• Title/Summary/Keyword: multi-Gaussian approach

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Performance Analysis of Space-Time Codes in Realistic Propagation Environments: A Moment Generating Function-Based Approach

  • Lamahewa Tharaka A.;Simon Marvin K.;Kennedy Rodney A.;Abhayapala Thushara D.
    • Journal of Communications and Networks
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    • v.7 no.4
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    • pp.450-461
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    • 2005
  • In this paper, we derive analytical expressions for the exact pairwise error probability (PEP) of a space-time coded system operating over spatially correlated fast (constant over the duration of a symbol) and slow (constant over the length of a code word) fad­ing channels using a moment-generating function-based approach. We discuss two analytical techniques that can be used to evaluate the exact-PEPs (and therefore, approximate the average bit error probability (BEP)) in closed form. These analytical expressions are more realistic than previously published PEP expressions as they fully account for antenna spacing, antenna geometries (uniform linear array, uniform grid array, uniform circular array, etc.) and scattering models (uniform, Gaussian, Laplacian, Von-mises, etc.). Inclusion of spatial information in these expressions provides valuable insights into the physical factors determining the performance of a space-time code. Using these new PEP expressions, we investigate the effect of antenna spacing, antenna geometries and azimuth power distribution parameters (angle of arrival/departure and angular spread) on the performance of a four-state QPSK space-time trellis code proposed by Tarokh et al. for two transmit antennas.

Identification of a Gaussian Fuzzy Classifier

  • Heesoo Hwang
    • International Journal of Control, Automation, and Systems
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    • v.2 no.1
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    • pp.118-124
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    • 2004
  • This paper proposes an approach to deriving a fuzzy classifier based on evolutionary supervised clustering, which identifies the optimal clusters necessary to classify classes. The clusters are formed by multi-dimensional weighted Euclidean distance, which allows clusters of varying shapes and sizes. A cluster induces a Gaussian fuzzy antecedent set with unique variance in each dimension, which reflects the tightness of the cluster. The fuzzy classifier is com-posed of as many classification rules as classes. The clusters identified for each class constitute fuzzy sets, which are joined by an "and" connective in the antecedent part of the corresponding rule. The approach is evaluated using six data sets. The comparative results with different classifiers are given.are given.

Multi-time probability density functions of the dynamic non-Gaussian response of structures

  • Falsone, Giovanni;Laudani, Rossella
    • Structural Engineering and Mechanics
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    • v.76 no.5
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    • pp.631-641
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    • 2020
  • In the present work, an approach for the multiple time probabilistic characterization of the response of linear structural systems subjected to random non-Gaussian processes is presented. Its fundamental property is working directly on the multiple time probability density functions of the actions and of the response. This avoids of passing through the evaluation of the response statistical moments at multiple time or correlations, reducing the computational effort in a consistent measure. This approach is the extension to the multiple time case of a previously published dynamic Probability Transformation Method (PTM) working on a single evolution of the response statistics. The application to some simple examples has revealed the efficiency of the method, both in terms of computational effort and in terms of accuracy.

Effects of the Multi-directional Irregular Waves on the Motion Responses and Tension Variations of ISSC-TLP (ISSC-TLP의 운동응답 및 변동장력에 미치는 다방향 불규칙파의 영향)

  • Lee, Chang-Ho
    • Journal of Ocean Engineering and Technology
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    • v.20 no.4 s.71
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    • pp.70-75
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    • 2006
  • A numerical procedure is described for estimating the effects of the multi-directional irregular waves on the motion responses and tension variations of the ISSC-TLP. The numerical approach is based on a three-dimensional source distribution method and a spectral analysis technique of directional waves. The spectral description for the linear system of ISSC-TLP in the frequency domain is sufficient to completely define the motion responses and tension variations. This is because both the wave inputs and responses are stationary Gaussian random processes, of which the statistical properties in the amplitude domain are well known. The numerical results for the linear motion responses and tension variations in regular waves are compared with the experimental and numerical ones, which are obtained in the literature. The results of comparison confirmed the validity of the proposed approach.

An Efficient Method for Solving a Multi-Item Newsboy Problem with a Budget-Constraint and a Reservation Policy (예산 제약과 예약 정책이 있는 복수 제품 신문 배달 소년 문제 해결을 위한 효율적 방법론)

  • Lee, Chang-Yong
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.37 no.1
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    • pp.50-59
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    • 2014
  • In this paper, we develop an efficient approach to solve a multiple-item budget-constraint newsboy problem with a reservation policy. A conventional approach for solving such problem utilizes an approximation for the evaluation of an inverse of a Gaussian cumulative density function when the argument of the function is small, and a heuristic method for finding an optimal Lagrangian multiplier. In contrast to the conventional approach, this paper proposes more accurate method of evaluating the function by using the normalization and an effective numerical integration method. We also propose an efficient way to find an optimal Lagrangian multiplier by proving that the equation for the budget-constraint is in fact a monotonically increasing function in the Lagrangian multiplier. Numerical examples are tested to show the performance of the proposed approach with emphases on the behaviors of the inverse of a Gaussian cumulative density function and the Lagrangian multiplier. By using sensitivity analysis of different budget constraints, we show that the reservation policy indeed provides greater expected profit than the classical model of not having the reservation policy.

