• Journal of the Korea Society of Computer and Information
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• v.3 no.1
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• pp.81-94
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• 1998

In order to extract the contour of interesting object in the image, Kass suggested the Active Contour Model called "Snakes". Snakes is a model which defines the contour of image energy. It also can find the contour of object by minimizing these energy functions. The speed of this model is slow and this model is sensitive of initialization. In order to improve these problems, Gunn extracted the accurate contour by using two initialization. and operated to less sensitive of initialization. This method could extract more accurate contour than the existing method, but it had no effect in the speed and it was sensitive of noise. This paper applied to the Energy Minimization Algorithm about only the pixel within the window applying the window of 8$\times$8 size at each contour point consisting Snakes in order to solve these problems. The method offered in this paper is applied to extract the contour of original image and cup image added to gaussian noise. By tracking the face using this offered method, it is applied to virtual reality and motion tracking. tracking.

• Journal of the Korean Society for Nondestructive Testing
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• v.16 no.1
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• pp.1-9
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• 1996

Many signal-processing techniques have been found to be useful in ultrasonic and nondestructive evaluation. Among the most popular techniques are signal averaging, spatial compounding, matched filters and homomorphic processing. One of the significant new process is split-spectrum processing(SSP), which can be equally useful in signal-to-noise ratio(SNR) improvement and grain characterization in several specimens. The purpose of this paper is to explore the utility of SSP in ultrasonic NDE. A wide variety of engineering problems are reviewed, and suggestions for implementation of the technique are provided. SSP uses the frequency-dependent response of the interfering coherent noise produced by unresolvable scatters in the resolution range cell of a transducer. It is implemented by splitting the frequency spectrum of the received signal by using gaussian bandpass filter. The theoretical basis for the potential of SSP for grain characterization in SUS 304 material is discussed, and some experimental evidence for the feasibility of the approach is presented. Results of SNR enhancement in signals obtained from real four samples of SUS 304. The influence of various processing parameters on the performance of the processing technique is also discussed. The minimization algorithm, which provides an excellent SNR enhancement when used either in conjunction with other SSP algorithms like polarity-check or by itself, is also presented.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.57-67
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• 1998

In order to extract the contour of interesting object in the image, Kass suggested the Active Contour Model called "Snakes" The speed of this model is slow and this model is sensitive of initialization. In order to improve these problems, Gunn extracted the accurate contour by using two initializations, and operated to less sensitive of initialization. This method could extract more accurate contour than the existing method, but it had no effect in the speed and it was sensitive of noise. This paper applied to the Energy Minimization Algorithm about only the pixel within the window applying the window of $8{\times}8$ size at each contour point consisting Snakes in order to solve these problems. In order to less sensitive of noise which exists within image, it suggests a method that moves the window to vertical direction for the gradient of each contour point.our point.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.55-61
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• 2014

This paper related with the ECMA (Enchanced CMA) algorithm performance which is possible to simultaneously compensation of the amplitude and phase by appling the minimum disturbance techniques in the CMA adatpve equalizer. The ECMA can improving the gradient noise amplification problem, stability and roburstness performance by the minimum disturbance technique that is the minimization of the equalizer tap weight variation in the point of squared euclidiean norm and the decision directed mode, and then the now cost function were proposed in order to simultaneouly compensation of amplitude and phase of the received signal with the minimum increment of computational operations. The performance of ECMA algorithm was compared to present MCMA by the computer simulation. For proving the performance, the recovered signal constellation that is the output of equalizer output signal and the residual isi and Maximum Distortion charateristic and MSE learning curve that are presents the convergence performance in the equalizer and the overall frequency transfer function of channel and equalizer were used. As a result of computer simulation, the ECMA has more better compensation capability of amplitude and phase in the recovered constellation, and the convergence time of adaptive equalization has improved compared to the MCMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.105-110
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• 2015

This paper relates with the eualization performance of Constellation Matching-MMA (CM-MMA) in order to the consists of optimum receiver for the minimization of intersymbol interference and additive noise effects that is occurs in the nonlinear communication channel. The error signal were obtained that combines the Constellation Matching technique that inserts the zero point between the signal point of equalizer for improving the residual isi and convergence speed compared to the currently used MMA algorithm. In the initial state of adaptive equalization, it depends on the MMA characteristics mainly. And in the steady state, it depends on the CM characteristics mainly. In order to analyzing the equalization performance, the output signal constellation, residual isi, maximum distortion, MSE and SER were applied, then it were compared with the present MMA algorithm. As a result of computer simulation, the CM-MMA has more better performance in the every performance index, and it was also confirmed that the constellation matching effect can be obtained in the greater than 20dB signal to noise ratio.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.30-36
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• 2000

In this paper, an ultrasonic testing method for inspection of high attenuation welding area using the minimum Polarity threshold algorithm which combines the minimum amplitude selection algorithm and polarity threshold algorithm is suggested to increase the signal to noise ratio of the flow signal. In order to confirm the usefulness of the suggested algorithm, experiments were performed using four probes and standard specimens following the ASME Xl Code. As a result, scattering signals were observed from the SE(safe end) and CCSS (centrifugal casting stainless steel) materials due to the microstructural characteristical, and the detectability was reduced due to the highly attenuated signal from the weldment area, but it was conformed that using the suggested algorithm, the signal to noise ratio increased about 2.6.

