• Title/Summary/Keyword: Division Algorithm

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Adaptive Random Access Algorithm for HIPERLAN/2 (HIPERLAN/2를 위한 적응적 랜덤 액세스 알고리즘)

  • Song Young-keum;Lee Jong-kyu
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.5B
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    • pp.310-316
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    • 2005
  • In this paper, we proposed and evaluated ARAH(Adaptive Random Access algorithm for HIPERLAN/2) to improve system performance. In this paper, HIPERLAN/2 uses OFDM(Orthogonal Frequency Division Multiplexing) modulation scheme to select appropriate PHY mode by Radio Channel Quality, Proposed the ARAH scheme uses these 7 PHY mode when mobile terminal determines the RCH(Random CHannel) number for random access. In this paper, these 7 PHY mode divided into two group, good and bad, and will be given high priority to mobile terminals which are in a good group. In the result of performance evaluation. ARAH algorithm, ARAH has a better performance of throughput and delay than existing algorithm.

Performance Evaluation of EEG-BCI Interface Algorithm in BCI(Brain Computer Interface)-Naive Subjects (뇌컴퓨터접속(BCI) 무경험자에 대한 EEG-BCI 알고리즘 성능평가)

  • Kim, Jin-Kwon;Kang, Dae-Hun;Lee, Young-Bum;Jung, Hee-Gyo;Lee, In-Su;Park, Hae-Dae;Kim, Eun-Ju;Lee, Myoung-Ho
    • Journal of Biomedical Engineering Research
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    • v.30 no.5
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    • pp.428-437
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    • 2009
  • The Performance research about EEG-BCI algorithm in BCI-naive subjects is very important for evaluating the applicability to the public. We analyzed the result of the performance evaluation experiment about the EEG-BCI algorithm in BCI-naive subjects on three different aspects. The EEG-BCI algorithm used in this paper is composed of the common spatial pattern(CSP) and the least square linear classifier. CSP is used for obtaining the characteristic of event related desynchronization, and the least square linear classifier classifies the motor imagery EEG data of the left hand or right hand. The performance evaluation experiments about EEG-BCI algorithm is conducted for 40 men and women whose age are 23.87${\pm}$2.47. The performance evaluation about EEG-BCI algorithm in BCI-naive subjects is analyzed in terms of the accuracy, the relation between the information transfer rate and the accuracy, and the performance changes when the different types of cue were used in the training session and testing session. On the result of experiment, BCI-naive group has about 20% subjects whose accuracy exceed 0.7. And this results of the accuracy were not effected significantly by the types of cue. The Information transfer rate is in the inverse proportion to the accuracy. And the accuracy shows the severe deterioration when the motor imagery is less then 2 seconds.

Application of Back-propagation Algorithm for the forecasting of Temperature and Humidity (온도 및 습도의 단기 예측에 있어서 역전파 알고리즘의 적용)

  • Jeong, Hyo-Joon;Hwang, Won-Tae;Suh, Kyung-Suk;Kim, Eun-Han;Han, Moon-Hee
    • Journal of Environmental Impact Assessment
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    • v.12 no.4
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    • pp.271-279
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    • 2003
  • Temperature and humidity forecasting have been performed using artificial neural networks model(ANN). We composed ANN with multi-layer perceptron which is 2 input layers, 2 hidden layers and 1 output layer. Back propagation algorithm was used to train the ANN. 6 nodes and 12 nodes in the middle layers were appropriate to the temperature model for training. And 9 nodes and 6 nodes were also appropriate to the humidity model respectively. 90% of the all data was used learning set, and the extra 10% was used to model verification. In the case of temperature, average temperature before 15 minute and humidity at present constituted input layer, and temperature at present constituted out-layer and humidity model was vice versa. The sensitivity analysis revealed that previous value data contributed to forecasting target value than the other variable. Temperature was pseudo-linearly related to the previous 15 minute average value. We confirmed that ANN with multi-layer perceptron could support pollutant dispersion model by computing meterological data at real time.

