Browsing by Author "Chen, SM"

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0.13-mu m low-kappa-Cu CMOS logic-based technology for 2.1-Gb high data rate read-channel
(2004-05-01)
Guo, JC
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Lien, WY
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Tsai, TL
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Chen, SM
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Wu, CM
High-performance analog/digital elements have been successfully fabricated bya 0.13-mum low-kappa-Cu logic-based mixed-signal CMOS process in a single chip to enable a 2.1-Gb/s read-channel for hard disk drives that is a record-high data rate supported by fully CMOS solution. The high-performance analog devices demonstrate superior drivability, matching, noise immunity, and reliability by a unique dual-gate oxide module to support the aggressive oxide thickness scaling and maintain promisingly good reliability in all aspects.
A knowledge-based method for fuzzy query processing for document retrieval
(1997-01-01)
Chen, SM
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Hsiao, WH
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Horng, YJ
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交大名義發表
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資訊工程學系
This paper presents a knowledge-based method for processing fuzzy queries and weighted-fuzzy, queries for document retrieval, where fuzzy concept matrices are used for knowledge representation and the elements in a fuzzy concept matrix are represented by trapezoidal fuzzy numbers parameterized by quadruples (a,b,c,d), where 0 less than or equal to a less than or equal to b less than or equal to c less than or equal to d less than or equal to 1. Intelligent retrieval capability and flexible user's queries are consequently provided for.
A new interpolative reasoning method in sparse rule-based systems
(1998-01-01)
Hsiao, WH
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Chen, SM
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Lee, CH
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資訊工程學系
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Department of Computer Science
In [7], Yan et al. analyzed Koczy and Hirota's linear interpolative reasoning method presented in [2,3] and found that the reasoning consequences by their method sometimes become abnormal fuzzy sets. Thus, they pointed out that a new interpolative reasoning method will be needed which can guarantee that the interpolated conclusion will also be triangular-type for a triangular-type observation. In this paper, we extend the works of [2,3,7] to present a new interpolative reasoning method to deal with fuzzy reasoning in sparse rule-based systems. The proposed method can overcome the drawback of Koczy and Hirota's method described in [7]. It can guarantee that the statement "If fuzzy rules A(1) double right arrow B-1, A(2) double right arrow B-2, and the observation A* are defined by triangular membership functions, the interpolated conclusion B* will also be triangular-type" holds. (C) 1998 Elsevier Science B.V.
A new interpolative reasoning method in sparse rule-based systems
(1998-01-01)
Hsiao, WH
;
Chen, SM
;
Lee, CH
;
資訊工程學系
;
Department of Computer Science
In [7], Yan et al. analyzed Koczy and Hirota's linear interpolative reasoning method presented in [2,3] and found that the reasoning consequences by their method sometimes become abnormal fuzzy sets. Thus, they pointed out that a new interpolative reasoning method will be needed which can guarantee that the interpolated conclusion will also be triangular-type for a triangular-type observation. In this paper, we extend the works of [2,3,7] to present a new interpolative reasoning method to deal with fuzzy reasoning in sparse rule-based systems. The proposed method can overcome the drawback of Koczy and Hirota's method described in [7]. It can guarantee that the statement "If fuzzy rules A(1) double right arrow B-1, A(2) double right arrow B-2, and the observation A* are defined by triangular membership functions, the interpolated conclusion B* will also be triangular-type" holds. (C) 1998 Elsevier Science B.V.
A new method for constructing fuzzy decision trees and generating fuzzy classification rules from training examples
(2000-10-01)
Chen, SM
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Lin, SY
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資訊工程學系
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Department of Computer Science
This paper presents a new method for constructing fuzzy decision trees and generating fuzzy classification rules from training instances using compound analysis techniques. The proposed method call generate simpler fuzzy classification rules and has a better classification accuracy rate than the existing method. Furthermore. the proposed method generated less fuzzy classification rules.
A new method for constructing membership functions and fuzzy rules from training examples
(1999-02-01)
Wu, TP
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Chen, SM
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資訊工程學系
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Department of Computer Science
To extract knowledge from a set of numerical data and build up a rule-based system is an important research topic in knowledge acquisition and expert systems. In recent years, many fuzzy systems that automatically generate fuzzy rules from numerical data have been proposed. In this paper, we propose a new fuzzy learning algorithm based on the alpha-cuts of equivalence relations and the alpha-cuts of fuzzy sets to construct the membership functions of the input variables and the output variables of fuzzy rules and to induce the fuzzy rules from the numerical training data set. Based on the proposed fuzzy learning algorithm, we also implemented a program on a Pentium PC using the MATLAB development tool to deal with the Iris data classification problem. The experimental results show that the proposed fuzzy learning algorithm has a higher average classification ratio and can generate fewer rules than the existing algorithm.
