• Title/Summary/Keyword: multi-valued function

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Neural adaptive equalization of M-ary QAM signals using a new activation function with a multi-saturated output region (새로운 다단계 복소 활성 함수를 이용한 신경회로망에 의한 M-ary QAM 신호의 적응 등화)

  • 유철우;홍대식
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.35C no.1
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    • pp.42-54
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    • 1998
  • For decreasing intersymbol interference (ISI) due to band-limited channels in digitalcommunication, the uses of equalization techniques are necessary. Among the useful adaptive equalization techniques, because of their ease of implementation and nonlinear capabilites, the neural networks have been used as an alternative for effectively dealing with the channel distortion. In this paepr, a complex-valued multilayer percepron is proposed as a nonlinear adaptive equalizer. After the important properties that a suitable complex-valued activation function must possess are discussed, a new complex-valued activation function is developed for the proposed schemes to deal with M-ary QAM signals of any constellation sizes. It has been further proven that by the nonlinear transformation of the proposed function, the correlation coefficient between the real and imaginary parts of input data decreases when they are jointly Gaussian random variables. Lastly, the effectiveness of the proposed scheme is demonstrated by simulations. The proposed scheme provides, compared with the linear equalizer using the least mean squares (LMS) algorith, an interesting improvement concerning Bit Error Rate (BER) when channel distortions are nonlinear.

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Variable Multi-valued Spatial Filter Detector with High Speed Exchangeable Weighting Function and Its Application

  • O, Hyunmin-G;Junya Takayama;Shinji Ohyama;Akira Kobayashi
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.79.3-79
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    • 2002
  • $\textbullet$ Introduction $\textbullet$ Structure of variable multi-valued spatial filter detector(VMSFD) $\textbullet$ Moment analysis by VMSFD $\textbullet$ Experimental results $\textbullet$ Fabricated chip with photodiode array $\textbullet$ Conclusion

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Hazard-Free Multi-valued sequential logic cirwits (Hazard-Free를 考慮한 多値順序論理回路)

  • 林寅七 = In-Chil Lim;李秀英
    • Communications of the Korean Institute of Information Scientists and Engineers
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    • v.5 no.2
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    • pp.94-98
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    • 1987
  • Multi-Valued(MV) sequential logic circuits are proposed which are free from HAZARD. In this paper, HAZARD is classified Function and Logic HAZARD, and MV switching function in which they are eliminated is described. Also, the basic MV memory elements which can be realized without HAZARD are presented, so that suggest the realizability in the large-scale MV logic system based on these elements.

ORTHOGONAL MULTI-WAVELETS FROM MATRIX FACTORIZATION

  • Xiao, Hongying
    • Journal of the Korean Mathematical Society
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    • v.46 no.2
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    • pp.281-294
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    • 2009
  • Accuracy of the scaling function is very crucial in wavelet theory, or correspondingly, in the study of wavelet filter banks. We are mainly interested in vector-valued filter banks having matrix factorization and indicate how to choose block central symmetric matrices to construct multi-wavelets with suitable accuracy.

Photovoltaic System Allocation Using Discrete Particle Swarm Optimization with Multi-level Quantization

  • Song, Hwa-Chang;Diolata, Ryan;Joo, Young-Hoon
    • Journal of Electrical Engineering and Technology
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    • v.4 no.2
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    • pp.185-193
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    • 2009
  • This paper presents a methodology for photovoltaic (PV) system allocation in distribution systems using a discrete particle swarm optimization (DPSO). The PV allocation problem is in the category of mixed integer nonlinear programming and its formulation may include multi-valued dis-crete variables. Thus, the PSO requires a scheme to deal with multi-valued discrete variables. This paper introduces a novel multi-level quantization scheme using a sigmoid function for discrete particle swarm optimization. The technique is employed to a standard PSO architecture; the same velocity update equation as in continuous versions of PSO is used but the particle's positions are updated in an alternative manner. The set of multi-level quantization is defined as integer multiples of powers-of-two terms to efficiently approximate the sigmoid function in transforming a particle's position into discrete values. A comparison with a genetic algorithm (GA) is performed to verify the quality of the solutions obtained.

