• Title/Summary/Keyword: performance metric

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A Study on Pipelined Architecture with Branch Prediction and Two Paths Strategy (분기 예측과 이중 경로 전략을 결합한 파이프라인 구조에 관한 연구)

  • Ju, Yeong-Sang;Jo, Gyeong-San
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.1
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    • pp.181-190
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    • 1996
  • Pipelined architecture improves processor performance by overlapping the execution of several different instructions. The effect of control hazard stalls the pipeline and reduces processor performance. In order to reduce the effect of control hazard caused by branch, we proposes a new approach combining both branch prediction and two paths strategy. In addition, we verify the performance improvement in a proposed approach by utilizing system performance metric CPI rather than BEP.

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A maximum likelihood sequence detector in impulsive noise environment (충격성 잡음 환경에서의 최우 검출기)

  • 박철희;조용수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.6
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    • pp.1522-1532
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    • 1996
  • In this paper, we compare the performance of channel estimators with the L$_{1}$-norm and L$_{2}$-norm criteria in impulaive noise environment, and show than the L$_{1}$-norm criterion is appropriate for that situation. Also, it is shown that the performance of the conventional maximum likelihood sequence detector(MLSD) can be improved by applying the same principle to mobile channels. That is, the performance of the conventional MLSD, which is known to be optimal under the Gaussian noise assumption, degrades in the impulsive noise of radio mobile communication channels. So, we proposed the MLSD which can reduce the effect of impulsive noise effectively by applying the results of channel estimators. Finally, it is confirmed by computer simulation that the performance of MLSD is significantly affected depending on the types of branch metrics, and that, in the impulsive noise environments, the proposed one with new branch metrics performs better thatn the conventional branch metric, l y(k)-s(k) l$^{[-992]}$ .

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Estimation of Detection Performance for Vehicle FMCW Radars Using EM Simulations

  • Yoo, Sungjun;Kim, Hanjoong;Byun, Gangil;Choo, Hosung
    • Journal of electromagnetic engineering and science
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    • v.19 no.1
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    • pp.13-19
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    • 2019
  • This paper proposes a systematic method for estimating detection performances of a frequency-modulated continuous wave radar using electromagnetic simulations. The proposed systematic method includes a radar system simulator that can obtain range-Doppler images using the electromagnetic (EM) simulations in conjunction with a test setup employed for performance evaluation of multiple targets at different velocities in a traffic environment. This method is then applied for optimizing the half-power beamwidths of the antenna array using an evaluation metric defined to improve the detection strengths for the multiple targets. The optimized antenna has vertical and horizontal half-power beam widths of $10^{\circ}$ and $60^{\circ}$, respectively. The results confirm that that the proposed systematic method is suitable to improve the radar detection performance with the enhanced radar-Doppler images.

Analysis of CIELuv Color feature for the Segmentation of the Lip Region (입술영역 분할을 위한 CIELuv 칼라 특징 분석)

  • Kim, Jeong Yeop
    • Journal of Korea Multimedia Society
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    • v.22 no.1
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    • pp.27-34
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    • 2019
  • In this paper, a new type of lip feature is proposed as distance metric in CIELUV color system. The performance of the proposed feature was tested on face image database, Helen dataset from University of Illinois. The test processes consists of three steps. The first step is feature extraction and second step is principal component analysis for the optimal projection of a feature vector. The final step is Otsu's threshold for a two-class problem. The performance of the proposed feature was better than conventional features. Performance metrics for the evaluation are OverLap and Segmentation Error. Best performance for the proposed feature was OverLap of 65% and 59 % of segmentation error. Conventional methods shows 80~95% for OverLap and 5~15% of segmentation error usually. In conventional cases, the face database is well calibrated and adjusted with the same background and illumination for the scene. The Helen dataset used in this paper is not calibrated or adjusted at all. These images are gathered from internet and therefore, there are no calibration and adjustment.

Load Balancing Schemes in the MANET with Multiple Internet Gateways (다중 인터넷 게이트웨이를 갖는 MANET의 부하 균등화 기법)

  • Kim, Young-Min;Lim, Yu-Jin;Yu, Hyun;Lee, Jae-Hwoon;Ahn, Sang-Hyun
    • The KIPS Transactions:PartC
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    • v.13C no.5 s.108
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    • pp.621-626
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    • 2006
  • A mobile ad hoc network (MANET) is an infrastructureless network that supports multi-hop communication. For the MANET nodes wishing to communicate with nodes in the wired Internet, the global Internet connectivity is required and this functionality can be achieved with the help of the Internet gateway. For the support of reliability and flexibility, multiple Internet gateways can be provisioned for a MANET. In this case, load-balancing becomes one of the important issues since the network performance such as the network throughput can be improved if the loads of the gateways are well-balanced. In this paper, we categorize the load-balancing mechanisms and propose a new metric for load-balancing. Simulation results show that our proposed mechanism using the hop distance and the number of routing table entries as a load-balancing metric enhances the overall network throughput.

