• Journal of information and communication convergence engineering
• /
• 제4권4호
• /
• pp.136-140
• /
• 2006

In this paper, we consider the detection of orthogonal space-time block codes (OSTBCs) without channel state information (CSI) at the receiver. Based on the conventional blind cyclic decoder, we propose an enhanced blind cyclic decoder which has higher system performance than the conventional one. Furthermore, the proposed decoder offers low complexity since it does not require the computation of singular value decomposition.

• ETRI Journal
• /
• 제26권5호
• /
• pp.384-390
• /
• 2004

We propose a new bandwidth-efficient technique that achieves high data rates over a wideband wireless channel. This new scheme is targeted for a multiple-input multiple- output orthogonal frequency-division multiplexing (MIMO-OFDM) system that achieves transmit diversity through a space frequency block code and capacity enhancement through the iterative joint processing of zero-forcing detection and maximum a posteriori (MAP) decoding. Furthermore, the proposed scheme is compared to the coded Bell Labs Layered Space-Time OFDM (BLAST-OFDM) scheme.

• 산업경영시스템학회지
• /
• 제28권1호
• /
• pp.114-120
• /
• 2005

This paper studies procedures for bottleneck detection in closed queueing networks(CQN's) with multiple job classes. Bottlenecks refer to servers operating at $100\%$ utilization. For CQN's, this can occur as the population sizes approach infinity. Bottleneck detection reduces to a non-linear complementary problem which in important special cases may be interpreted as a Kuhn-Tucker set. Efficient computational procedures are provided.

• 한국전자파학회지:전자파기술
• /
• 제4권3호
• /
• pp.54-62
• /
• 1993

이 논문에서는 다중 TCM (Multiple Trellis-Coded Modulation, MTCM)을 적용하여 변조 시스템의 성능 을 향상 시컨 트렐리스 부호화된 8DPSK를 구성하고 그 성능을 분석한다. 또한 BER(Bit Error Rate)의 향상 을 위해 다중 심볼 차동 검파 방식을 적용한다. 모탤링한 채덜은 디지틀 위성 이동 통신 채널인 라이시안 페이 딩(Rician fading) 채널이다. 디코딩 방볍은 비터비 알고리듬을 사용하며, 연집 에러에의한 비터비 디코더의 에러 전파를 막기위해 인터리빙을 사용한다. 컴퓨터 시율레이션올 통하여 다중 TCM파 다중 심벌 차동 겁파를 적용한 트렐리스 부호화된 8DPSK는 동일한 대역폭 효율을 갖는 부호화되지 않은 차동 변조 방식보다 향상된 성능을 보임을 알 수 있다. 또한 페이딩 환경에서는 인터리빙 방법이 성능 향상에 중요함을 알 수 있다.

• 한국추진공학회:학술대회논문집
• /
• 한국추진공학회 2008년도 제31회 추계학술대회논문집
• /
• pp.192-195
• /
• 2008

다중 트림 상태에서 헬리콥터용 소형 터보샤프트 엔진에 부착된 센서의 고장을 검출하기 위한 방법을 제시한다. 먼저 헬리곱터의 엔진, 로터, 되먹임(feedback) 제어루프가 포함된 비선형 모델을 구하고 다중 트림 상태에서의 선형 모델을 추출하였다. 고장 검출 방법은 칼만필터에 기반한 방법을 채용하였는데 트림 상태가 변화할 때에 필터의 추정값이 연속적으로 변화하도록 상태변수 초기값을 재구성하였다. 또한 어떠한 센서가 고장이 일어났는지 구분할 수 있도록 어떤 센서의 고장을 검출한 다음 문제가 없는 경우 다음 센서의 고장 검출을 수행하는 단계적인 방법을 사용하였다. 시뮬레이션을 통하여 제시한 방법이 다중 트림 상태에서 각 센서의 고장을 잘 검출함을 보였다.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2021년도 추계학술대회
• /
• pp.422-424
• /
• 2021

In this paper, it leads the approach of fusing multiple RGB cameras for visual objects recognition based on deep learning with convolution neural network and 3D Light Detection and Ranging (LiDAR) to observe the environment and match into a 3D world in estimating the distance and position in a form of point cloud map. The goal of perception in multiple cameras are to extract the crucial static and dynamic objects around the autonomous vehicle, especially the blind spot which assists the AV to navigate according to the goal. Numerous cameras with object detection might tend slow-going the computer process in real-time. The computer vision convolution neural network algorithm to use for eradicating this problem use must suitable also to the capacity of the hardware. The localization of classified detected objects comes from the bases of a 3D point cloud environment. But first, the LiDAR point cloud data undergo parsing, and the used algorithm is based on the 3D Euclidean clustering method which gives an accurate on localizing the objects. We evaluated the method using our dataset that comes from VLP-16 and multiple cameras and the results show the completion of the method and multi-sensor fusion strategy.

• 전자공학회논문지B
• /
• 제29B권1호
• /
• pp.102-112
• /
• 1992

We have already proposed an extended fuzzy clustering algorithm which considers the importance of the data to be classified in a previous paper. In this paper, we suggest the extended fuzzy clustering algorithm based new method to slove a multiple peak detection problem, and prove experimently that this algorithm can detect the multiple peak adaptively to the noise and the shape of peaks.

• Journal of Positioning, Navigation, and Timing
• /
• 제1권1호
• /
• pp.15-21
• /
• 2012

For a GNSS receiver's robustness against RFI and the high accuracy of navigation solution in GNSS, interference source detection and mitigation are needed. In this paper, an adaptive lattice IIR notch filter is employed to track single-tone continuous wave and swept continuous wave interference signals, and an interference detection method is proposed. Furthermore, this paper presents interference source characterization algorithm using multiple ground stations' interference detection results. The measurement of the signal powers from each ground station is used to build weighting factors to estimate the type of the interference. The performance of interference detection algorithm is simulated for scenarios of GPS signal in the presence of single-tone continuous wave interference and swept continuous wave interference.

• Journal of information and communication convergence engineering
• /
• 제18권2호
• /
• pp.75-81
• /
• 2020

Approximately 1.3 million people die from traffic accidents each year, and smartphone usage while driving is one of the main causes of such accidents. Therefore, detection of smartphone usage by drivers has become an important part of distracted driving detection. Previous studies have used single camera-based methods to collect the driver images. However, smartphone usage detection by employing a single camera can be unsuccessful if the driver occludes the phone. In this paper, we present a driver smartphone usage detection system that uses multiple cameras to collect driver images from different perspectives, and then processes these images with ensemble convolutional neural networks. The ensemble method comprises three individual convolutional neural networks with a simple voting system. Each network provides a distinct image perspective and the voting mechanism selects the final classification. Experimental results verified that the proposed method avoided the limitations observed in single camera-based methods, and achieved 98.96% accuracy on our dataset.

• Journal of Electrical Engineering and Technology
• /
• 제10권3호
• /
• pp.1284-1292
• /
• 2015

As visual surveillance systems become more and more common in human lives, approaches based on these systems to solve security problems in practice are boosted, especially in railway applications. In this paper, we first propose a robust snag detection algorithm and then present a railway security system by using a combination of multiple sensors and the vision based snag detection algorithm. The system aims safety at several repeatedly occurred situations including slope protection, inspection of the falling-object from bridges, and the detection of snags and foreign objects on the rail. Experiments demonstrate that the snag detection is relatively robust and the system could guarantee the security of the railway through these real-time protections and detections.