Analysis of Quality Control Technique Characteristics on Single Polarization Radar Data (단일편파 레이더자료 품질관리기술 특성 분석)

  • Park, Sora;Kim, Heon-Ae;Cha, Joo Wan;Park, Jong-Seo;Han, Hye-Young
    • Atmosphere
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    • v.24 no.1
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    • pp.77-87
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    • 2014
  • The radar reflectivity is significantly affected by ground clutter, beam blockage, anomalous propagation (AP), birds, insects, chaff, etc. The quality of radar reflectivity is very important in quantitative precipitation estimation. Therefore, Weather Radar Center (WRC) of Korea Meteorological Administration (KMA) employed two quality control algorithms: 1) Open Radar Product Generator (ORPG) and 2) fuzzy quality control algorithm to improve quality of radar reflectivity. In this study, an occurrence of AP echoes and the performance of both quality control algorithms are investigated. Consequently, AP echoes frequently occur during the spring and fall seasons. Moreover, while the ORPG QC algorithm has the merit of removing non-precipitation echoes, such as AP echoes, it also removes weak rain echoes and snow echoes. In contrast, the fuzzy QC algorithm has the advantage of preserving snow echoes and weak rain echoes, but it eliminates the partial area of the contaminated echo, including the AP echoes.

Analysis of Understanding Using Deep Learning Facial Expression Recognition for Real Time Online Lectures (딥러닝 표정 인식을 활용한 실시간 온라인 강의 이해도 분석)

  • Lee, Jaayeon;Jeong, Sohyun;Shin, You Won;Lee, Eunhye;Ha, Yubin;Choi, Jang-Hwan
    • Journal of Korea Multimedia Society
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    • v.23 no.12
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    • pp.1464-1475
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    • 2020
  • Due to the spread of COVID-19, the online lecture has become more prevalent. However, it was found that a lot of students and professors are experiencing lack of communication. This study is therefore designed to improve interactive communication between professors and students in real-time online lectures. To do so, we explore deep learning approaches for automatic recognition of students' facial expressions and classification of their understanding into 3 classes (Understand / Neutral / Not Understand). We use 'BlazeFace' model for face detection and 'ResNet-GRU' model for facial expression recognition (FER). We name this entire process 'Degree of Understanding (DoU)' algorithm. DoU algorithm can analyze a multitude of students collectively and present the result in visualized statistics. To our knowledge, this study has great significance in that this is the first study offers the statistics of understanding in lectures using FER. As a result, the algorithm achieved rapid speed of 0.098sec/frame with high accuracy of 94.3% in CPU environment, demonstrating the potential to be applied to real-time online lectures. DoU Algorithm can be extended to various fields where facial expressions play important roles in communications such as interactions with hearing impaired people.

A simple computational algorithm of ML optimum multiuser detector for synchronous code division multiple access channels (동기화된 부호 분할 다원 접속 채널을 위한 ML 최적 다중 사용자 검출기의 간단한 계산 알고리즘)

  • 권형욱;최태영;오성근
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.33A no.5
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    • pp.1-9
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    • 1996
  • In this paper, we propose an efficient computational algorithm that can reduce significantly the computational complexity of the ML optimum multiuser detector known as the most excellent detector in synchronous code division multiple access channels. The proposed detector uses the sequential detection algorithm based on the alternating maximization appraoch to obtain the ML estimates. As initial estimates for this sequential algorithm, we can use the estimated values obtained by the conventional single-user detector, the linear decorrelating multiuser detector, or the decorrelating decision-feedback muliuser detector, the linear decorrelating multiuser detector, or the decorrelating decision-feedback multiuser detector. We have performed computer simulations in order to see the convergence behaviors and the detection performance of the propsoed algorithm in terms of initial algorithms and the number of users, and then to compare the computational complexity with that of the ML optimum multiuser detector. From the results, we have seen that the proposed alternating maximization detector has nearly equal detction performance with that of the ML optimum multiuser detctor in only a few iteration.

