• Proceedings of the Acoustical Society of Korea Conference
• /
• 1992.06a
• /
• pp.23-28
• /
• 1992

The purpose of this paper is to develop a new adaptive echo canceller improving convergence speed and near-end-talker detection performance of the conventional echo canceller. In a conventional adaptive echo canceller, an adaptive digital filter with TDL(Tapped-Delay Line) structure modelling the echo path uses the LMS(Least Mean Square) algorithm to cote the coefficients, and NET detector using energy comparison method prevents the adaptive digital filter to update the coefficients during the periods of the NET signal presence. The convergence speed of the LMS algorithm depends on the eigenvalue spread ratio of the reference signal and NET detector using the energy comparison method yields poor detection performance if the magnitude of the NET signal is small. This paper presents a new adaptive echo canceller which uses the pre-whitening filter to improve the convergence speed of the LMS algorithm. The pre-whitening filter is realized by using a low-order lattice predictor. Also, a new NET signal detection algorithm is presented, where the start point of the NET signal is detected by computing the cross-correlation coefficient between the primary input and the ADF(Adaptive Digital Filter) output while the end point is detected by using the energy comparison method. The simulation results show that the convergence speed of the proposed adaptive echo canceller is faster than that of the conventional echo canceller and the cross-correlation coefficient yield more accurate detection of the start point of the NET signal.

• The KIPS Transactions:PartA
• /
• v.11A no.2
• /
• pp.159-164
• /
• 2004

In the previous researches, tree comparison methods are almost studied in comparing weighted or labeled tree(decorated tree). But in this paper, we propose a tree comparison and similarity evaluation algorithm can be applied to comparison of two normal trees. The algorithm converts two trees into node string using unparser, evaluates similarity and finally return similarity value from 0.0 to 1.0. In the experiment part of this paper, we visually presented matched nodes and unmatched nodes between two trees. By using this tree similarity algorithm, we can not only evaluate similarity between two specific programs or documents but also detect duplicated code.

• Journal of Environmental Science International
• /
• v.18 no.4
• /
• pp.355-367
• /
• 2009

Comparison study on the land surface temperatures, which are calculated from four different algorithms for MODIS data, was carried out and the characteristics of each algorithm on land surface temperature estimation were also analysed in this study. Algorithms, which are well used for various satellite data analysis, in the comparisons are proposed by Price, Becker and Li, Ulivieri et al., and Wan. Verification of estimated land surface temperature from each algorithm is also performed using observation based regression data. The coefficient of determination ($R^2$) for daytime land surface temperature estimated from Wan's algorithm is higher than that of another algorithms at all seasons and the value of $R^2$ reach on 0.92 at spring. Although $R^2$ for Ulivieri's algorithm is slightly lower than that for Wan's algorithm, the variation pattern of land surface temperature for two algorithms are similar. However, the difference of estimated values among four algorithms become small at the region of high land surface temperature.

• Proceedings of the KSRS Conference
• /
• 1998.09a
• /
• pp.307-312
• /
• 1998

The paper first describes the atmospheric correction algorithm for the Ocean Color and Temperature Scanner (OCTS) visible band data used at Earth Observation Center (EOC) of National Space Development Agency of Japan (NASDA). It uses 10 candidate aerosol models including "Asian dust model" introduced in consideration of the unique feature of aerosols over the east Asian waters. Based on the observations at 670 and 865 nm bands where the reflectance of the water body can be discarded, the algorithm selects a pair of aerosol models that accounts best for the observed spectral reflectances to synthesize the aerosol reflectance in other bands. The paper also evaluates the performance of the algorithm by comparing the satellite estimates of water-leaving radiance and chlorophyll-a concentration with selected buoy-and ship-measured data. In comparison with the old CZCS-type atmospheric correction algorithm where the aerosol reflectance is as-sumed to be spectrally independent, the OCTS algorithm records factor 2-3 less error in estimating the normalized water-leaving radiances. In terms of chlorophyll-a concentration estimation, however, the accuracy stays vey similar compared to that of the CZCS-type algorithm. This is considered to be due to the nature of in-water algorithm which relies on spectral ratio of water-leaving radiances.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.11
• /
• pp.2131-2138
• /
• 2011

