• Title/Summary/Keyword: Wavelet Function

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A Study on the Performance Analysis of 4-ary Scaling Wavelet Shift Keying (4-ary 스케일링 웨이브릿 편이 변조 시스템의 성능 분석에 관한 연구)

  • Jeong, Tae-Il;Ryu, Tae-Kyung;Kim, Jong-Nam;Moon, Kwang-Seok;Kim, Hyun-Deok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.5
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    • pp.1155-1163
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    • 2010
  • An algorithm of the conventional wavelet shift keying is carried out that the scaling function and wavelet are encoded to 1(mark) and 0(space) for the input binary data, respectively. Two bit modulation technique which uses four carrier frequencies is existed. Four carrier frequencies are defined as scaling function, inversed scaling function, wavelet, and inversed wavelet, which are encoded to 10, 11, 00 and 01, respectively. In this paper, we defined 4-ary SWSK (4-ary scaling wavelet shift keying) which is two bit modulation, and it is derived to the probability of bit error and symbol error of the defined system from QPSK. In order to analyze to the performance of 4-ary SWSK, we are obtained in terms of the probability of bit error and symbol error for QPSK (quadrature phase shift keying), MFSK(M-ary frequency shift keying) and proposed method. As a results of simulation, we confirmed that the proposed method was superior to the performance in terms of the probability of bit error and symbol error.

Noise Cancellation of Thoracic Sound Using Wavelet Transform (웨이브렛 변환을 이용한 흉부음의 잡음 제거)

  • 황향자;최규훈;박기영;박강서;김종교
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2244-2247
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    • 2003
  • In this paper, we present a method which can minimize distortion from desired signal in thoracic sound signal processing. We firstly chose the proper wavelet mother function to reduce noise components. Secondly, we chose a clean thoracic sound, then added Gaussian noise and 3 step(10, 15, 20db) uniform noise to it. Finally, the various wavelet functions are applied for noise cancellation. To evaluate the efficiency of this study, we computed SNR and RSE value. Then we found the optimal mother wavelet function for thoracic sound.

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A Design of the PID controller Using Wavelet Neural network (웨이브렛 신경망을 이용한 PID제어기의 설계)

  • 하홍곤
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.17 no.1
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    • pp.74-79
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    • 2003
  • In this paper, the PID controller is constructed with a neural network and wavelet function. And the wavelet neural PID controller is adapted by choosing the values of the dilation and translation parameter of the wavelet function. Weights are adjusted by the inverse propagation algolithm. Applying this method to the position control system, its usefulness is verified from the results of experiment.

Bayesian Methods for Wavelet Series in Single-Index Models

  • Park, Chun-Gun;Vannucci, Marina;Hart, Jeffrey D.
    • 한국데이터정보과학회:학술대회논문집
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    • 2005.04a
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    • pp.83-126
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    • 2005
  • Single-index models have found applications in econometrics and biometrics, where multidimensional regression models are often encountered. Here we propose a nonparametric estimation approach that combines wavelet methods for non-equispaced designs with Bayesian models. We consider a wavelet series expansion of the unknown regression function and set prior distributions for the wavelet coefficients and the other model parameters. To ensure model identifiability, the direction parameter is represented via its polar coordinates. We employ ad hoc hierarchical mixture priors that perform shrinkage on wavelet coefficients and use Markov chain Monte Carlo methods for a posteriori inference. We investigate an independence-type Metropolis-Hastings algorithm to produce samples for the direction parameter. Our method leads to simultaneous estimates of the link function and of the index parameters. We present results on both simulated and real data, where we look at comparisons with other methods.

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Chatter Detection for Improving Surface Quality of Hard Turning Process with Wavelet Transformation (Wavelet을 이용하여 하드터닝 공정에서 표면품위의 향상을 위한 채터 진단에 관한 연구)

  • 박영호;공정흥;양희남;김일해;장동영;한동철
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.1
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    • pp.70-78
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    • 2004
  • This paper presents study of efficiency of wavelet transformation for on-line chatter detection during hard fuming process. From comparison with other time series and statistical methods such as fast fourier transformation (FFT), Kurtosis and standard deviation (STD), wavelet transform is better than others in on-line chatter detection. With using wavelet function with pseudo frequency corresponding to chatter frequency, chatter could be detected more sensitively. And for both force signal from dynamometer and displacement signal from capacitance type cylindrical sensor (CCS), wavelet transform with DB2 function on level 4 could be well used for chatter detection in hard turning process.