A new method for evaluating weapon systems using fuzzy set theory
(1996-07-01)
Chen, SM
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資訊工程學系
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Department of Computer Science
This paper presents a new method for evaluating weapon systems using fuzzy set theory. The proposed method is more flexible than the one presented in [11] due to the fact that it allows each item of criteria to have a different weight represented by a triangular fuzzy number. Furthermore, because the proposed method does not need to perform complicated entropy weight calculations as described in [11], its execution is much faster than the one shown in [11].
A new method for evaluating weapon systems using fuzzy set theory
(1996-07-01)
Chen, SM
;
交大名義發表
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資訊工程學系
;
National Chiao Tung University
;
Department of Computer Science
This paper presents a new method for evaluating weapon systems using fuzzy set theory. The proposed method is more flexible than the one presented in [11] due to the fact that it allows each item of criteria to have a different weight represented by a triangular fuzzy number. Furthermore, because the proposed method does not need to perform complicated entropy weight calculations as described in [11], its execution is much faster than the one shown in [11].
A new method for fuzzy information retrieval based on fuzzy hierarchical clustering and fuzzy inference techniques
(2005-04-01)
Horng, YJ
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Chen, SM
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Chang, YC
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Lee, CH
;
資訊工程學系
In this paper, we extend the work of Kraft et al to present a new method for fuzzy information retrieval based on fuzzy hierarchical clustering and fuzzy inference techniques. First, we present a fuzzy agglomerative hierarchical clustering algorithm for clustering documents and to get the document cluster centers of document clusters. Then, we present a method to construct fuzzy logic rules based on the document clusters and their document cluster centers. Finally, we apply the constructed fuzzy logic rules to modify the user's query for query expansion and to guide the information retrieval system to retrieve documents relevant to the user's request. The fuzzy logic rules can represent three kinds of fuzzy relationships (i.e., fuzzy positive association relationship, fuzzy specialization relationship and fuzzy generalization relationship) between index terms. The proposed fuzzy information retrieval method is more flexible and more intelligent than the existing methods due to the fact that it can expand users' queries for fuzzy information retrieval in a more effective manner.
A new method for generating fuzzy rules from numerical data for handling classification problems
(2001-08-01)
Chen, SM
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Lee, SH
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Lee, CH
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資訊工程學系
;
Department of Computer Science
Fuzzy classification is one of the important applications of fuzzy logic. Fuzzy classification Systems are capable of handling perceptual uncertainties, such as the vagueness and ambiguity involved in classification problems. The most important task to accomplish a fuzzy classification system is to rnd a set of fuzzy rules suitable for a specific classification problem. In this article, we present a new method for generating fuzzy rules from numerical data for handling fuzzy classification problems based on the fuzzy subsethood values between decisions to be made and terms of attributes by using the level threshold value alpha and the applicability threshold value beta, where alpha is an element of [0, 1] and beta is an element of [0, 1]. We apply the proposed method to deal with the "Saturday Morning Problem,'' where the proposed method has a higher classification accuracy rate and generates fewer fuzzy rules than the existing methods.
A new method for tool steel materials selection under fuzzy environment
(1997-12-16)
Chen, SM
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交大名義發表
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資訊工程學系
;
National Chiao Tung University
;
Department of Computer Science
This paper presents a new method to solve the tool steel materials selection problem under fuzzy environment, where the importance weights of different criteria and the ratings of various alternatives under different criteria are assessed in linguistic terms represented by fuzzy numbers. Because proposed method uses simple arithmetic operations rather than the complicated arithmetic operations for aggregation and ranking of fuzzy numbers described in Wang and Chang (1995), its execution is much faster than the one presented in Wang and Chang (1995). (C) 1997 Elsevier Science B.V.
