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Search Results: 1 - 10 of 41580 matches for " Liang Chang "
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Kitaev models based on unitary quantum groupoids
Liang Chang
Mathematics , 2013, DOI: 10.1063/1.4869326
Abstract: We establish a generalization of Kitaev models based on unitary quantum groupoids. In particular, when inputting a Kitaev-Kong quantum groupoid $H_\mathcal{C}$, we show that the ground state manifold of the generalized model is canonical isomorphic to that of the Levin-Wen model based on a unitary fusion category $\mathcal{C}$. Therefore the generalized Kitaev models provide realizations of the target space of the Turaev-Viro TQFT based on $\mathcal{C}$.
$\bf{Z_{Kup}=|Z_{Henn}|^2}$ for Semisimple Hopf Algebras
Liang Chang
Mathematics , 2015,
Abstract: Hennings and Kuperberg defined quantum invariants $Z_{Henn}$ and $Z_{Kup}$ of closed oriented $3$-manifolds based on certain Hopf algebras, respectively. We prove that $Z_{Kup}=|Z_{Henn}|^2$ for any closed oriented $3$-manifold when both invariants are based on finite dimensional semisimple factorizable Hopf algebras.
The Symbolic OBDD Algorithm for Finding Optimal Semi-matching in Bipartite Graphs  [PDF]
Tianlong Gu, Liang Chang, Zhoubo Xu
Communications and Network (CN) , 2011, DOI: 10.4236/cn.2011.32009
Abstract: The optimal semi-matching problem is one relaxing form of the maximum cardinality matching problems in bipartite graphs, and finds its applications in load balancing. Ordered binary decision diagram (OBDD) is a canonical form to represent and manipulate Boolean functions efficiently. OBDD-based symbolic algorithms appear to give improved results for large-scale combinatorial optimization problems by searching nodes and edges implicitly. We present novel symbolic OBDD formulation and algorithm for the optimal semi-matching problem in bipartite graphs. The symbolic algorithm is initialized by heuristic searching initial matching and then iterates through generating residual network, building layered network, backward traversing node-disjoint augmenting paths, and updating semi-matching. It does not require explicit enumeration of the nodes and edges, and therefore can handle many complex executions in each step. Our simulations show that symbolic algorithm has better performance, especially on dense and large graphs.
A Novel Symbolic Algorithm for Maximum Weighted Matching in Bipartite Graphs  [PDF]
Tianlong Gu, Liang Chang, Zhoubo Xu
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2011, DOI: 10.4236/ijcns.2011.42014
Abstract: The maximum weighted matching problem in bipartite graphs is one of the classic combinatorial optimization problems, and arises in many different applications. Ordered binary decision diagram (OBDD) or algebraic decision diagram (ADD) or variants thereof provides canonical forms to represent and manipulate Boolean functions and pseudo-Boolean functions efficiently. ADD and OBDD-based symbolic algorithms give improved results for large-scale combinatorial optimization problems by searching nodes and edges implicitly. We present novel symbolic ADD formulation and algorithm for maximum weighted matching in bipartite graphs. The symbolic algorithm implements the Hungarian algorithm in the context of ADD and OBDD formulation and manipulations. It begins by setting feasible labelings of nodes and then iterates through a sequence of phases. Each phase is divided into two stages. The first stage is building equality bipartite graphs, and the second one is finding maximum cardinality matching in equality bipartite graph. The second stage iterates through the following steps: greedily searching initial matching, building layered network, backward traversing node-disjoint augmenting paths, updating cardinality matching and building residual network. The symbolic algorithm does not require explicit enumeration of the nodes and edges, and therefore can handle many complex executions in each step. Simulation experiments indicate that symbolic algorithm is competitive with traditional algorithms.
Asymmetric Impact of Informed Trading Activity on Stock Return Volatility  [PDF]
Alex YiHou Huang, Ching-Liang Chang
Theoretical Economics Letters (TEL) , 2014, DOI: 10.4236/tel.2014.47071
Abstract:

Prior research has shown that informed trading activity decreases the stock return volatility because trading causes stock prices to converge to fundamentals. On the contrary to existing studies, this paper documents the empirical asymmetric relation between informed trading activity and volatility. Stocks with relatively less private information are associated with lower participation of informed traders, and an increase in informed trading activity for those stocks would increase their return volatility. This finding is robust under both pooled and Fama-MacBeth regressions with various constructions for the realized volatility and probability of informed trading measurements.

