• Title/Summary/Keyword: S-Transform

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A MARKOVIAN APPROACH TO THE FORWARD RECURRENCE TIME IN THE RENEWAL PROCESS

  • Kim, Jong-Woo;Lee, Eui-Yong;Shim, Gyoo-Cheol
    • Journal of the Korean Statistical Society
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    • v.33 no.3
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    • pp.299-302
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    • 2004
  • A Markovian approach is introduced to find the Laplace transform of the forward recurrence time in the renewal process at finite time t > 0. Until now, most works on the forward recurrence time have been done through renewal arguments.

NEW SEVEN-PARAMETER MITTAG-LEFFLER FUNCTION WITH CERTAIN ANALYTIC PROPERTIES

  • Maryam K. Rasheed;Abdulrahman H. Majeed
    • Nonlinear Functional Analysis and Applications
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    • v.29 no.1
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    • pp.99-111
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    • 2024
  • In this paper, a new seven-parameter Mittag-Leffler function of a single complex variable is proposed as a generalization of the standard Mittag-Leffler function, certain generalizations of Mittag-Leffler function, hypergeometric function and confluent hypergeometric function. Certain essential analytic properties are mainly discussed, such as radius of convergence, order, type, differentiation, Mellin-Barnes integral representation and Euler transform in the complex plane. Its relation to Fox-Wright function and H-function is also developed.

Outlier Detection Based on Discrete Wavelet Transform with Application to Saudi Stock Market Closed Price Series

  • RASHEDI, Khudhayr A.;ISMAIL, Mohd T.;WADI, S. Al;SERROUKH, Abdeslam
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.12
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    • pp.1-10
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    • 2020
  • This study investigates the problem of outlier detection based on discrete wavelet transform in the context of time series data where the identification and treatment of outliers constitute an important component. An outlier is defined as a data point that deviates so much from the rest of observations within a data sample. In this work we focus on the application of the traditional method suggested by Tukey (1977) for detecting outliers in the closed price series of the Saudi Arabia stock market (Tadawul) between Oct. 2011 and Dec. 2019. The method is applied to the details obtained from the MODWT (Maximal-Overlap Discrete Wavelet Transform) of the original series. The result show that the suggested methodology was successful in detecting all of the outliers in the series. The findings of this study suggest that we can model and forecast the volatility of returns from the reconstructed series without outliers using GARCH models. The estimated GARCH volatility model was compared to other asymmetric GARCH models using standard forecast error metrics. It is found that the performance of the standard GARCH model were as good as that of the gjrGARCH model over the out-of-sample forecasts for returns among other GARCH specifications.

Wavelet Transform Technology for Translation-invariant Iris Recognition (위치 이동에 무관한 홍채 인식을 위한 웨이블렛 변환 기술)

  • Lim, Cheol-Su
    • The KIPS Transactions:PartB
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    • v.10B no.4
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    • pp.459-464
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    • 2003
  • This paper proposes the use of a wavelet based image transform algorithm in human iris recognition method and the effectiveness of this technique will be determined in preprocessing of extracting Iris image from the user´s eye obtained by imaging device such as CCD Camera or due to torsional rotation of the eye, and it also resolves the problem caused by invariant under translations and dilations due to tilt of the head. This technique values through the proposed translation-invariant wavelet transform algorithm rather than the conventional wavelet transform method. Therefore we extracted the best-matching iris feature values and compared the stored feature codes with the incoming data to identify the user. As result of our experimentation, this technique demonstrate the significant advantage over verification when it compares with other general types of wavelet algorithm in the measure of FAR & FRR.

Synchronous Generator Protective Algorithm using Wavelet Transform of Fault Currents (고장전류의 웨이브릿 변환을 이용한 동기 발전기 보호 알고리즘)

  • Park, Chul-Won;Shin, Myong-Chul
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.5
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    • pp.834-840
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    • 2007
  • A generator plays an important role in transferring an electric power to power system networks. The generator protection systems in Korea have been imported and operated through a tum-key from overseas entirely. Therefore, a study of the generator protection field has in urgent need for a stable operation of the imported goods, and for preparation of next generation protection system. The paper describes the fault detection algorithm using WT(Wave!et Transform) of currents for a generator protection. The fault current signals after executing a terminal fault modeling collect using a MA TLAB package, and calculate the wavelet coefficients through the process of a multi -level decomposition (MLD). The proposed algorithm for a fault detection using the Daubechies WT (wavelet transform) was executed with a C language for the command line function and for the real time realization after analyzing MATLAB's graphical interface. The advanced technique had complemented the defects of a DFT by applying a Daubechies WT. and had improved faster a speed and more accurate of fault discriminant than a conventional DFR.

