• Journal of the Korea Society of Computer and Information
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• v.25 no.2
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• pp.49-58
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• 2020

In this study, we solve an online multi-object problem which finds object states (i.e. locations and sizes) while conserving their identifications in online-provided images and detections. We handle this problem based on a tracking-by-detection approach by linking (or associating) detections between frames. For more accurate online association, we propose novel online appearance learning with discrete fourier transform and partial least square analysis (PLS). We first transform each object image into a Fourier image in order to extract meaningful features on a frequency domain. We then learn PLS subspaces which can discriminate frequency features of different objects. In addition, we incorporate the proposed appearance learning into the recent confidence-based association method, and extensively compare our methods with the state-of-the-art methods on MOT benchmark challenge datasets.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.1
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• pp.138-149
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• 1994

This paper introduces a new monitoring technique which utilizes an adaptive signal processing for feature generation, coupled with a multilayered merual network for pattern recognition. The cutting force signal in face milling operation was modeled by a low order discrete autoregressive model, shere parameters were estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(recursive least square) method with discounted measurements. The influences of the adaptation algorithm parameters as well as some considerations for modeling on the estimation results are discussed. The sensitivity of the extimated model parameters to the tool state(new and worn tool)is presented, and the application of a multilayered neural network to tool state monitoring using the previously generated features is also demonstrated with a high success rate. The methodology turned out to be quite suitable for in-process tool wear monitoring in the sense that the model parameters are effective as tool state features in milling operation and that the classifier successfully maps the sensors data to correct output decision.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.11B
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• pp.1884-1894
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• 2000

광대역 무선 통신 시스템에서는 주파수 선택적 다중경로 페이딩 채널상에서 발생하는 인접 심볼간의 간섭에 의한 성능 열화를 극복하기 위해서 채널 등화 기술의 도입이 필연적이다. 그러나, 데이터 전송률이 증가함에 따라 채널 등화에 필요한 훈련열의 길이가 늘어나고, 이로 인한 오버헤드를 감소하기 위해서는 보다 수렴률이 높은 적응 알고리즘이 요구된다. 본 논문에서는 주파수 영역의 적응 여파 기법 중의 하나인 자기 직교환 방식의 결정궤환 등화기를 고려한다. 이 채널 등화기에서는 적응 알고리즘으로 DCT-LMS (discrete cosine transform least mean square) 알고리즘을 채택함으로써 수렴률과 MSE (mean square error) 성능을 향상시켜 결과적으로 광대역 무선통신에서 요구되는 훈련열에 따른 오버헤드를 감소시킬 수 있게 된다. 시뮬레이션을 통해 주파수 선택적 다중경로 페이딩 채널에서의 제안된 채널 등화 기법에 대한 성능을 분석한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.8
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• pp.1510-1514
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• 2011

In this paper, linear discrete model of the electro-hydraulic servo system are made for parameters estimation. The parameters of electro-hydraulic servo system are estimated using the recursive least square method. Persistent excitation conditions are studied in order to estimate parameters of electro-hydraulic servo system to real values and parameters estimation affections are studied due to the forgetting factors variation. As the results, An parameter estimation method has been synthesized for minimizing the error between reference and error.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.69-72
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• 1999

In this paper, an efficient time domain equalization algorithm for discrete wavelet multitone(DWMT) data transmission is developed. In this algorithm, the time domain equalizer(TEQ) consists of two stages, i.e., the channel impulse response shortening equalizer(TEQ-S) in the first stage and the channel frequency flattening equalizer(TEQ-F) in the second stage. TEQ-S reduces the length of transmission channel impulse response to decrease intersymbol interference(ISI) followed by TEQ-F that enhances the channel frequency response characteristics to the level of an ideal channel, hence diminishes the bit error rate. TEQ-S is implemented using the least-squares(LS) method, while TEQ-F is designed by using the least mean-square(LMS) algorithm. Since DWMT system also requires of the frequency domain equalizer in order to further reduce ICI and ISI the hardware complexity is an another concern. However, by adopting an well designed and trained TEQ, the hardware complexity of the whole DWMT system can be greatly reduced.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1407-1419
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• 2020