A study on print estimation using wavelet transformation method (Wavelet 변환 방식을 이용한 인쇄물 평가에 관한 연구)

  • 김택준;조가람;구철희
    • Journal of the Korean Graphic Arts Communication Society
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    • v.20 no.1
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    • pp.28-44
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    • 2002
  • Wavelet transformation in image compression is to offer higher image compressibility and high-quality by quantization and entropy encoding. More image quality is good that reconstructed image by wavelet calculation than acquire cosine transform. Therefore, wavelet itself is function if it is wavelet's feature, in this function, do processing applying difference scale and resolution. That is, this is not that fixed resolution has been decided like existent compression way, when it regulated scale, damage goes in pixel and picture looks like break without giving damage entirely in reflex even if magnify or curtail Decoding. Therefore, this paper is in Image that using new wavelet application compression way research that see applies comparing In each image noted this time compressing step by step with circle image compression efficiency recognize. Also, estimated quality pass through by printing of compressed image, investigated compression ratio of most suitable that get print of high quality and elevation of transmission speed.

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ASYMPTOTIC NORMALITY OF WAVELET ESTIMATOR OF REGRESSION FUNCTION UNDER NA ASSUMPTIONS

  • Liang, Han-Ying;Qi, Yan-Yan
    • Bulletin of the Korean Mathematical Society
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    • v.44 no.2
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    • pp.247-257
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    • 2007
  • Consider the heteroscedastic regression model $Y_i=g(x_i)+{\sigma}_i\;{\epsilon}_i=(1{\leq}i{\leq}n)$, where ${\sigma}^2_i=f(u_i)$, the design points $(x_i,\;u_i)$ are known and nonrandom, and g and f are unknown functions defined on closed interval [0, 1]. Under the random errors $\epsilon_i$ form a sequence of NA random variables, we study the asymptotic normality of wavelet estimators of g when f is a known or unknown function.

HIGH ACCURACY POINTS OF WAVELET APPROXIMATION

  • Kwon, Soon-Geol
    • Journal of applied mathematics & informatics
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    • v.27 no.1_2
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    • pp.69-78
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    • 2009
  • The accuracy of wavelet approximation at resolution h = $2^{-k}$ to a smooth function f is limited by O($h^M$), where M is the number of vanishing moments of the mother wavelet ${\psi}$; that is, the approximation order of wavelet approximation is M - 1. High accuracy points of wavelet approximation are of interest in some applications such as signal processing and numerical approximation. In this paper, we prove the scaling and translating properties of high accuracy points of wavelet approximation. To illustrate the results in this paper, we also present two examples of high accuracy points of wavelet approximation.

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Growing Algorithm of Wavelet Neural Network (웨이블렛 신경망의 성장 알고리즘)

  • 서재용;김성주;김성현;김용민;전홍태
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.05a
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    • pp.57-60
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    • 2001
  • In this paper, we propose growing algorithm of wavelet neural network. It is growing algorithm that adds hidden nodes using wavelet frame which approximately supports orthogonality in wavelet neural network based on wavelet theory. The result of this processing can be reduced global error and progresses performance efficiency of wavelet neural network. We apply the proposed algorithm to approximation problem and evaluate effectiveness of proposed algorithm.

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Identification of Track Irregularity using Wavelet Transfer Function (웨이브렛 전달함수를 이용한 궤도틀림 식별)

  • Shin, Soo-Bong;Lee, Hyeung-Jin;Kim, Man-Cheol;Yoon, Seok-Jun
    • Journal of the Korean Society for Railway
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    • v.13 no.3
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    • pp.304-308
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    • 2010
  • This paper presents a methodology for identifying track irregularity using a wavelet transfer function. An equivalent wavelet SISO (single-input single-output) transfer function is defined by the measured track geometry and the acceleration data measured at a bogie of a train. All the measured data with various sampling frequencies were rearranged according to the constant 25cm reference recording distance of the track recording vehicle used in the field. Before applying the wavelet transform, measured data were regressed by eliminating those out of the range. The inverse wavelet transfer function is also formulated to estimate track geometry. The closeness of the estimated track geometry to the actual one is evaluated by the coherence function and also by FRF (frequency response function). A track irregularity index is defined by comparing the variance of the estimation error from the intact condition and that from the current condition. A simulation study has been carried out to examine the proposed algorithm.