• The Journal of the Acoustical Society of Korea
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• v.14 no.6
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• pp.27-31
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• 1995

In this paper, the determination method of available bandwidth for automation of the split-spectrum processing(SSP) has been studied. The SSP is used for the visibility enhancement of the ultrasonic signal with grain noise. Even though the SSP has proved useful in signal-to-noise ratio enhancement, its application and automation have been limited due to ambiguity in the determination of available bandwidth. Until recently, it is the usual practice to optimize the available bandwidth by trial and error. The spectral histogram is the statistical distribution of the spectral windows that is selected by the minimization algorithm with the whole band of the spectrum of the received ultrasonic signal. Since the available bandwidth can be determined adaptively using spectral histogram, this method can be used for automation of the SSP. In order to evaluate the determination technique of the available bandwidth using spectral histogram, this method is applied to experimental ultrasonic data. The experimental results show that the spectral histogram is an efficient method for determination of the available bandwidth and automation of the SSP.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.797-804
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• 2013

This paper presents an efficient design method of multiplierless 2-D state space digital filter based on a particle swarm optimization(PSO) algorithm. The design task is reformulated as a constrained minimization problem and is solved by our newly developed PSO algorithm. To ensure the stability of the designed 2-D state space digital filters, a stability strategy is embedded in the basic PSO algorithm. The superiority of the proposed method is demonstrated by several experiments. The results show that the approximation error and roundoff noise of the resultant filters are better than those of the digital filters which designed by recently published filter design methods. In addition, the designed filters with power-of-two coefficients have only about 1/4 computational burden of the 2-D digital filters designed in the 2's complement binary representation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.127-133
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• 2013

This paper compare the performance of CCA (Compact Constellation Algorithm) adaptive equalization algorithm by effect of the compact slice weighting value for minimization of the intersymbol interference in the communication channel. The CCA combines the conventional DDA and RCA algorithm, it uses the constant modulus of the transmission signal and the considering the output of decision device by the power of compact slice weighting value in order to improving the initial convergence characteristics and the equalization noise by misadjustment in the steady state. In this process, it is confirmed by computer simulation that the compact slice weight affects the performance of CCA adaptive equalization algorithm. The performance index includes the output signal constellation, the residual isi and maximum distortion and MSE that is for the convergence characteristics, the SER according to the signal and noise power ratio at the channel is used. As a result of computer, it shows that the large weighting value gives more good in every performance index. But in SER performance, it is known that the small values gives more good in low SNR and the large values gives more good in high SNR.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1772-1781
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• 2017

In this study, the design methodology for alleviating the overfitting problem of Polynomial Neural Networks(PNN) is realized with the aid of two kinds techniques such as L2 regularization and Sum of Squared Coefficients (SSC). The PNN is widely used as a kind of mathematical modeling methods such as the identification of linear system by input/output data and the regression analysis modeling method for prediction problem. PNN is an algorithm that obtains preferred network structure by generating consecutive layers as well as nodes by using a multivariate polynomial subexpression. It has much fewer nodes and more flexible adaptability than existing neural network algorithms. However, such algorithms lead to overfitting problems due to noise sensitivity as well as excessive trainning while generation of successive network layers. To alleviate such overfitting problem and also effectively design its ensuing deep network structure, two techniques are introduced. That is we use the two techniques of both SSC(Sum of Squared Coefficients) and $L_2$ regularization for consecutive generation of each layer's nodes as well as each layer in order to construct the deep PNN structure. The technique of $L_2$ regularization is used for the minimum coefficient estimation by adding penalty term to cost function. $L_2$ regularization is a kind of representative methods of reducing the influence of noise by flattening the solution space and also lessening coefficient size. The technique for the SSC is implemented for the minimization of Sum of Squared Coefficients of polynomial instead of using the square of errors. In the sequel, the overfitting problem of the deep PNN structure is stabilized by the proposed method. This study leads to the possibility of deep network structure design as well as big data processing and also the superiority of the network performance through experiments is shown.