Real-Time Human Tracking Using Skin Area and Modified Multi-CAMShift Algorithm (피부색과 변형된 다중 CAMShift 알고리즘을 이용한 실시간 휴먼 트래킹)

  • Min, Jae-Hong;Kim, In-Gyu;Baek, Joong-Hwan
    • Journal of Advanced Navigation Technology
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    • v.15 no.6
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    • pp.1132-1137
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    • 2011
  • In this paper, we propose Modified Multi CAMShift Algorithm(Modified Multi Continuously Adaptive Mean Shift Algorithm) that extracts skin color area and tracks several human body parts for real-time human tracking system. Skin color area is extracted by filtering input image in predefined RGB value range. These areas are initial search windows of hands and face for tracking. Gaussian background model prevents search window expending because it restricts skin color area. Also when occluding between these areas, we give more weights in occlusion area and move mass center of target area in color probability distribution image. As result, the proposed algorithm performs better than the original CAMShift approach in multiple object tracking and even when occluding of objects with similar colors.

Optimization-based Image Watermarking Algorithm Using a Maximum-Likelihood Decoding Scheme in the Complex Wavelet Domain

  • Liu, Jinhua;Rao, Yunbo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.1
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    • pp.452-472
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    • 2019
  • Most existing wavelet-based multiplicative watermarking methods are affected by geometric attacks to a certain extent. A serious limitation of wavelet-based multiplicative watermarking is its sensitivity to rotation, scaling, and translation. In this study, we propose an image watermarking method by using dual-tree complex wavelet transform with a multi-objective optimization approach. We embed the watermark information into an image region with a high entropy value via a multiplicative strategy. The major contribution of this work is that the trade-off between imperceptibility and robustness is simply solved by using the multi-objective optimization approach, which applies the watermark error probability and an image quality metric to establish a multi-objective optimization function. In this manner, the optimal embedding factor obtained by solving the multi-objective function effectively controls watermark strength. For watermark decoding, we adopt a maximum likelihood decision criterion. Finally, we evaluate the performance of the proposed method by conducting simulations on benchmark test images. Experiment results demonstrate the imperceptibility of the proposed method and its robustness against various attacks, including additive white Gaussian noise, JPEG compression, scaling, rotation, and combined attacks.

Dual Foot-PDR System Considering Lateral Position Error Characteristics

  • Lee, Jae Hong;Cho, Seong Yun;Park, Chan Gook
    • Journal of Positioning, Navigation, and Timing
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    • v.11 no.1
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    • pp.35-44
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    • 2022
  • In this paper, a dual foot (DF)-PDR system is proposed for the fusion of integration (IA)-based PDR systems independently applied on both shoes. The horizontal positions of the two shoes estimated from each PDR system are fused based on a particle filter. The proposed method bounds the position error even if the walking time increases without an additional sensor. The distribution of particles is a non-Gaussian distribution to express the lateral error due to systematic drift. Assuming that the shoe position is the pedestrian position, the multi-modal position distribution can be fused into one using the Gaussian sum. The fused pedestrian position is used as a measurement of each particle filter so that the position error is corrected. As a result, experimental results show that position of pedestrians can be effectively estimated by using only the inertial sensors attached to both shoes.

Android Malware Detection Using Permission-Based Machine Learning Approach (머신러닝을 이용한 권한 기반 안드로이드 악성코드 탐지)

  • Kang, Seongeun;Long, Nguyen Vu;Jung, Souhwan
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.3
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    • pp.617-623
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    • 2018
  • This study focuses on detection of malicious code through AndroidManifest permissoion feature extracted based on Android static analysis. Features are built on the permissions of AndroidManifest, which can save resources and time for analysis. Malicious app detection model consisted of SVM (support vector machine), NB (Naive Bayes), Gradient Boosting Classifier (GBC) and Logistic Regression model which learned 1,500 normal apps and 500 malicious apps and 98% detection rate. In addition, malicious app family identification is implemented by multi-classifiers model using algorithm SVM, GPC (Gaussian Process Classifier) and GBC (Gradient Boosting Classifier). The learned family identification machine learning model identified 92% of malicious app families.

Effects of Impulsive Noise on the Performance of Uniform Distributed Multi-hop Wireless Sensor Networks

  • Rob, Jae-Sung
    • Journal of information and communication convergence engineering
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    • v.5 no.4
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    • pp.300-304
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    • 2007
  • Wireless sensor networks represent a new and exciting communication paradigm which could have multiple applications in future wireless communication. Therefore, performance analysis of such a wireless sensor network paradigm is needed in complex wireless channel. Wireless networks could be an important means of providing ubiquitous communication in the future. In this paper, the BER performance of uniform distributed wireless sensor networks is evaluated in non-Gaussian noise channel. Using an analytical approach, the impact of Av. BER performance relating the coherent BPSK system at the end of a multi-hop route versus the spatial density of sensor nodes and impulsive noise parameters A and $\Gamma$ is evaluated.