Browsing by Author "Lin, Shin-Yeu"

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A classification-based fault detection and isolation scheme for the ion implanter
(2006-11-01)
Lin, Shin-Yeu
;
Horng, Shih-Cheng
;
電控工程研究所
;
Institute of Electrical and Control Engineering
We propose a classification-based fault detection and isolation scheme for the ion implanter. The proposed scheme consists of two parts: 1) the classification part and 2) the fault detection and isolation part. In the classification part, we propose a hybrid classification tree (HCT) with learning capability to classify the recipe of a working wafer in the ion implanter, and a k-fold cross-validation error is treated as the accuracy of the classification result. In the fault detection and isolation part, we propose a warning signal generation criteria based on the classification accuracy to detect and fault isolation scheme based on the HCT to isolate the actual fault of an ion implanter. We have compared the proposed classifier with the existing classification software and tested the validity of the proposed fault detection and isolation scheme for real cases to obtain successful results.
A Computationally Efficient Method for Large Subcarrier Assignment and Bit Allocation Problem of Multiuser OFDM System
(2008-12-01)
Lin, Shin-Yeu
;
Huang, Jung-Shou
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper, we propose a computationally efficient method to solve the large dimension Adaptive Subcarrier Assignment and Bit Allocation (ASABA) problem of multiuser orthogonal frequency division multiplexing system. Our algorithm consists of three Ordinal Optimization (00) stages to find a good enough solution to the considered problem. First of all, we reformulate the considered problem to separate it into subcarrier assignment and bit allocation problem such that the objective function of a feasible subcarrier assignment pattern is the corresponding optimal bit allocation for minimizing the total consumed power. Then in the first stage, we develop an approximate objective function to evaluate the performance of a subcarrier assignment pattern and use a genetic algorithm to search through the huge solution space and select s best subcarrier assignment patterns based on the approximate objective values. In the second stage, we employ an off-line trained artificial neural network to estimate the objective values of the s subcarrier assignment patterns obtained in stage I and select the I best patterns. In the third stage, we use the exact objective function to evaluate the I subcarrier assignment patterns obtained in stage 2, and the best one associated with the corresponding optimal bit allocation is the good enough solution that we seek. We apply our algorithm to numerous cases of large-dimension ASABA problems and compare the results with those obtained by four existing algorithms. The test results show that our algorithm is the best in both aspects of solution quality and computational efficiency.
A Petri-Net-Based Automated Distributed Dynamic Channel Assignment for Cellular Network
(2009-10-01)
Lin, Shin-Yeu
;
Chan, Ting-Yu
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper, we propose a Petri-net (PN)-based automated distributed dynamic channel assignment (DDCA) method for the cellular network. We view DDCA as a discrete event system (DES) and propose a PN to model the automated DDCA. The spontaneous handshaking mechanism in the proposed PN can resolve the hard constraint of the cellular network so that no two cells within the channel reuse distance can use the same channel. Instead of the commonly adopted packing and resonance conditions for channel assignment and reassignment, we propose available channel-based channel-selection and channel-reassignment schemes. We rigorously prove the adequacy of the proposed PN and the satisfaction of hard constraint. We also test the proposed PN-based automated DDCA method using numerous test cases. The test results show that our method outperforms the comparing methods in terms of blocking probability.
Adaptive subcarrier assignment and bit allocation for multiuser OFDM system using ordinal optimization approach
(2008-09-01)
Lin, Shin-Yeu
;
Huang, Jung-Shou
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper, we propose an ordinal optimization (OO) theory-based four-stage approach to deal with the subcarrier assignment and bit allocation problem of a multiuser orthogonal frequency-division multiplexing (OFDM) system. The four-stage OO approach ensures the quality of the obtained solution, however, at the cost of solving a continuous version of the considered problem in the first stage. To resolve this computational complexity problem, we propose a hardware-implementable dual projected gradient (DPG) method to exploit deep-submicrometer technology. Compared to some existing methods using numerous simulation cases with randomly generated parameters, our approach is excellent in the aspect of power consumption. In the meantime, the estimated computation time of our approach can meet the real-time application requirement. Furthermore, we use extensive simulations to compare our good-enough solutions with the true optimal solutions, and the results show that the objective value obtained by our approach deviates from the optimal objective value around 1% on average.
Application of an ordinal optimization algorithm to the wafer testing process
(2006-11-01)
Lin, Shin-Yeu
;
Horng, Shih-Cheng
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this correspondence, we have formulated a stochastic optimization problem to find the optimal threshold values to reduce the overkills of dies under a tolerable retest level in wafer testing process. The problem is a hard optimization problem with a huge solution space. We propose an ordinal optimization theory-based two-level algorithm to solve for a vector of good enough threshold values and compare with those obtained by others using a set of 521 real test wafers. The test results confirm the feature of controlling the retest level in our formulation, and the pairs of overkills and retests resulted from our approach are almost Pareto optimal. In addition, our approach spends only 6.05 min in total in a Pentium IV personal computer to obtain the good enough threshold values.
