• Title/Summary/Keyword: Probability Density function

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INCOMPLETE EXTENDED HURWITZ-LERCH ZETA FUNCTIONS AND ASSOCIATED PROPERTIES

  • Parmar, Rakesh K.;Saxena, Ram K.
    • Communications of the Korean Mathematical Society
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    • v.32 no.2
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    • pp.287-304
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    • 2017
  • Motivated mainly by certain interesting recent extensions of the generalized hypergeometric function [Integral Transforms Spec. Funct. 23 (2012), 659-683] by means of the incomplete Pochhammer symbols $({\lambda};{\kappa})_{\nu}$ and $[{\lambda};{\kappa}]_{\nu}$, we first introduce incomplete Fox-Wright function. We then define the families of incomplete extended Hurwitz-Lerch Zeta function. We then systematically investigate several interesting properties of these incomplete extended Hurwitz-Lerch Zeta function which include various integral representations, summation formula, fractional derivative formula. We also consider an application to probability distributions and some special cases of our main results.

An Adaptive Contrast Enhancement Method for Real-Time Processing (실시간 처리를 위한 적응형 콘트라스트 향상 기법)

  • Cho Hwa-Hyun;Choi Myung-Ryul
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.1
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    • pp.51-57
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    • 2005
  • In this paper, we propose an adaptive contrast control method for the flat real-time processing. The proposed method has employed probability density function(PDF) in order to control a sudden change in image-brightness. In addition, the proposed algerian obtains the maximum contrast without affecting the processed image. In order to reduce hardware complexity, we have utilized approximated CDF based on sampling values. Visual test and standard deviation of their histogram have been introduced to evaluate the resultant output images of at: proposed method and the original ones.

A probabilistic nearest neighbor filter incorporating numbers of validated measurements

  • Sang J. Shin;Song, Taek-Lyul;Ahn, Jo-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.82.1-82
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    • 2002
  • $\textbullet$ Nearest neighbor filter $\textbullet$ Probabilistic nearest neighbor filter $\textbullet$ Probabilistic nearest neighbor filter incorporating numbers of validated measurements $\textbullet$ Probability density function of the NDS $\textbullet$ Simulation results in a clutter environment to verify the performances $\textbullet$ Sensitivity analysis for the unknown spatial clutter density

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The Study on Application of Regional Frequency Analysis using Kernel Density Function (핵밀도 함수를 이용한 지역빈도해석의 적용에 관한 연구)

  • Oh, Tae-Suk;Kim, Jong-Suk;Moon, Young-Il;Yoo, Seung-Yeon
    • Journal of Korea Water Resources Association
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    • v.39 no.10 s.171
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    • pp.891-904
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    • 2006
  • The estimation of the probability precipitation is essential for the design of hydrologic projects. The techniques to calculate the probability precipitation can be determined by the point frequency analysis and the regional frequency analysis. The regional frequency analysis includes index-flood technique and L-moment technique. In the regional frequency analysis, even if the rainfall data passed homogeneity, suitable distributions can be different at each point. However, the regional frequency analysis can supplement the lacking precipitation data. Therefore, the regional frequency analysis has weaknesses compared to parametric point frequency analysis because of suppositions about probability distributions. Therefore, this paper applies kernel density function to precipitation data so that homogeneity is defined. In this paper, The data from 16 rainfall observatories were collected and managed by the Korea Meteorological Administration to achieve the point frequency analysis and the regional frequency analysis. The point frequency analysis applies parametric technique and nonparametric technique, and the regional frequency analysis applies index-flood techniques and L-moment techniques. Also, the probability precipitation was calculated by the regional frequency analysis using variable kernel density function.

Change of stochastic properties of MEMS structure in terms of dimensional variations using function approximation moment method (함수 근사 모멘트 기법을 활용한 치수 분포에 따른 MEMS 구조물의 통계적 특성치 변화에 관한 연구)

  • Huh J.S.;Kwak B.M.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.602-606
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    • 2005
  • A systematic procedure of probability analysis for general distributions is developed based on the first four moments estimated from polynomial interpolation of the system response function and the Pearson system. The function approximation is based on a specially selected experimental region for accuracy and the number of function evaluations is taken equal to that of the unknown coefficient for efficiency. For this purpose, three error-minimizing conditions are proposed and corresponding canonical experimental regions are formed for popular probability. This approach is applied to study the stochastic properties of the performance functions of a MEMS structure, which has quite large fabrication errors compared to other structures. Especially, the vibratory micro-gyroscope is studied using the statistical moments and probability density function (PDF) of the performance function to be the difference between resonant frequencies corresponding to sensing and driving mode. The results show that it is very sensitive to the fabrication errors and that the types of PDF of each variable also affect the stochastic properties of the performance function although they have same the mean and variance.