Long time-series gridded data is crucial for the analyses of Earth environmental changes. Climate reanalysis and satellite images are now used as global-scale periodical and quantitative information for the atmosphere and land surface. This paper examines the feasibility of DCT-PLS (penalized least square regression based on discrete cosine transform) for the spatial gap filling of gridded data through the experiments for multiple variables. Because gap-free data is required for an objective comparison of original with gap-filled data, we used LDAPS (Local Data Assimilation and Prediction System) daily data and MODIS (Moderate Resolution Imaging Spectroradiometer) monthly products. In the experiments for relative humidity, wind speed, LST (land surface temperature), and NDVI (normalized difference vegetation index), we made sure that randomly generated gaps were retrieved very similar to the original data. The correlation coefficients were over 0.95 for the four variables. Because the DCT-PLS method does not require ancillary data and can refer to both spatial and temporal information with a fast computation, it can be applied to operative systems for satellite data processing.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.60-67
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• 1990

This paper proposes a model-based fault detection method for linear/nonlinear system having modelling errors, nonlinearities and measurement noise. The system model is represented by the unified operator [5] in order to apply to both the continuous-time and discrete-time problems. The fault detection method suggested here accounts for the effects of noise, model mismatch and nonlinearities. Modelling errors are depicted by additive forms and the nominal model denominator is fixed via prior experiments in order to quantify the nucertainty bound on the parameter estima-tion. The least square method is used to estimate the numerator parameters of the nominal model. performance than traditional methods.

• Journal of computational fluids engineering
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• v.11 no.1 s.32
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• pp.57-66
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• 2006

An optimal shape design approach is presented for a subsonic S-shaped intake using aerodynamic sensitivity analysis. Two-equation turbulence model is employed to capture strong counter vortices in the S-shaped duct more precisely. Sensitivity analysis is performed for the three-dimensional Navier-Stokes equations coupled with two-equation turbulence models using a discrete adjoint method For code validation, the result of the flow solver is compared with experiment data and other computational results of bench marking test. To study the influence oj turbulence models and grid refinement on the duct flow analysis, the results from several turbulence models are compared with one another and the minimum number of grid points, which can yield an accurate solution is investigated The adjoint variable code is validated by comparing the complex step derivative results. To realize a sufficient and flexible design space, NURBS equations are introduced as a geometric representation and a new grid modification technique, Least Square NURBS Grid Approximation is applied With the verified flow solver, the sensitivity analysis code and the geometric modification technique, the optimization of S-shaped intake is carried out and the enhancement of overall intake performance is achieved The designed S-shaped duct is tested in several off-design conditions to confirm the robustness of the current design approach. As a result, the capability and the efficiency of the present design tools are successfully demonstrated in three-dimensional highly turbulent internal flow design and off-design conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.7C
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• pp.627-634
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• 2007

When a higher-order modulation scheme (16QAM or 64QAM) is applied to the communications system using the nonlinear high power amplifier (HPA), the performance can be degraded by the nonlinear distortion of the HPA. The nonlinear distortion can be compensated by the adaptive nonlinear Volterra equalizer using the low-complexity LMS algorithm at the receiver. However, the LMS algorithm shows very slow convergence performance. So, in this paper, the parallel M-band discrete wavelet transformed LMS algorithm is proposed in order to improve the convergence speed. Throughout the computer simulations, it is shown that the convergence performance of the proposed method is superior to that of the conventional time-domain and transform-domain LMS algorithms.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.305-316
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• 2010

The MODerate Resolution Imaging Spectroradiometer (MODIS) sensor has 36 bands at 250m, 500m, 1km spatial resolution. However, 500m or 1km MODIS data exhibits a few limitations when low resolution data is applied at small areas that possess complex land cover types. In this study, we produce seven 250m spectral bands by fusing two MODIS 250m bands into five 500m bands. In order to recommend the best fusion method by which one acquires MODIS data, we compare seven fusion methods including the Brovey transform, principle components algorithm (PCA) fusion method, the Gram-Schmidt fusion method, the least mean and variance matching method, the least square fusion method, the discrete wavelet fusion method, and the wavelet-PCA fusion method. Results of the above fusion methods are compared using various evaluation indicators such as correlation, relative difference of mean, relative variation, deviation index, peak signal-to-noise ratio index and universal image quality index, as well as visual interpretation method. Among various fusion methods, the local mean and variance matching method provides the best fusion result for the visual interpretation and the evaluation indicators. The fusion algorithm of 250m MODIS data may be used to effectively improve the accuracy of various MODIS land products.