Distributed optimal power flow with discrete control variables of large distributed power systems
(2008-08-01)
Lin, Ch'i-Hsin
;
Lin, Shin-Yeu
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper, we propose a distributed algorithm to solve the yet explored distributed optimal power flow problem with discrete control variables of large distributed power systems. The proposed algorithm consists of two distinguished features: 1) a distributed algorithm for solving continuous distributed optimal power flow to serve as a core technique in the framework of ordinal optimization (OO) strategy, and 2) implementing the OO strategy in a distributed power system to select a good enough discrete control variable solution. We have tested the proposed algorithm for several cases on the IEEE 118-bus and Tai Power 244-bus systems using a 4-PC network. The test results demonstrate the validity, robustness, and excellent computational efficiency of the proposed distributed algorithm in getting a good enough feasible solution.
Expert system based parallel multi-1D block matching algorithm with implementation for motion estimation
(2012-02-15)
Lin, Shin-Yeu
;
Su, Chong-Wei
;
Huang, Jung-Shou
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper, we propose an expert-system based parallel multi-1-dimensional block matching algorithm (ESPM-1D-BMA) for motion estimation (ME). Instead of the conventional 2D block matching, we employ the parallel multi-1D blocks matching to improve the computing speed. To improve the ME accuracy, we design a knowledge base and inference engine to determine the true motion vector (MV) from the results of parallel multi-1D blocks matching. To speed up the computing speed further, we present a hardware architecture for implementing the ESPM-1D-BMA. We have demonstrated that the MV estimation accuracy achieved by the proposed ESPM-1D-BMA is much better than the comparing fast block matching algorithms and is close to the 2 dimensional full search block matching algorithm (2D-FSBMA). We also demonstrate that the computing speed of the proposed ESPM-1D-BMA is about two times as fast as the mixed-signal 2D-FSBMA (MS-2D-FSBMA). (C) 2011 Elsevier Ltd. All rights reserved.
Expert system based parallel multi-1D block matching algorithm with implementation for motion estimation
(2011-02-15)
Lin, Shin-Yeu
;
Su, Chong-Wei
;
Huang, Jung-Shou
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper, we propose an expert-system based parallel multi-1-dimensional block matching algorithm (ESPM-1D-BMA) for motion estimation (ME). Instead of the conventional 2D block matching, we employ the parallel multi-1D blocks matching to improve the computing speed. To improve the ME accuracy, we design a knowledge base and inference engine to determine the true motion vector (MV) from the results of parallel multi-1D blocks matching. To speed up the computing speed further, we present a hardware architecture for implementing the ESPM-1D-BMA. We have demonstrated that the MV estimation accuracy achieved by the proposed ESPM-1D-BMA is much better than the comparing fast block matching algorithms and is close to the 2 dimensional full search block matching algorithm (2D-FSBMA). We also demonstrate that the computing speed of the proposed ESPM-1D-BMA is about two times as fast as the mixed-signal 2D-FSBMA (MS-2D-FSBMA). (C) 2011 Elsevier Ltd. All rights reserved.
Multi-1D Block Matching Algorithm Based Motion Estimation Processor Using Mixed-Signal Approach
(2010)
Lin, Shin-Yeu
;
Su, Chong-Wei
;
Huang, Jung-Shou
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper, we propose a Mixed Signal Parallel Multi 1Dimensional Block Matching Algorithm (MSPM-1D-BMA) based motion estimation (ME) processor. In contrast to the typical 2Dimensional full search block matching algorithm (2DFSBMA), the MSPM-1D-BMA based ME processor will greatly reduce the number of data movements in between memories. We employ a voting algorithm in the proposed ME processor to improve the accuracy of motion vector (MV) estimation. We have demonstrated that the MV estimation accuracy achieved by the proposed ME processor is much better than the existing fast block matching algorithms and is close to 2DFSBMA. We also demonstrated that the speed of the proposed ME processor approaches two times as that of the mixed signal 2DFSBMA based ME processor.
Ordinal optimization approach to stochastic simulation optimization problems and applications
(2006)
Lin, Shin-Yeu
;
Horng, Shih-Cheng
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper, we propose an ordinal optimization approach to solve for a good enough solution of the stochastic simulation optimization problem with huge decision-variable space. We apply the proposed ordinal optimization algorithm to G/G/1/K polling systems to solve for a good enough number-limited service discipline to minimize the weighting average waiting time. We have compared our results with those obtained by the existing service disciplines and found that our approach outperforms the existing ones. We have also used the genetic algorithm and simulated annealing method to solve the same stochastic simulation optimization problem, and the results show that our approach is much more superior in the aspects of computational efficiency and the quality of obtained solution.