• Title/Summary/Keyword: Information input algorithm

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Chaos QPSK Modulated Beamspace MIMO System Using ESPAR Antenna (ESPAR 안테나를 사용하는 카오스 QPSK 변조 빔 공간 MIMO 시스템)

  • Lee, Jun-Hyun;Bok, Jun-Yeong;Ryu, Heung-Gyoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39A no.2
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    • pp.77-85
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    • 2014
  • Recently, utilization of MIMO(Multi-Input Multi-Output) system using array antennas is evaluated significantly according to the extension of high-capacity and high-speed communication services. However, MIMO system has disadvantages such as high-complexity and high-power-consumption, because RF(Radio Frequency) chain is required as antenna number, and several array antenna is used in conventional MIMO system. In order to solve these problems, research about beamspace MIMO system using ESPAR(Electronically Steerable Parasitic Array Radiator) antenna that has single RF chain by using one active antenna and several parasitic elements has been studied actively. Beamspace MIMO system using ESPAR antenna is possible to solve the problems of conventional MIMO system, because this system is composed by single RF chain. In this paper, in order to improve the system security, chaos communication algorithm that has characteristics such as non-periodic, non-predictability, easy implementation and initial condition is applied to QPSK (Quadrature Phase Shift Keying) modulated beamspace MIMO system. We design the chaos QPSK modulated beamspace MIMO system, and evaluate SER performance of this system.

Fast Speech Recognition System using Classification of Energy Labeling (에너지 라벨링 그룹화를 이용한 고속 음성인식시스템)

  • Han Su-Young;Kim Hong-Ryul;Lee Kee-Hee
    • Journal of the Korea Society of Computer and Information
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    • v.9 no.4 s.32
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    • pp.77-83
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    • 2004
  • In this paper, the Classification of Energy Labeling has been proposed. Energy parameters of input signal which are extracted from each phoneme are labelled. And groups of labelling according to detected energies of input signals are detected. Next. DTW processes in a selected group of labeling. This leads to DTW processing faster than a previous algorithm. In this Method, because an accurate detection of parameters is necessary on the assumption in steps of a detection of speeching duration and a detection of energy parameters, variable windows which are decided by pitch period are used. A pitch period is detected firstly : next window scale is decided between 200 frames and 300 frames. The proposed method makes it possible to cancel an influence of windows and reduces the computational complexity by $25\%$.

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A VLSI Architecture for the Real-Time 2-D Digital Signal Processing (실시간 2차원 디지털 신호처리를 위한 VLSI 구조)

  • 권희훈
    • Information and Communications Magazine
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    • v.9 no.9
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    • pp.72-85
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    • 1992
  • The throughput requirement for many digital signal processing is such that multiple processing units are essential for real-time implementation. Advances in VLSI technology make it feasible to design and implement computer systems consisting of a large number of function units. The research on a very high throughput VLSI architecture for digital signal processing applications requires the development of an algorithm, decomposition scheme which can minimize data communication requirements as well as minimize computational complexity. The objectives of the research are to investigate computationally efficient algorithms for solution of the class of problems which can be modeled as DLSI systems or adaptive system, and develop VLSI architectures and associated multiprocessor systems which can be used to implement these algorithms in real-time. A new VLSI architecture for real-time 2-D digital signal processing applications is proposed in this research. This VLSI architecture extends the concept of having a single processing units in a chip. Because this VLSI architecture has the advantage that the complexity and the number of computations per input does not increase as the size of the input data in increased, it can process very large 2-D date in near real-time.

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Quality Improvement of Low Bitrate HE-AAC using Linear Prediction Pre-processor (저 전송률 환경에서 선형예측 전처리기를 사용한 HE-AAC의 성능 향상)

  • Lee, Jae-Seong;Lee, Gun-Woo;Park, Young-Chul;Youn, Dae-Hee
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.8C
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    • pp.822-829
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    • 2009
  • This paper proposes a new method of improving the quality of High Efficiency Advanced Audio Coding (HE-AAC). HE-AAC encodes input source by allocating bits for each scalefactor bands appropriately according to human ear's psychoacoustic property. As a result, insufficient bits are assigned to the bands which have relatively low energy. This imbalance between different energy bands can cause decreasing of sound quality like musical noise. In the proposed system, a Linear Prediction (LP) module is combined with HE-AAC as a pre-processor to improve sound quality by even bits distribution. To apply accurate human being's psychoacoustic property, the psychoacoustic model uses Fast Fourier Transform (FFT) spectrum of original input signal to make masking threshold. In its implementation, masking threshold of psychoacoustic model is normalized using the LP spectral envelope in prior to quantization of the LP residual. Experimental result shows that, the proposed algorithm allocates bits appropriately for insufficient bits condition and improves the performance of HE-AAC.

A QOC Signal Detection Method for Spatially Multiplexed MIMO Systems (공간다중화 MIMO 시스템을 위한 QOC 신호검출 기법)

  • Im, Tae-Ho;Kim, Jae-Kwon;Cho, Yong-Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.9C
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    • pp.771-777
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    • 2010
  • This paper proposes a new signal detection method, called QR-OSIC with Candidates (QOC) method, for spatially multiplexed multiple input multiple output (MIMO) systems. By using the ordered successive interference cancellation (OSIC) algorithm and the maximum likelihood (ML) metric, the proposed method achieves near-ML performance without requiring a large number of candidates. Although the proposed method can be used for both hard and soft decoding systems, it is especially useful for soft decoding systems since the LLR values for all the bits can be efficiently computed without using LLR estimation. The proposed method is also suitable for VLSI implementation since it leads to fixed throughput system.

