Browsing by Author "YU, SS"

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A NEW THINNING ALGORITHM FOR GRAY-SCALE IMAGES BY THE RELAXATION TECHNIQUE
(1990)
YU, SS
;
TSAI, WH
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資訊工程學系
;
Department of Computer Science
ATTRIBUTED STRING MATCHING WITH MERGING FOR SHAPE-RECOGNITION
(1985)
TSAI, WH
;
YU, SS
;
資訊工程學系
;
Department of Computer Science
EXCHANGE INTERACTION IN DILUTED MAGNETIC SEMICONDUCTORS - CRYSTAL-STRUCTURE-INDUCED ANISOTROPY
(1995-08-15)
YU, SS
;
LEE, VC
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光電工程研究所
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Institute of EO Enginerring
In this paper, we employ the model developed by Larson et al. to calculate the exchange interaction between magnetic ions in diluted magnetic semiconductors in a method that incorporates explicitly the intrinsic symmetry of the host crystals. We find that the symmetry of the wave function, and thus the interaction matrix element, could induce strong directional dependence of the exchange interaction despite the fact that superexchange is mediated via virtual excitations near the center of the Brillouin zone, where the band energy is essentially isotropic.
GENERAL QUANTUM-THEORY OF NONLINEAR OPTICAL-PULSE PROPAGATION
(1995-01-01)
LAI, YC
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YU, SS
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光電工程研究所
;
Institute of EO Enginerring
HOW QUICKLY SELF-RAMAN EFFECTS AND 3RD-ORDER DISPERSION DESTROY SQUEEZING
(1994)
LAI, YC
;
YU, SS
;
光電工程學系
;
Department of Photonics
RELAXATION BY THE HOPFIELD NEURAL NETWORK
(1992-02-01)
YU, SS
;
TSAI, WH
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資訊工程學系
;
Department of Computer Science
The relaxation process is a useful technique for using contextual information to reduce local ambiguity and achieve global consistency in various applications. It is basically a parallel execution model, adjusting the confidence measures of involved entities based on interrelated hypotheses and confidence measures. On the other hand, the neural network is a computational model with massively parallel execution capability. The output of each neuron depends mainly on the information provided by other neurons. Therefore, there exist certain common properties in the relaxation process and the neural network technique. A mapping method that makes the Hopfield neural network perform the relaxation process is proposed. By this method, the neural network technology can be easily adapted to solve the many problems which have already been solved by the relaxation process. An advantage of this is that the relaxation process can be performed in real time since the Hopfield network can be implemented by conventional analog circuits. Experimental results are given to demonstrate the feasibility of the proposed method by performing the image thresholding operation on the proposed neural network.
SPATIOTEMPORAL SOLITARY PULSES IN GRADED-INDEX MATERIALS WITH KERR NONLINEARITY
(1995-08-15)
YU, SS
;
CHIEN, CH
;
LAI, YC
;
WANG, YP
;
光電工程學系
We analyze spatio-temporal pulse propagation in graded-index Kerr materials with the variational method, and find that if the path of propagation provides negative group-velocity dispersion, stable solitary pulses exist for pulse energy smaller than a critical value, Spatial and temporal degrees of freedom cannot be analyzed separately due to their coupling through the Kerr nonlinarity. Our unified analysis not only elucidates the hidden coupling, but also clarifies relations between parameters of the solitary pulse. The analysis is verified by direct numerical simulation of the paraxial wave equation.