The Effect of Intermittent Signal on the Performance of Code Tracking Loop in GNSS Receivers
Chung-Liang Chang
Journal of Electrical and Computer Engineering , 2011, DOI: 10.1155/2011/418032
Abstract: This paper analyzes the code tracking performance in the presence of signal blanking in Global Navigation Satellite System (GNSS). The blanking effect is usually caused by buildings that obscure the signal in either a periodic or random manner. In some cases, ideal blanking is used to remove random or periodic interference. Nevertheless, the effect of temporary discontinuity of signal often leads to the tracking and position error. To analyze this problem, three types of blanking model are considered: no blanking, periodic blanking, and random blanking of the signals input into the code tracking loop. The mean time to lose lock (MTLL) is to assess the performance of code tracking system under signal blanking. Finally, the effect of steady-state tracking errors on the performance of tracking loop resulting from blanking environment is also discussed.
網路虛擬實境與情境學習的整合應用 Application of Internet Virtual Reality and Situated Learning
Chaoyun Liang,Hong Chang
Journal of Educational Media & Library Sciences , 1998,
Abstract: 無 This article introduces an ongoing project that integrates Internet virtual reality techniques with situated learning theory, and tries to find out the synthesized application. Based upon the synthesis, the authors develop a set of learning materials that can provide an environment for multiple-user participation and real-time interaction on Internet. A detailed description of the instructional design process is offered, followed by the suggestions for future research in this promising area.
Improving patient safety- a medical student’s perspective
Zhen Chang Liang
International Journal of Students' Research , 2011, DOI: 10.5549/ijsr.1.1.1-3
Abstract:
Self-Tuning Synthesis Filter against Mutual Coupling and Interferences for GNSS and Its Implementation on Embedded Board
Chung-Liang Chang
EURASIP Journal on Advances in Signal Processing , 2010, DOI: 10.1155/2010/123625
Abstract: Traditional spatial-temporal adaptive signal processing techniques are often applied to conduct narrowband and wideband interferences. However, its mitigation performance degrades greatly due to mutual coupling. To solve this problem, this paper aims to utilize a spatial-temporal self-tuning synthesis filter capable of mutual coupling compensation and interference mitigation. The spatial filter and temporal filter are to compensate for the effect of mutual coupling and interference mitigation, respectively. Self-tuning mechanism is to adopt least square (LS) and minimum variable distortionless response- (MVDR-) based method to adjust spatial and temporal weights of antenna array. The experiment platform is established by the embedded development board. Simulation and experiment results demonstrate that the proposed method can effectively compensate for mutual coupling, mitigate the cochannel interference up to 30 dB, and enhance the acquisition performance of receivers in global navigation satellite system (GNSS).
Self-Tuning Synthesis Filter against Mutual Coupling and Interferences for GNSS and Its Implementation on Embedded Board
Chang Chung-Liang
EURASIP Journal on Advances in Signal Processing , 2010,
Abstract: Traditional spatial-temporal adaptive signal processing techniques are often applied to conduct narrowband and wideband interferences. However, its mitigation performance degrades greatly due to mutual coupling. To solve this problem, this paper aims to utilize a spatial-temporal self-tuning synthesis filter capable of mutual coupling compensation and interference mitigation. The spatial filter and temporal filter are to compensate for the effect of mutual coupling and interference mitigation, respectively. Self-tuning mechanism is to adopt least square (LS) and minimum variable distortionless response- (MVDR-) based method to adjust spatial and temporal weights of antenna array. The experiment platform is established by the embedded development board. Simulation and experiment results demonstrate that the proposed method can effectively compensate for mutual coupling, mitigate the cochannel interference up to 30 dB, and enhance the acquisition performance of receivers in global navigation satellite system (GNSS).
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