A new method for tool steel materials selection under fuzzy environment
(1997-12-16)
Chen, SM
;
資訊工程學系
;
Department of Computer Science
This paper presents a new method to solve the tool steel materials selection problem under fuzzy environment, where the importance weights of different criteria and the ratings of various alternatives under different criteria are assessed in linguistic terms represented by fuzzy numbers. Because proposed method uses simple arithmetic operations rather than the complicated arithmetic operations for aggregation and ranking of fuzzy numbers described in Wang and Chang (1995), its execution is much faster than the one presented in Wang and Chang (1995). (C) 1997 Elsevier Science B.V.
A novel bi-directional amplifier with applications in active Van Atta retrodirective arrays
(2003-02-01)
Chung, SJ
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Chen, SM
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Lee, YC
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電信工程研究所
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Institute of Communications Engineering
A novel two-port bi-directional amplifier, which may simultaneously amplify the waves coming from both ports, is proposed and demonstrated in this paper. Using this amplifier, a two-element active Van Atta retrodirective array is implemented and compared to a four-element passive array. The bi-directional amplifier is constructed by two identical one-port reflection-type amplifiers and a 3-dB 90degrees hybrid. The reflection-type amplifier is designed using an FET with a single-power-supply configuration. A quarter-wavelength microstrip radial stub is connected to the device's source terminal to narrow down the negative-resistance frequency range so as to avoid oscillation at undesired frequencies. The fabricated bi-directional amplifier provides the transmission gain over the frequency band from 5.76 to 6.88 GHz, with a peak value of 9.1 dB at 6.04 GHz. Printed Yagi antennas with four directors are adopted to build both the active and passive Van Atta arrays. The 3-dB back-scattering beamwidth of the active array is measured as wide as 74degrees. Finally, it is observed from the measurements that, although only half of the antenna elements are used, the active Van Atta array produces a back-scattering field level 4.5 dB,, on average, higher than the passive one does. This verifies the performance of the bi-directional amplifier.
A numerical study on the evolution and structure of a stress-driven free-surface turbulent shear flow
(2005-12-25)
Tsai, WT
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Chen, SM
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Moeng, CH
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土木工程學系
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Department of Civil Engineering
Turbulent shear flow beneath a flat free surface driven by a surface stress is simulated IF numerically to gain a better understanding of the hydrodynamic processes governing the scalar transfer across the air-water interface. The simulation is posed to mimic the subsequent development of a wind-driven shear layer as in a previous experiment except that the initiation of the surface waves is inhibited, thus focusing on the boundary effect of the stress-imposed surface on the underlying turbulent flow and vice versa. Despite the idealizations inherent in conducting the simulation, the computed flow exhibits the major surface features, qualitatively similar to those that appear in the laboratory and field experiments. Two distinct surface signatures, namely elongated high-speed streaks and localized low-speed spots, are observed in the simulated flow. Including temperature as a passive tracer and describing an upward heat flux at the surface, we obtain high-speed streaks that are colder and low-speed spots that are warmer than the surrounding regions. The high-speed streaks, arranged with somewhat equal cross-spacing of centimetres scale, are formed by an array of streamwise jets within the viscous sublayer immediately next to the surface. Beneath the streaks, counter-rotating streamwise vortex pairs are observed among other prevailing elongated vortices. However, they are significantly shorter in length and more irregular than their corresponding high-speed streaks at the surface. Accompanying the more organized high-speed streaks, localized regions of low streamwise velocity emerge randomly on the surface. These low-speed spots are attributed to strong upwelling flows which disrupt the viscous sublayer and also bring up the submerged fluids of low streamwise velocity. The occasional interruptions of the streamwise high-speed Jets by the upwelling flows account for bifurcation or dislocation of the surface streaks. Statistics of the turbulence are presented and their implications for the formation of the flow structures are discussed.
A Petri net model for temporal knowledge representation and reasoning - Comment
(1997-02-01)
Chen, SM
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Jong, WT
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資訊工程學系
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Department of Computer Science
In the above paper(1), Yao has presented a unified time Petri net model (TPN) for temporal knowledge representation and reasoning, where the TPN model presented has a good contribution in the aspect of temporal knowledge representation and reasoning, However, there are a number of errors which should be corrected. The purpose of this paper is to identify these errors, and the corrections provided permit the readers who have been confused by the errors to gain a better understanding of the good ideas presented.