A Climate Prediction Method Based on EMD and Ensemble Prediction Technique

  • Bi, Shuoben;Bi, Shengjie;Chen, Xuan;Ji, Han;Lu, Ying
    • Asia-Pacific Journal of Atmospheric Sciences
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    • v.54 no.4
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    • pp.611-622
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    • 2018
  • Observed climate data are processed under the assumption that their time series are stationary, as in multi-step temperature and precipitation prediction, which usually leads to low prediction accuracy. If a climate system model is based on a single prediction model, the prediction results contain significant uncertainty. In order to overcome this drawback, this study uses a method that integrates ensemble prediction and a stepwise regression model based on a mean-valued generation function. In addition, it utilizes empirical mode decomposition (EMD), which is a new method of handling time series. First, a non-stationary time series is decomposed into a series of intrinsic mode functions (IMFs), which are stationary and multi-scale. Then, a different prediction model is constructed for each component of the IMF using numerical ensemble prediction combined with stepwise regression analysis. Finally, the results are fit to a linear regression model, and a short-term climate prediction system is established using the Visual Studio development platform. The model is validated using temperature data from February 1957 to 2005 from 88 weather stations in Guangxi, China. The results show that compared to single-model prediction methods, the EMD and ensemble prediction model is more effective for forecasting climate change and abrupt climate shifts when using historical data for multi-step prediction.

Multi-variate Fuzzy Polynomial Regression using Shape Preserving Operations

  • Hong, Dug-Hun;Do, Hae-Young
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.1
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    • pp.131-141
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    • 2003
  • In this paper, we prove that multi-variate fuzzy polynomials are universal approximators for multi-variate fuzzy functions which are the extension principle of continuous real-valued function under $T_W-based$ fuzzy arithmetic operations for a distance measure that Buckley et al.(1999) used. We also consider a class of fuzzy polynomial regression model. A mixed non-linear programming approach is used to derive the satisfying solution.

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A BEM implementation for 2D problems in plane orthotropic elasticity

  • Kadioglu, N.;Ataoglu, S.
    • Structural Engineering and Mechanics
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    • v.26 no.5
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    • pp.591-615
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    • 2007
  • An improvement is introduced to solve the plane problems of linear elasticity by reciprocal theorem for orthotropic materials. This method gives an integral equation with complex kernels which will be solved numerically. An artificial boundary is defined to eliminate the singularities and also an algorithm is introduced to calculate multi-valued complex functions which belonged to the kernels of the integral equation. The chosen sample problem is a plate, having a circular or elliptical hole, stretched by the forces parallel to one of the principal directions of the material. Results are compatible with the solutions given by Lekhnitskii for an infinite plane. Five different orthotropic materials are considered. Stress distributions have been calculated inside and on the boundary. There is no boundary layer effect. For comparison, some sample problems are also solved by finite element method and to check the accuracy of the presented method, two sample problems are also solved for infinite plate.

A Study on the Realization of Variable Spatial Filtering Detector with Multi-Value Weighting Function (계측용 공간필터의 가변적 다치화된 가중치 실현에 관한 연구)

  • Jeong, Jun-Ik;Han, Young-Bae;Go, Hyun-Min;Rho, Do-Hwan
    • Proceedings of the KIEE Conference
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    • 1998.11b
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    • pp.481-483
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    • 1998
  • In general, spatial filtering method was proposed to simplify measurement system through parallel Processing hardware. Spatial filtering is a method of detection that we can get a spatial pattern information, as we process a special space pattern, to say, as we process spatial parallel process by using the spatial weighting function. The important processing characteristics will be depended in according to how ire design a spatial weighting function, a spatial sensitive distribution. The form of the weighting function which is realized from the generally used spatial filtering is fixed and the weighting value was already became a binary-value. In this paper, we propose a new method in order to construct adaptive measurement systems. This method is a weighting function design to make multi-valued and variable.

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A Study on the plan of the Main Entrance and the Concourse in General Hospitals for Healthcare Environments as Multi-therapy (멀티 테라피를 적용한 치유 환경적 종합병원 로비공간 계획에 관한 연구)

  • Noh, Eun-Jung;Oh, Eun-Jin;Kim, Chung-Ki
    • Proceedings of the Korean Institute of Interior Design Conference
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    • 2005.10a
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    • pp.115-118
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    • 2005
  • Korea has experienced many changes since modern hospitals started to be built. Among these changes, interest in 'Promotion of Curing environment', which is the most fundamental one of the hospital functions, has increased more and more. The lobby makes the first impression of a medical building and that is an important function. Recently, the lobby became highly valued not only as a waiting area or a pathway only but as a cultural area. The lobby is considered simply as a complex and busy area because it plays an important role in the building' communications and access systems and has various uses and functions. Based on the concept of curing environment, the lobby can be planned as a facility combining culture and medical functions by applying multi therapy.

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