No-reference Image Quality Assessment With A Gradient-induced Dictionary

  • Li, Leida;Wu, Dong;Wu, Jinjian;Qian, Jiansheng;Chen, Beijing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.1
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    • pp.288-307
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    • 2016
  • Image distortions are typically characterized by degradations of structures. Dictionaries learned from natural images can capture the underlying structures in images, which are important for image quality assessment (IQA). This paper presents a general-purpose no-reference image quality metric using a GRadient-Induced Dictionary (GRID). A dictionary is first constructed based on gradients of natural images using K-means clustering. Then image features are extracted using the dictionary based on Euclidean-norm coding and max-pooling. A distortion classification model and several distortion-specific quality regression models are trained using the support vector machine (SVM) by combining image features with distortion types and subjective scores, respectively. To evaluate the quality of a test image, the distortion classification model is used to determine the probabilities that the image belongs to different kinds of distortions, while the regression models are used to predict the corresponding distortion-specific quality scores. Finally, an overall quality score is computed as the probability-weighted distortion-specific quality scores. The proposed metric can evaluate image quality accurately and efficiently using a small dictionary. The performance of the proposed method is verified on public image quality databases. Experimental results demonstrate that the proposed metric can generate quality scores highly consistent with human perception, and it outperforms the state-of-the-arts.

Depth Map Interpolation Using High Frequency Components (고주파 성분을 이용한 깊이맵의 보간)

  • Jang, Seung-Eun;Kim, Sung-Yeol;Kim, Man-Bae
    • Journal of Broadcast Engineering
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    • v.17 no.3
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    • pp.459-470
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    • 2012
  • In this paper, we propose a method to upsample a low-resolution depth map to a high-resolution version. While conventional camera sensors produce high-resolution color images, the sizes of the depth maps of range/depth sensors are usually low. In this paper, we consider the utilization of high-frequency components to the conventional depth map interpolation methods such as bilinear, bicubic, and bilateral. The proposed method is composed of the three steps: high-frequency component extraction, high-frequency component application, and interpolation. Two objective evaluation measures such as sharpness degree and blur metric are used to examine the performance. Experimental results show that the proposed method significantly outperforms other conventional methods by a factor of 2 in terms of sharpness degree. As well, a blur metric is reduced by a factor of 14 %.

An Adaptive K-best Algorithm Based on Path Metric Comparison for MIMO Systems (MIMO System을 위한 Path Metric 비교 기반 적응형 K-best 알고리즘)

  • Kim, Bong-Seok;Choi, Kwon-Hue
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.11A
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    • pp.1197-1205
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    • 2007
  • An adaptive K-best detection scheme is proposed for MIMO systems. The proposed scheme changes the number of survivor paths, K based on the degree of the reliability of Zero-Forcing (ZF) estimates at each K-best step. The critical drawback of the fixed K-best detection is that the correct path's metric may be temporarily larger than K minimum paths metrics due to imperfect interference cancellation by the incorrect ZF estimates. Based on the observation that there are insignificant differences among path metrics (ML distances) when the ZF estimates are incorrect, we use the ratio of the minimum ML distance to the second minimum as a reliability indicator for the ZF estimates. So, we adaptively select the value of K according to the ML distance ratio. It is shown that the proposed scheme achieves the significant improvement over the conventional fixed K-best scheme. The proposed scheme effectively achieves the performance of large K-best system while maintaining the overall average computation complexity much smaller than that of large K system.

Decision on the Optimal Photographing Angle and Overlapping Ratio of Non-metric Cameras for Development of Automatic Image Stitching System (영상집성 자동화 시스템 개발을 위한 비측량용 카메라의 최적 촬영각 및 중복도 결정)

  • Kim, Dae Sung;Shin, Sang Chul
    • Journal of Korean Society for Geospatial Information Science
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    • v.21 no.2
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    • pp.117-123
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    • 2013
  • This study focuses on the determination of optimal photographing angle and overlapping ratio for automatic image stitching system using a non-metric camera module with motorized head. Photographing overlap was calculated considering the angle of view on different kinds of lenses and moving angle of motorized head per each option, and optimal photographing angle and overlapping ratio could be determined through the experimental result using the operating time, data volume and performance of image stitching. Through this experiment, we could find that it was effective to take a picture with $36^{\circ}$ of interval(33.82% of overlap) in vertical direction and $24^{\circ}$ or $30^{\circ}$ of interval(36.51% or 20.63% of overlap) in horizontal direction using 35mm lens for automatic image stitching system.

Super Metric: Quality Assessment Methods for Immersive Video (몰입형 비디오 품질 평가를 위한 슈퍼 메트릭)

  • Jeong, Jong-Beom;Kim, Seunghwan;Lee, Soonbin;Kim, Inae;Ryu, Eun-Seok
    • Journal of Internet Computing and Services
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    • v.22 no.2
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    • pp.51-58
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    • 2021
  • Three degrees of freedom plus(3DoF+) and six degrees of freedom(6DoF) system, which supports a user's movements in graphical and natural scene-based virtual reality, requires multiple high-quality and high-resolution videos to provide immersive media. Previous video quality assessment methods are not appropriate for the 3DoF+ and 6DoF system assessment because different types of artifacts occur in these systems which are not shown in the traditional video compression. This paper provides the performance assessments of several quality assessment methods in 3DoF+ system. Furthermore, this paper presents a super metric, which combines multiple quality assessment methods, thereby it showed a higher correlation coefficient with the subjective quality assessment than the previous methods. Experimental results on 3DoF+ immersive video showed 0.4513 gain on correlation coefficient with subjective quality assessment compared to that of peak signal-to-noise ratio(PSNR).