• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.6
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• pp.556-564
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• 2013

This paper proposes an initial rotor position detecting algorithm of a PM synchronous motor using an incremental encoder. The proposed algorithm estimates the phase offset between the rotor magnetic flux and the Z-pulse of the incremental encoder by applying six aligning mode current control. The absolute rotor position for driving a PM synchronous motor is calculated by using the phase offset of the Z pulse and A, B pulse signals of the encoder. The PMSM drives based on the estimated rotor position is applied to the elevator door system. The door length is measured on line at first setup of the elevator. The speed control for open, close, and reopen of the elevator door is also presented and the proposed algorithm for the elevator door system is verified by experiment.

• Structural Engineering and Mechanics
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• v.13 no.1
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• pp.35-52
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• 2002

It was shown in the previous study (Lee and Bertero 1993) that incremental collapse can lead to the exhaustion of the plastic rotation capacity at critical regions in a structure when subjected to the number of load cycles and load intensities as expected during maximum credible earthquakes and that this type of collapse can be predicted using the shakedown analysis technique. In this study, a minimum-weight design methodology, which takes into account not only the prevention of this incremental collapse but also the requirements of the serviceability limit states, is proposed by using the shakedown analysis technique and a nonlinear programming algorithm (gradient projection method).

• Journal of IKEEE
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• v.12 no.1
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• pp.65-74
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• 2008

One of the popular methods used for pattern classification is the MBR (Memory-Based Reasoning) algorithm. Since it simply computes distances between a test pattern and training patterns or hyperplanes stored in memory, and then assigns the class of the nearest training pattern, it is notorious for memory usage and can't learn additional information from new data. In order to overcome this problem, we propose an incremental learning algorithm (iMPA). iMPA divides the entire pattern space into fixed number partitions, and generates representatives from each partition. Also, due to the fact that it can not learn additional information from new data, we present iMPA which can learn additional information from new data and not require access to the original data, used to train. Proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory using benchmark data sets from UCI Machine Learning Repository.

• Journal of IKEEE
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• v.18 no.2
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• pp.248-254
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• 2014

The hierarchical conference causes the data delay because the exchanged data between terminals in the conference go through the hierarchical structure. In this paper, we propose an algorithm which minimizes the average path distance between terminals in a non-incremental hierarchical conference, and which considers the computing resource. For terminals which want to join the ongoing hierarchical conference, our algorithm selects terminals that the new connection is possible among terminals in the conference with the computing resource consideration. Then, after all distance values between the selected terminals and terminals which want to join the ongoing hierarchical conference are computed, and the terminal-pair which have minimum distance value is selected, the ongoing hierarchical conference is extended with a connection of the terminal-pair which consists of a terminal among selected terminals and other terminal among terminals which want to join the ongoing hierarchical conference. This continues until all terminals are included in the conference. As the experimental results with the proposed non-incremental scheme, the hierarchical conference can be organized with 24% better performance than the earlier incremental scheme on the basis of average path distance between terminals.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.268-272
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• 2009

In this paper, we propose a Gaussian Mixture Model (GMM) based incremental robust adaptation with a forgetting factor for the speaker verification. Speaker recognition system uses a speaker model adaptation method with small amounts of data in order to obtain a good performance. However, a conventional adaptation method has vulnerable to the outlier from the irregular utterance variations and the presence noise, which results in inaccurate speaker model. As time goes by, a rate in which new data are adapted to a model is reduced. The proposed algorithm uses an incremental robust adaptation in order to reduce effect of outlier and use forgetting factor in order to maintain adaptive rate of new data on GMM based speaker model. The incremental robust adaptation uses a method which registers small amount of data in a speaker recognition model and adapts a model to new data to be tested. Experimental results from the data set gathered over seven months show that the proposed algorithm is robust against outliers and maintains adaptive rate of new data.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.2
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• pp.164-172
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• 2001

This paper describes common MPPT(Maximum Power Point Tracking) control algorithm; Constant Voltage Control, P&O(Perturbation and Observation), IncCond(Incremental Conductance), and investigated it\`s efficiency. Though simulation and efficiency evaluation, the steady/transient states characteristics and efficiency of control algorithms are analyzed respectively. Also, two-mode MPPT control to improve on the existing control algorithm. Moreover, is proposed for high efficiency this paper suggests a topology for MPPT measuring efficiency and a method of examination.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.5 s.311
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• pp.17-28
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• 2006

In this paper, we investigate a problem of updating sequential patterns when new transactions are added to a database. We present an efficient updating algorithm for sequential pattern mining that incrementally updates added transactions by reusing frequent patterns found previously. Our performance study shows that this method outperforms both AprioriAll and PrefixSpan algorithm which updates from scratch, since our method can efficiently utilize reduced candidate sets which result from the incremental updating technique.

• The Journal of Information Technology
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• v.1 no.1
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• pp.65-84
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• 1998

The MBR (Memory Based Reasoning) is a supervised learning method that utilizes the distances among the input and trained patterns in its classification, and is also called a distance based learning algorithm. The MBR is based on the k-NN classifier, in which teaming is performed by simply storing training patterns in the memory without any further processing. This paper proposes a new learning algorithm which is more efficient than the traditional k-NN classifier and has incremental learning capability, Furthermore, our proposed algorithm is insensitive to noisy patterns, and guarantees more efficient memory usage.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.54
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• pp.1-11
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• 2000

This study suggests the partition algorithm for updating the discovered association rules in large database, because a database may allow frequent or occasional updates, and such update may not only invalidate some existing strong association rules, but also turn some weak rules into strong ones. the Partition algorithm updates strong association rules efficiently in the whole update database reuseing the information of the old large itemsets. Partition algorithms that is suggested in this study scans an incremental database in view of the fact that it is difficult to find the new set of large itemset in the whole updated database after an incremental database is added to the original database. This method of generating large itemsets is different from that of FUP(Fast Update) and KDP(Kim Dong Pil)

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3B
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• pp.138-143
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• 2005

This paper aims to optimize an access probe algorithm for the CDMA 2000 system. The incremental value of PWR_STEP increases as NUM_STEP as 1dBm±0.2 for access probe of the area with good receiving sensitivity when the mobile station transmits via access channel and does not receive any ACK message. However, for the area with weak receiving sensitivity, according to the algorithm of open-loop power control, the transmitting power amplifier becomes saturated and PWR_STEP incremental value keeps performing access probe to 0dBm±0.2. Therefore interference and battery consumption increases according to the transmission of the mobile station. We have optimized the access probe algorithm according to the receiving sensitivity. We transmit the incremental value of access probe power, with delaying as much RT slot value as indicated by IS-95C standard in case of good receiving sensitivity and with delaying RT+l slot value in case of weak receiving sensitivity. Simulation results showed that the proposed algorithm contributes to decrease of the interference and battery consumption according to the transmitting power of the mobile station and improves the call duration.