Browsing by Author "Tsai, I-Ling"

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Kondo effect in a side-coupled double quantum dot system embedded in a mesoscopic ring
(2010-05-15)
Tsai, I-Ling
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Chung, Chung-Hou
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電子物理學系
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Department of Electrophysics
We study finite-size effect of the Kondo screening cloud in a double quantum dot setup via a large-N slave-boson mean-field theory. In this setup, one of the dots is embedded in a close metallic ring with a finite size L and the other dot is side coupled to the embedded dot via an antiferromagnetic spin-spin-exchange coupling with a strength K. The antiferromagnetic coupling favors local spin-singlet state and suppresses the Kondo screening. The mean-field phase diagram as a function of 1/L and K shows a crossover to the local spin-singlet ground state from the Kondo phase to occur at K < K(c) (L = 4n, 4n + 1, 4n + 3) and at K > K(c) (L = 4n + 2). The effective Kondo temperature T(k) (proptotional to inverse of the Kondo screening cloud size) shows the Kosterlitz-Thouless (KT) scaling at finite sizes for L = 4n, 4n + 2, indicating quantum transition of the KT type between the Kondo screened phase for K <= K(c) and a local spin-singlet phase for K >= K(c) in the thermodynamic limit with Kc being the critical value. The local density of states on the embedded quantum dot and the persistent current at finite sizes with different values of K are calculated in the crossover region.
Real-Time Embedded EEG-Based Brain-Computer Interface
(2009)
Ko, Li-Wei
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Tsai, I-Ling
;
Yang, Fu-Shu
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Chung, Jen-Feng
;
Lu, Shao-Wei
Online artifact rejection, feature extraction, and pattern recognition are essential to advance the Brain Computer Interface (BCI) technology so as to be practical for real-world applications. The goals of BCI system should be a small size, rugged, lightweight, and have low power consumption to meet the requirements of wearability, portability, and durability. This study proposes and implements a moving-windowed Independent Component Analysis (ICA) on a battery-powered, miniature, embedded BCI. This study also tests the embedded BCI on simulated and real EEG signals. Experimental results indicated that the efficacy of the online ICA decornposition is comparable with that of the offline version of the same algorithm, suggesting the feasibility of ICA for online analysis of EEG in a BCI. To demonstrate the feasibility of the wearable embedded BCI, this study also implements an online spectral analysis to the resultant component activations to continuously estimate subject's task performance in near real time.