmetry in time perception, namely if one hemisphere is more competent regarding time perception, accuracy in judging duration should be higher for the contralateral hand. The results of the present study indicated that there are no significant differences in performance between right-handed and left-handed participants, or between male and female participants, in the estimation of short intervals of time.
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Date Issued
2005
Identifier
CFE0000768, ucf:46572
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000768
The Power of Quantum Walk: Insights, Implementation, and Applications
Title
The Power of Quantum Walk: Insights, Implementation, and Applications.
Creator
Chiang, Chen-Fu, Wocjan, Pawel, Marinescu, Dan, Dechev, Damian, Mucciolo, Eduardo, University of Central Florida
Abstract / Description
In this thesis, I investigate quantum walks in quantum computing from threeaspects: the insights, the implementation, and the applications. Quantum walks are the quantum analogue of classical random walks. For the insights of quantum walks, I list and explain the required components for quantizing a classical random walk into a quantum walk. The components are, for instance, Markov chains, quantum phase estimation, and quantum spectrum theorem. I then demonstrate how the product of two...
Show moreIn this thesis, I investigate quantum walks in quantum computing from threeaspects: the insights, the implementation, and the applications. Quantum walks are the quantum analogue of classical random walks. For the insights of quantum walks, I list and explain the required components for quantizing a classical random walk into a quantum walk. The components are, for instance, Markov chains, quantum phase estimation, and quantum spectrum theorem. I then demonstrate how the product of two reflections in the walk operator provides a quadratic speed-up, in comparison to the classical counterpart. For the implementation of quantum walks, I show the construction of an efficient circuit for realizing one single step of the quantum walk operator. Furthermore, I devise a more succinct circuit to approximately implement quantum phase estimation with constant precision controlled phase shift operators. From an implementation perspective, efficient circuits are always desirable because the realization of a phase shift operator with high precision would be a costly task and a critical obstacle. For the applications of quantum walks, I apply the quantum walk technique along with other fundamental quantum techniques, such as phase estimation, to solve the partition function problem. However, there might be some scenario in which the speed-up of spectral gap is insignificant. In a situation like that that,I provide an amplitude amplification-based approach to prepare the thermal Gibbs state. Such an approach is useful when the spectral gap is extremely small. Finally, I further investigate and explore the effect of noise (perturbation)on the performance of quantum walks.
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Date Issued
2011
Identifier
CFE0004094, ucf:49148
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004094
Characterization of a Spiking Neuron Model via a Linear Approach
Title
Characterization of a Spiking Neuron Model via a Linear Approach.
Creator
Jabalameli, Amirhossein, Behal, Aman, Hickman, James, Haralambous, Michael, University of Central Florida
Abstract / Description
In the past decade, characterizing spiking neuron models has been extensively researched as anessential issue in computational neuroscience. In this thesis, we examine the estimation problemof two different neuron models. In Chapter 2, We propose a modified Izhikevich model withan adaptive threshold. In our two-stage estimation approach, a linear least squares method anda linear model of the threshold are derived to predict the location of neuronal spikes. However,desired results are not...
Show moreIn the past decade, characterizing spiking neuron models has been extensively researched as anessential issue in computational neuroscience. In this thesis, we examine the estimation problemof two different neuron models. In Chapter 2, We propose a modified Izhikevich model withan adaptive threshold. In our two-stage estimation approach, a linear least squares method anda linear model of the threshold are derived to predict the location of neuronal spikes. However,desired results are not obtained and the predicted model is unsuccessful in duplicating the spikelocations. Chapter 3 is focused on the parameter estimation problem of a multi-timescale adaptivethreshold (MAT) neuronal model. Using the dynamics of a non-resetting leaky integrator equippedwith an adaptive threshold, a constrained iterative linear least squares method is implemented tofit the model to the reference data. Through manipulation of the system dynamics, the thresholdvoltage can be obtained as a realizable model that is linear in the unknown parameters. This linearlyparametrized realizable model is then utilized inside a prediction error based framework to identifythe threshold parameters with the purpose of predicting single neuron precise firing times. Thisestimation scheme is evaluated using both synthetic data obtained from an exact model as well asthe experimental data obtained from in vitro rat somatosensory cortical neurons. Results show theability of this approach to fit the MAT model to different types of reference data.
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Date Issued
2015
Identifier
CFE0005958, ucf:50803
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005958