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Novel Digital Cancelation Method in Presence of Harmonic Self-Interference

  • Ju, Hyungsik;Gwak, Donghyuk;Lee, Yuro;Kim, Tae-Joong
    • ETRI Journal
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    • v.39 no.2
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    • pp.245-254
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    • 2017
  • In-band full-duplex (IFD) communication has recently attracted a great deal of interest because it potentially provides a two-fold spectral efficiency increase over half-duplex communications. In this paper, we propose a novel digital self-interference cancelation (DSIC) algorithm for an IFD communication system in which two nodes exchange orthogonal frequency-division multiplexing (OFDM) symbols. The proposed DSIC algorithm is based on the least-squares estimation of a self-interference (SI) channel with block processing of multiple OFDM symbols, in order to eliminate the fundamental and harmonic components of SI induced through the practical radio frequency devices of an IFD transceiver. In addition, the proposed DSIC algorithm adopts discrete Fourier transform processing of the estimated SI channel to further enhance its cancelation performance. We provide a minimum number of training symbols to estimate the SI channel effectively. The evaluation results show that our proposed DSIC algorithm outperforms a conventional algorithm.

Partial Transmit Sequence Optimization Using Improved Harmony Search Algorithm for PAPR Reduction in OFDM

  • Singh, Mangal;Patra, Sarat Kumar
    • ETRI Journal
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    • v.39 no.6
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    • pp.782-793
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    • 2017
  • This paper considers the use of the Partial Transmit Sequence (PTS) technique to reduce the Peak-to-Average Power Ratio (PAPR) of an Orthogonal Frequency Division Multiplexing signal in wireless communication systems. Search complexity is very high in the traditional PTS scheme because it involves an extensive random search over all combinations of allowed phase vectors, and it increases exponentially with the number of phase vectors. In this paper, a suboptimal metaheuristic algorithm for phase optimization based on an improved harmony search (IHS) is applied to explore the optimal combination of phase vectors that provides improved performance compared with existing evolutionary algorithms such as the harmony search algorithm and firefly algorithm. IHS enhances the accuracy and convergence rate of the conventional algorithms with very few parameters to adjust. Simulation results show that an improved harmony search-based PTS algorithm can achieve a significant reduction in PAPR using a simple network structure compared with conventional algorithms.

Application of Ray Following Algorithm to High Resolution Satellite Image Simulation

  • Shin, Dong-Seok;Park, Won-Kyu
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.559-564
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    • 2002
  • This paper describes a new algorithm named as ray following algorithm which is applied for high-resolution satellite image simulation. The problems of the conventional ray tracing algorithm are pointed out especially when terrain elevations vary abruptly. The proposed algorithm follows the directional ray vector sequentially and thoroughly in order to determine the crossing point of the ray with the terrain surface. This way of sequential height comparison method is regarded as the only way to obtain accurate surface cross-section when a highly variant digital surface model is used. The experimental results show and compare the validities of the conventional and proposed algorithms.

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PAPR reduction of OFDM systems using H-SLM method with a multiplierless IFFT/FFT technique

  • Sivadas, Namitha A.
    • ETRI Journal
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    • v.44 no.3
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    • pp.379-388
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    • 2022
  • This study proposes a novel low-complexity algorithm for computing inverse fast Fourier transform (IFFT)/fast Fourier transform (FFT) operations in binary phase shift keying-modulated orthogonal frequency division multiplexing (OFDM) communication systems without requiring any twiddle factor multiplications. The peak-to-average power ratio (PAPR) reduction capacity of an efficient PAPR reduction technique, that is, H-SLM method, is evaluated using the proposed IFFT algorithm without any complex multiplications, and the impact of oversampling factor for the accurate calculation of PAPR is analyzed. The power spectral density of an OFDM signal generated using the proposed multiplierless IFFT algorithm is also examined. Moreover, the bit-error-rate performance of the H-SLM technique with the proposed IFFT/FFT algorithm is compared with the classical methods. Simulation results show that the proposed IFFT/FFT algorithm used in the H-SLM method requires no complex multiplications, thereby minimizing power consumption as well as the area of IFFT/FFT processors used in OFDM communication systems.