A Petri net model for temporal knowledge representation and reasoning - Comment
(1997-02-01)
Chen, SM
;
Jong, WT
;
交大名義發表
;
資訊工程學系
;
National Chiao Tung University
In the above paper(1), Yao has presented a unified time Petri net model (TPN) for temporal knowledge representation and reasoning, where the TPN model presented has a good contribution in the aspect of temporal knowledge representation and reasoning, However, there are a number of errors which should be corrected. The purpose of this paper is to identify these errors, and the corrections provided permit the readers who have been confused by the errors to gain a better understanding of the good ideas presented.
Aggregating fuzzy opinions in the group decision-making environment
(1998-06-01)
Chen, SM
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資訊工程學系
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Department of Computer Science
This paper presents a new method for dealing with fuzzy opinion aggregation in group decision-making problems. The proposed method has the following advantages: (1) The experts' estimates do not necessarily have a common intersection at alpha-level cuts, where alpha epsilon (0,1). (2) It can perform fuzzy opinion aggregation in a more efficient manner. (3) It does not need to use the Delphi method to adjust trapezoidal fuzzy numbers given by experts.
Automatically constructing multi-relationship fuzzy concept networks for document retrieval
(2003-04-01)
Horng, YJ
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Chen, SM
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Lee, CH
;
資訊工程學系
;
Department of Computer Science
Although the knowledge bases incorporated in existing information retrieval systems can enhance retrieval effectiveness, many of them are built by domain experts. It is obvious that the construction of such knowledge bases requires a large amount of human effort. In this paper, an intelligent fuzzy information retrieval system with an automatically constructed knowledge base is presented; the knowledge base is represented by a multi-relationship fuzzy concept network. The multi-relationship fuzzy concept network can describe four kinds of context-independent and context-dependent fuzzy relationships, i.e., "fuzzy positive association" relationship, "fuzzy negative association" relationship, "fuzzy generalization" relationship, and "fuzzy specialization" relationship between concepts. The users of the fuzzy information retrieval system can submit a fuzzy contextual query which specifies the search context in the query formula. The fuzzy information retrieval system retrieves documents whose contents are relevant to the user's query by some kinds of fuzzy relationships for the specified search context of the user's query. The proposed fuzzy information retrieval method is more intelligent and more flexible than the existing methods due to the fact that it can construct multi-relationship fuzzy concept networks automatically and it can provide contextual search capability to allow the users to specify fuzzy contextual queries in a more intelligent and flexible manner.
Automatically constructing multi-relationship fuzzy concept networks in fuzzy information retrieval systems
(2001)
Horng, YJ
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Chen, SM
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Lee, CH
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資訊工程學系
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Department of Computer Science
In this paper, an intelligent fuzzy information retrieval system with an automatically constructed knowledge base is presented. The knowledge base is represented by a multi-relationship fuzzy concept network that can depict the relationships and their associating relevance degrees between concepts clearly. Based on the multi-relationship fuzzy concept network architecture, the users of the fuzzy information retrieval system can submit a fuzzy contextual query that specifies; the search context in the query formula. The fuzzy information retrieval system retrieves documents whose contents are relevant to the user's query by some required relationships beneath a specified search context The proposed fuzzy information retrieval method is more intelligent and more flexible than the existing methods since it can automatically construct knowledge bases (i.e, multi-relationship fuzzy concept networks) and it provides contextual search capability that allows users to specify fuzzy contextual queries in a more flexible manner.
Bidirectional approximate reasoning based on interval-valued fuzzy sets
(1997-11-01)
Chen, SM
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Hsiao, WH
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Jong, WT
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交大名義發表
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資訊工程學系
This paper proposes a bidirectional approximate reasoning method based on interval-valued fuzzy sets, where fuzzy production rules are used for knowledge representation, and the fuzzy terms appearing in the fuzzy production rules of a rule-based system are represented by interval-valued fuzzy sets. The proposed method is more flexible than the one presented in the paper by Bien and Chun [IEEE Trans. Fuzzy Systems 2 (1994) 177] due to the fact that it allows the fuzzy terms appearing in the fuzzy production rules of a rule-based system to be represented by interval-valued fuzzy sets rather than general fuzzy sets. Furthermore, because the proposed method requires only simple arithmetic operations, and because it allows bidirectional approximate reasoning, it can be executed much faster and more flexible than the single-input-single-output approximate reasoning scheme presented in the paper by Gorzalczany [Fuzzy Sets and Systems 21 (1987) 1]. (C) 1997 Elsevier Science B.V.