A Study on Management Method of Infectious Wastes Applying RFID (감염성 폐기물 관리를 위한 RFID 적용에 관한 연구)

  • Joung, Lyang-Jae;Sung, Nak-Chang;Kang, Hean-Chan;Kang, Dae-Seong
    • Journal of the Institute of Convergence Signal Processing
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    • v.8 no.1
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    • pp.63-72
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    • 2007
  • Recently, as recognizing the risk about the infection of an infectious wastes, the problems about the management and treatment of the infectious wastes stand out socially. In this paper, as being possible monitoring whole processing from the origin of the infectious waste to the processing plant, using the RFID which is the kernel technology of the next generation, we tried to solve the second infection problem by inefficient treatment of the infectious wastes. Through the research suggesting in this paper, as storing and monitoring the procedural business articles and the problem about miss-writing and input error being found in management system like documentary writing by the existing manager and computation input by the web application, we can understand the management state, immediately. And the Bio information for the personal authentication is carried out through storing the feature vector calculation by the PCA algorithm, into the tag. It suggested more systematic and safer management plan than previous thing, as giving attention about the wastes to manager.

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Efficient Allocation and Connection of Concentrators and Repeaters Using Approximate Steiner Minimum Tree in Automatic Meter Reading System (원격 검침 시스템에서 근사 최소 스타이너 트리를 이용한 집중기 및 중계기의 효율적인 배치와 연결)

  • Kim, Chae-Kak;Kim, In-Bum;Kim, Soo-In
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.10B
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    • pp.994-1003
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    • 2009
  • For Automatic Meter Reading System, good topology of check machines, concentrators, and repeaters in client field is important. Steiner Minimum Tree is a minimum cost tree connecting all given nodes with introducing Steiner points. In this paper, an efficient mechanism allocating and connecting check machines, concentrators and repeaters which are essential elements in automatic meter reading system is proposed, which conducts repeated applications of building approximate Minimum Steiner Trees. In the mechanism, input nodes and Steiner points might correspond to check machine, concentrators or repeaters and edges might do to the connections between them. Therefore, through suitable conversions and processes of them, an efficient network for automatic meter reading system with both wired and wireless communication techniques could be constructed. In our experiment, for 1000 input nodes and 200 max connections per node, the proposed mechanism shortened the length of produced network by 19.1% comparing with the length of Minimum Spanning Tree built by Prim's algorithm.

Monitoring and Prediction of Appliances Electricity Usage Using Neural Network (신경회로망을 이용한 가전기기 전기 사용량 모니터링 및 예측)

  • Jung, Kyung-Kwon;Choi, Woo-Seung
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.8
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    • pp.137-146
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    • 2011
  • In order to support increased consumer awareness regarding energy consumption, we present new ways of monitoring and predicting with energy in electric appliances. The proposed system is a design of a common electrical power outlet called smart plug that measures the amount of current passing through current sensor at 0.5 second. To acquire data for training and testing the proposed neural network, weather parameters used include average temperature of day, min and max temperature, humidity, and sunshine hour as input data, and power consumption as target data from smart plug. Using the experimental data for training, the neural network model based on Back-Propagation algorithm was developed. Multi layer perception network was used for nonlinear mapping between the input and the output data. It was observed that the proposed neural network model can predict the power consumption quite well with correlation coefficient was 0.9965, and prediction mean square error was 0.02033.

A Study on the extraction of hydrologic-Model input parameter using GSIS (GSIS를 이용한 수문모형 입력매개변수 추출에 관한 연구)

  • Lee, Geung-Sang;Chae, Hyo-Seok;Park, Jeong-Nam;Cho, Gi-Sung
    • Journal of Korean Society for Geospatial Information Science
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    • v.8 no.2 s.16
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    • pp.11-22
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    • 2000
  • It needs to extract the accurate topological characteristics and hydrological parameters of watershed in order to manage water resource efficiently. But, these data are processed yet by manual wok and simple operation in hydrologic fields. In this paper, we presented algorithm that could extract topological characteristics and hydrological parameters over watershed using GSIS and it gives the saving of data processing tin and the confidency of data. We presented coupling method between GSIS and hydrologic model by using extracted parameters into the input parameter of HEC-HMS hydrologic model. The extraction procedure of topological characteristics and hydrological parameters is as below. First, watershed and stream are extracted by DEM and curve unmber is extracted throughout the overlay of landuse map and soil map. Also, we extracted surface parameters like the length of the longest flow path and the slope of the longest flow path by Grid computation into watershed and stream. And we gave the method that could extract hydrologic parameters like Muskingum K and sub-basin lag tin by executing computation into surface parameters and average Sn curve number being extracted.

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Detection of Visual Attended Regions in Road Images for Assisting Safety Driving (안전 운전 지원을 위한 도로 영상에서 시각 주의 영역 검출)

  • Kim, Jong-Bae
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.49 no.1
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    • pp.94-102
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    • 2012
  • Recently entered into an aging socity as the number of elderly drivers is increasing. Traffic accidents of elderly drivers are caused by driver inattentions such as poor vehicle control due to aging, visual information retrieval problems caused by presbyopia, and objects identifying problems caused by low contrast sensitivity. In this paper, detection method of ROIs on the road is proposed. The proposed method creates the saliency map to detect the candidate ROIs from the input image. And, the input image is segmented to obtain the ROIs boundary. Finally, selective visual attention regions are detected according to the presence or absence of a segmented region with saliency pixels. Experimental results from a variety of outdoor environmental conditions, the proposed method presented a fast object detection and a high detection rate.