Free and transient responses of linear complex stiffness system by Hilbert transform and convolution integral

  • Bae, S.H.;Cho, J.R.;Jeong, W.B.
    • Smart Structures and Systems
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    • v.17 no.5
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    • pp.753-771
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    • 2016
  • This paper addresses the free and transient responses of a SDOF linear complex stiffness system by making use of the Hilbert transform and the convolution integral. Because the second-order differential equation of motion having the complex stiffness give rise to the conjugate complex eigen values, its time-domain analysis using the standard time integration scheme suffers from the numerical instability and divergence. In order to overcome this problem, the transient response of the linear complex stiffness system is obtained by the convolution integral of a green function which corresponds to the unit-impulse free vibration response of the complex system. The damped free vibration of the complex system is theoretically derived by making use of the state-space formulation and the Hilbert transform. The convolution integral is implemented by piecewise-linearly interpolating the external force and by superimposing the transient responses of discretized piecewise impulse forces. The numerical experiments are carried out to verify the proposed time-domain analysis method, and the correlation between the real and imaginary parts in the free and transient responses is also investigated.

Abnormal Detection of CTLS Aircraft Wing Structure using SWT (SWT를 이용한 CTLS항공기 날개 구조물 이상탐지)

  • Shin, Hyun-Sung;Hong, Gyo-Young
    • Journal of Advanced Navigation Technology
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    • v.22 no.5
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    • pp.359-366
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    • 2018
  • In this paper, the noise is removed by using CTLS aircraft installed FBG sensor inside the aircraft wing. We suggest a normal wavelet transform scheme with motion - invariant characteristics for noise reduction. In the case of installing FBG sensors inside the composite material as in CTLS, large and small empty spaces and parts or sections are generated between the adhesive layers, and a signal splitting problem occurs. FBG sensor is not affected by noise. but eletromagnetic, light source, light detector and signal processing device are influeced by noise because these are eletronic components what affected by eletromagnetic wave. because of this, errors are occured. Experimental results show that the noise can be removed using normal wavelet transform and more accurate data detection is possible.

A New Image Clustering Method Based on the Fuzzy Harmony Search Algorithm and Fourier Transform

  • Bekkouche, Ibtissem;Fizazi, Hadria
    • Journal of Information Processing Systems
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    • v.12 no.4
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    • pp.555-576
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    • 2016
  • In the conventional clustering algorithms, an object could be assigned to only one group. However, this is sometimes not the case in reality, there are cases where the data do not belong to one group. As against, the fuzzy clustering takes into consideration the degree of fuzzy membership of each pixel relative to different classes. In order to overcome some shortcoming with traditional clustering methods, such as slow convergence and their sensitivity to initialization values, we have used the Harmony Search algorithm. It is based on the population metaheuristic algorithm, imitating the musical improvisation process. The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. We propose in this paper a new unsupervised clustering method called the Fuzzy Harmony Search-Fourier Transform (FHS-FT). It is based on hybridization fuzzy clustering and the harmony search algorithm to increase its exploitation process and to further improve the generated solution, while the Fourier transform to increase the size of the image's data. The results show that the proposed method is able to provide viable solutions as compared to previous work.

Wavelet transform-based hierarchical active shape model for object tracking (객체추적을 위한 웨이블릿 기반 계층적 능동형태 모델)

  • Kim Hyunjong;Shin Jeongho;Lee Seong-won;Paik Joonki
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.11C
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    • pp.1551-1563
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    • 2004
  • This paper proposes a hierarchical approach to shape model ASM using wavelet transform. Local structure model fitting in the ASM plays an important role in model-based pose and shape analysis. The proposed algorithm can robustly find good solutions in complex images by using wavelet decomposition. we also proposed effective method that estimates and corrects object's movement by using Wavelet transform-based hierarchical motion estimation scheme for ASM-based, real-time video tracking. The proposed algorithm has been tested for various sequences containing human motion to demonstrate the improved performance of the proposed object tracking.

Prediction of Flashover and Pollution Severity of High Voltage Transmission Line Insulators Using Wavelet Transform and Fuzzy C-Means Approach

  • Narayanan, V. Jayaprakash;Sivakumar, M.;Karpagavani, K.;Chandrasekar, S.
    • Journal of Electrical Engineering and Technology
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    • v.9 no.5
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    • pp.1677-1685
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    • 2014
  • Major problem in the high voltage power transmission line is the flashover due to polluted ceramic insulators which leads to failure of equipments, catastrophic fires and power outages. This paper deals with the development of a better diagnostic tool to predict the flashover and pollution severity of power transmission line insulators based on the wavelet transform and fuzzy c-means clustering approach. In this work, laboratory experiments were carried out on power transmission line porcelain insulators under AC voltages at different pollution conditions and corresponding leakage current patterns were measured. Discrete wavelet transform technique is employed to extract important features of leakage current signals. Variation of leakage current magnitude and distortion ratio at different pollution levels were analyzed. Fuzzy c-means algorithm is used to cluster the extracted features of the leakage current data. Test results clearly show that the flashover and pollution severity of power transmission line insulators can be effectively realized through fuzzy clustering technique and it will be useful to carry out preventive maintenance work.