• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.547-554
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• 2007

This thesis presents a kind of active noise control(ANC) algorithm for reducing noise due to engine inside a car. The proposed control algorithm is, by using WP(Wavelet Packet), a one improving the instability due to delay of noise transmission and the lack of response ability for the rapid change of noise, which are defects of the existing FXLMS(Filtered-X Least Mean Square) algorithm. The chief character of this system is a thing that faster operation than the FXLMS is implemented by inserting WP in the secondary path. In other words, WP implements parallel operation. Then, the weights of filter in the adaptive algorithm will be updated faster. In addition, because WP have so excellent a resolution, they can process very minute noise. The efficiency of this control algorithm will be demonstrated in the matlab simulation and in the actual experiments by using a Labview program and a car.

• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.441-451
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• 2022

In the era of bigdata, scalability is a crucial issue in learning models. Among many others, the Alternating Direction of Multipliers (ADMM, Boyd et al., 2011) algorithm has gained great popularity in solving large-scale problems efficiently. In this article, we propose applying the ADMM algorithm to solve the least square problem penalized by the pairwise-difference penalty, frequently used to identify group structures among coefficients. ADMM algorithm enables us to solve the high-dimensional problem efficiently in a unified fashion and thus allows us to employ several different types of penalty functions such as LASSO, Elastic Net, SCAD, and MCP for the penalized problem. Additionally, the ADMM algorithm naturally extends the algorithm to distributed computation and real-time updates, both desirable when dealing with large amounts of data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.1984-1989
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• 1998

Convergence properties of the stochastic gradient adaptive algorithm based on the least mean absolute third (LMAT) error criterion is presented.In particular, the performnce of the algorithmis examined and compared with least mena square (LMS) algorithm for several different probability densities of the measurement noisein a system identification mode. It is observedthat the LMAT algorithm outperforms the LMS algorithm for most of the noise probability densities, except for the case of the exponentially distributed noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.601-610
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• 2004

In this paper, the performance of an adaptive array antenna using Constant Modulus Algorithm (CMA) based on the signal structure for the IMT-2000 3GPP specification reverse link of an asynchronous direct sequence code division multiple access (DS-CDMA) system are evaluated. In addition, the performance is compared with the array antenna using Least Mean Square (LMS) based on the training signal. The simulation parameters such as the number of multipath, mu10pa1h intensity profiles between path, spreading gain and multiuser etc., are considered in the Monte Carlo simulation. Simulation results demonstrate an adaptive array antenna using CMA may give more capacity gain than the amy antenna using LMS in the case of multipath fading channel.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.6
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• pp.609-615
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• 2000

The energy conservation is one of the most important issues in recent years. Especially, the energy conservation through improved control strategies is one of the most highly possible area to be implemented in the near future. The energy conservation of the ice storage system can be accomplished through the improved control strategies. A real time building load prediction algorithm was developed. The expected highest and the lowest outdoor temperature of the next day were used to estimate the next day outdoor temperature profile. The measured dry bulb temperature and the measured building load were used to estimate system parameters by using the on-line weighted recursive least square method. The estimated hourly outdoor temperatures and the estimated hourly system parameters were used to predict the next day hourly building loads. In order to see the effectiveness of the building load prediction algorithm, two different types of building models were selected and analysed. The simulation results show less than 1% in error for the prediction of the next day building loads. Therefore, this algorithm may successfully be used for the development of improved control algorithms of the ice storage system.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.274-279
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• 1998

For the accurate generation of DEMs, the determination of match quality in adaptive least square matching algorithm is significantly important. Traditionally, only the degree of convergence of a solution matrix in least squares estimation has been considered for the determination of match quality. It is, however, not enough to determine the true match quality. This paper reports two approaches of match quality determination based on adaptive least square correlation : the conventional if-then logic approaches with scene geometry and correlation as additional quality measures; and, the fuzzy logic approaches. Through these, accurate decision of match quality will minimize the number of blunder and maximize the number of exact match. The proposed methods have been tested on JERS and SPOT images and the results show good performance.

• The Journal of the Acoustical Society of Korea
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• v.6 no.3
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• pp.60-67
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• 1987

In this paper, a phoneme classification method for Korean speech recognition has been proposed and its performance has been studied. The phoneme classification has been done based on the phonemic features extracted by the prewindowed recursive least-square (PRLS) algorithm that is a kind of adaptive filter algorithms. Applying the PRLS algorithm to input speech signal, precise detection of phoneme boundaries has been made, Reference patterns of Korean phonemes have been generated by the ordinery vector quantization (VQ) of feature vectors obtained manualy from prototype regions of each phoneme. In order to obtain the performance of the proposed phoneme classification method, the method has been tested using spoken names of seven Korean cities which have eleven different consonants and eight different vowels. In the speaker-dependent phoneme classification, the accuracy is about $85\%$ considering simple phonemic rules of Korean language, while the accuracy of the speaker-independent case is far less than that of the speaker-dependent case.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.7
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• pp.1468-1476
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• 1997

In mobile communication systems, the Reduced State Sequence Estimation(RSSE) receiver must be able to track changes in the channel. This is carried out by the adaptive channel estimator. However, when the tentative decisions are used in the channel estimator, incorrect decisions can cause error propagation. This paper presents a new channel estimator using the path history in the Viterbi decoder for preventing error propagation. The selection of the path history in the Viterbi decoder for preventing error propagation. The selection of the path history for the channel estimator depends on the path metric as in the decoding of the Viterbi decoder in RSSE. And a discussion on the channel estimator with different adaptation algorithms such as Least Mean Square(LMS) algorithm and Recursive Least Square(RLS) algorithm is provided. Results from computer simulations show that the RSSE receivers using the proposed channel estimator have better performance than the other conventional RSSE receiver, and that the channel estimator with RLS algorithm is adequate for multipath fading channel.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.162-167
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• 2003

In this paper, a novel feasible real-time system was researched for a differential driven wheeled autonomous mobile robot so that the mobile robot can move in a smooth, safe and elegant way. Least Square Minimum Path Planning was well used for the system to generate a smooth executable path for the mobile robot, and the point-to-point tracking algorithm was presented as well as its application in arbitrary path tracking. In order to make sure the robot can run elegantly and safely, trapezoidal speed was integrated into the point-to-point path tracking algorithm. The application to guest following for the autonomous mobile robot shows its wide application of the algorithm. The novel design was successfully proved to be feasible by our experiments on our mobile robot Interactive Robot Usher (IRU) in National University of Singapore.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.2
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• pp.164-171
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• 2009

This paper presents new learning algorithm of dynamic Bayesian networks (DBN) by means of constrained least square (LS) estimation algorithm and gradient descent method. First, we propose constrained LS based parameter estimation for a Markov chain (MC) model given observation data sets. Next, a gradient descent optimization is utilized for online estimation of a hidden Markov model (HMM), which is bi-linearly constructed by adding an observation variable to a MC model. We achieve numerical simulations to prove its reliability and superiority in which a series of non stationary random signal is applied for the DBN models respectively.