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An Accuracy Estimation of AEP Based on Geographic Characteristics and Atmospheric Variations in Northern East Region of Jeju Island (제주 북동부 지역의 지형과 대기변수에 따른 AEP계산의 정확성에 대한 연구)

  • Ko, Jung-Woo;Lee, Byung-Gul
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.3
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    • pp.295-303
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    • 2012
  • Clarify wind energy productivity depends on three factors: the wind probability density function(PDF), the turbine's power curve, and the air density. The wind PDF gives the probability that a variable will take on the wind speed value. Wind shear refers to the change in wind speed with height above ground. The wind speed tends to increase with the height above ground. also, Wind PDF refers to the change with height above ground. Wind analysts typically use the Weibull distribution to characterize the breadth of the distribution of wind speeds. The Weibull distribution has the two-parameter: the scale factor c and the shape factor k. We can use a linear least squares algorithm(or Ln-least method) and moment method to fit a Weibull distribution to measured wind speed data which data was located same site and different height. In this study, find that the scale factor is related to the average wind speed than the shape factor. and also different types of terrain are characterized by different the scale factor slop with height above ground. The gross turbine power output (before accounting for losses) was caculated the power curve whose corresponding air density is closest to the air density. and air desity was choose two way. one is the pressure of the International Standard Atmosphere up to an elevation, the other is the measured air pressure and temperature to calculate the air density. and then each power output was compared.

Dual-Hop Amplify-and-Forward Multi-Relay Maximum Ratio Transmission

  • Erdogan, Eylem;Gucluoglu, Tansal
    • Journal of Communications and Networks
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    • v.18 no.1
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    • pp.19-26
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    • 2016
  • In this paper, the performance of dual-hop multi-relay maximum ratio transmission (MRT) over Rayleigh flat fading channels is studied with both conventional (all relays participate the transmission) and opportunistic (best relay is selected to maximize the received signal-to-noise ratio (SNR)) relaying. Performance analysis starts with the derivation of the probability density function, cumulative distribution function and moment generating function of the SNR. Then, both approximate and asymptotic expressions of symbol error rate (SER) and outage probability are derived for arbitrary numbers of antennas and relays. With the help of asymptotic SER and outage probability, diversity and array gains are obtained. In addition, impact of imperfect channel estimations is investigated and optimum power allocation factors for source and relay are calculated. Our analytical findings are validated by numerical examples which indicate that multi-relay MRT can be a low complexity and reliable option in cooperative networks.

Robust Histogram Equalization Using Compensated Probability Distribution

  • Kim, Sung-Tak;Kim, Hoi-Rin
    • MALSORI
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    • v.55
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    • pp.131-142
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    • 2005
  • A mismatch between the training and the test conditions often causes a drastic decrease in the performance of the speech recognition systems. In this paper, non-linear transformation techniques based on histogram equalization in the acoustic feature space are studied for reducing the mismatched condition. The purpose of histogram equalization(HEQ) is to convert the probability distribution of test speech into the probability distribution of training speech. While conventional histogram equalization methods consider only the probability distribution of a test speech, for noise-corrupted test speech, its probability distribution is also distorted. The transformation function obtained by this distorted probability distribution maybe bring about miss-transformation of feature vectors, and this causes the performance of histogram equalization to decrease. Therefore, this paper proposes a new method of calculating noise-removed probability distribution by using assumption that the CDF of noisy speech feature vectors consists of component of speech feature vectors and component of noise feature vectors, and this compensated probability distribution is used in HEQ process. In the AURORA-2 framework, the proposed method reduced the error rate by over $44\%$ in clean training condition compared to the baseline system. For multi training condition, the proposed methods are also better than the baseline system.

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Analysis on the Performance of $2{\times}1$ Alamouti Scheme in Time-varying and Spatially Correlated Channels (시변 및 공간 상관 채널 환경에서 $2{\times}1$ 알라마우티 구조 (Alamouti Scheme)의 성능 분석)

  • Lee, Eun-Ju;Park, Jae-Don;Yoon, Gi-Wan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.05a
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    • pp.539-542
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    • 2011
  • In this paper, we have implemented a performance analysis of $2{\times}1$ Alamouti scheme suggested by Alamouti, composed of the transmit space-time code and the simple linear decoding processing, in perfectly time-varying and spatially correlated channels. In addition, we derived the closed-form probability density function (PDF) of the output signal-to-noise ratio (SNR) and the outage probability of the Alamouti scheme as a function of the spatial correlation coefficient in the consideration of no correlation in time. As a result, it was found that the performance of the Alamouti scheme could be significantly degraded particularly in the case that the channels are time-varying and spatially correlated.

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Detection of a bias level in prediction errors due to input accelerations (입력 가속에서 비롯된 innovation 바이어스 레벨의 검출)

  • 신해곤;홍순목
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.554-557
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    • 1992
  • In this paper the normalized innovations squared of a Kalman filter is used to detect a bias level in prediction errors due to target accelerations. The probability density function of the normalized innovation squared is obtained for a steady state Kalman filter, and it is used to calculate the detection probability of the bias level. A typical example is given to compute the detection probability.

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