GPS is vulnerable to jamming because of extremely low signal power. Many anti-jamming techniques are studied for complement this vulnerability. Anti-jamming techniques using array antenna are most effective technique and these techniques are required the DOA estimates. MUSIC algorithm and Root-MUSIC Algorithm are typical algorithms used in DOA estimation. Two algorithms have different characteristics, so the choice of an algorithm may depends on many factors such as the environment and the system requirements. The analysis and performance comparison of both algorithms is necessary to choose the best method to apply. This paper summarizes the theory of MUSIC and Root-MUSIC algorithms. And this paper extends both algorithm to estimate two-dimensional angles. The software simulator of both algorithms are implemented to evaluate the performance. Root-MUSIC algorithm has the computational advantage on ULA. MUSIC algorithm is applicable to any antenna array. MUSIC shows better estimation performance when number of array element is small while the computational load of MUSIC is much higher than Root-MUSIC.

• Korean Journal of Remote Sensing
• /
• v.14 no.3
• /
• pp.262-276
• /
• 1998

The paper first describes the atmospheric correction algorithm for the Ocean Color and Temperature Scanner (OCTS) visible band data used at Earth Observation Center (EOC) of National Space Development Agenrr of japan (NASDA). It uses 10 candidate aerosol models including "Asian dust model" introduced in consideration of the unique feature of aerosols over the east Asian waters. Based on the observations at 670 and 865 nm bands where the reflectance of the water body can be discarded, the algorithm selects a pair of aerosol models that accounts best for the observed spectral reflectances to synthesize the aerosol reflectance in other bands. The paper also evaluates the performance of the algorithm by comparing the satellite estimates of water-leaving radiance and chlorophyll-a concentration with selected buoy- and ship-measured data. In comparison with the old CZCS-type atmospheric correction algorithm where the aerosol reflectance is assumed to be spectrally independent, the OCTS algorithm records factor 2-3 less error in estimating the normalized water-leaving radiances. In terms of chlorophyll-a concentration estimation, however, the accuracy stays very similar compared to that of the CZCS-type algorithm. This is considered to be due to the nature of in-water algorithm which relies on spectral ratio of water-leaving radiances.

• Journal of Information Processing Systems
• /
• v.17 no.4
• /
• pp.721-736
• /
• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• Journal of Korean Society of Transportation
• /
• v.14 no.1
• /
• pp.135-154
• /
• 1996

This paper presents a heuristic algorithm for classifying vehicles using a single loop detector. The data used for the development of the algorithm are the frequency variation of a vehicle sensored from the circle-shaped loop detectors which are normal buried beneath the expressway. The pre-processing of data is required for the development of the algorithm that actually consists of two parts. One is both normalization of occupancy time and that with frequency variation, the other is finding of an adaptable number of sample size for each vehicle category and calculation of average value of normalized frequencies along with occupancy time that will be stored for comparison. Then, detected values are compared with those stored data to locate the most fitted pattern. After the normalization process, we developed some frameworks for comparison schemes. The fitted scales used were 10 and 15 frames in occupancy time(X-axis) and 10 and 15 frames in frequency variation (Y-axis). A combination of X-Y 10-15 frame turned out to be the most efficient scale of normalization producing 96 percent correct classification rate for six types of vehicle.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.11a
• /
• pp.648-654
• /
• 2007

This paper presents the result of a comparison study to evaluate the performance of several semi-active control algorithms for use with large-scale MR damper applied to a building structure under seismic excitation using real-time hybrid test method. Recently, a variety of semi-active control algorithm studies are developed and generally evaluated the performance by using numerical analysis. In this paper real-time hybrid test method was applied to performance evaluating of semi-active control algorithms including a clipped optimal algorithm and the modulated homogeneous friction algorithm.

• International journal of advanced smart convergence
• /
• v.5 no.1
• /
• pp.30-33
• /
• 2016

With the advent of big data, data mining is more increasingly utilized in various decision-making fields by extracting hidden and meaningful information from large amounts of data. Even as exponential increase of the request of unrevealing the hidden meaning behind data, it becomes more and more important to decide to select which data mining algorithm and how to use it. There are several mainly used data mining algorithms in biology and clinics highlighted; Logistic regression, Neural networks, Supportvector machine, and variety of statistical techniques. In this paper it is attempted to compare the classification performance of an exemplary algorithm J48 and REPTree of ML algorithms. It is confirmed that more accurate classification algorithm is provided by the performance comparison results. More accurate prediction is possible with the algorithm for the goal of experiment. Based on this, it is expected to be relatively difficult visually detailed classification and distinction.