• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.1
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• pp.14-19
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• 2013

Nonlinearity parameter is an inherent property of materials measuring fundamental acoustic amplitude($A_1$) and second harmonic amplitude($A_2$). However, measurement of $A_1$ and $A_2$ has complex calibration procedure, many researchers prefer to measure relative nonlinearity parameter rather than absolute nonlinearity parameter. But, relative nonlinearity parameter is only detect materials degradation with various degradation samples, it is limited application in determining third order elastic constants of materials. Therefore, in this study, the piezoelectric detection method is adopted to measure absolute nonlinearity parameter due to experimental simplicity compare to capacitive detector. Linearity of measurement system is verified by $A_1^2vsA_2$ plot, and we measured ultrasonic nonlinearity parameters of fused silica and Al2024-T4.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1521-1528
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• 2010

This paper examines technical writing and teaching methods based on the perspectives of the complex learning system theory. So, the paper first discusses the constituent elements and characteristics of the complex learning system theory and continues to examine the potential of applying the complex learning system theory to new teaching methods. As a result, not only did the research expand the approach methods of providing technical writing education but also confirmed the potential of actual implementation. Such results will provide a leeway to start applying new teaching methods for technical writing education. Furthermore, the paper proposes more detailed case studies related to this topic as well as development of this research to produce textbooks and other higher level researches.

• Journal of Korean Society of Steel Construction
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• v.20 no.3
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• pp.389-398
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• 2008

The current design practice of electric transmission tower is based on the allowable stress design. However, it is difficult to find the cause behind a transmission tower's collapse by the above design approach as the collapse is caused by large secondary deformations based on and geometrical nonlinear behavior.influence factor for the nonlinear behavior is mainly residual stress, initial imperfection and end restraints on members. In this study, the necessity of the nonlinear analysis is examined through the comparison between elastic ana the nonlinear analysis, a new analytical method (equivalent nonlinear analysis technique) is proposed. To confirm the reliability of the proposed method, the computed ultimate load of the transmission tower using the method was compared with that of the nonlinear finite element analysis. Effects of parameters, such as compressive force and the slenderness ratio of the brace member on the main post member, were investigated. The effective member length according to influential parameters was formulated in table form for practical purposes.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.11
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• pp.1220-1228
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• 2010

In this paper, we suggest a scheme to develop an efficient discrete nonlinear model based on polynomial structure for a RF power amplifier(PA). We describe a procedure to extract a discrete nonlinear model such as Taylor series or memory polynomial by sampling the input and output signal of RF PA. The performance of the model is analyzed varying the model parameters such as sample rate, nonlinear order, and memory depth. The results show that the relative error of the model is converged if the parameters are larger than specific values. We suggest an efficient modeling scheme considering complexity of the discrete model depending on the values of the model parameters. Modeling efficiency index(MEI) is defined, and it is used to extract optimum values for the model parameters. The suggested scheme is applied to discrete modeling of various RF PAs with various input signals such as WCDMA, WiBro, etc. The suggested scheme can be applied to the efficient design of digital predistorter for the wideband transmitter.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.203-209
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• 2016

In this paper, we introduce a fuzzy inference systems for nonlinear inference using fuzzy cluster. Typically, the generation of fuzzy rules for nonlinear inference causes the problem that the number of fuzzy rules increases exponentially if the input vectors increase. To handle this problem, the fuzzy rules of fuzzy model are designed by dividing the input vector space in the scatter form using fuzzy clustering algorithm which expresses fuzzy cluster. From this method, complex nonlinear process can be modeled. The premise part of the fuzzy rules is determined by means of FCM clustering algorithm with fuzzy clusters. The consequence part of the fuzzy rules have four kinds of polynomial functions and the coefficient parameters of each rule are estimated by using the standard least-squares method. And we use the data widely used in nonlinear process for the performance and the nonlinear characteristics of the nonlinear process. Experimental results show that the non-linear inference is possible.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.71-76
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• 2023

This paper studied a method of attenuating nonlinear noise using a Wiener filter of a neural network structure in an acoustic noise attenuator. This system improves nonlinear noise attenuation performance with a deep learning algorithm using a neural network Wiener filter instead of using a conventional adaptive filter. A voice is estimated from a single input voice signal containing nonlinear noise using a 128-neuron, 8-neuron hidden layer and an error back propagation algorithm. In this study, a simulation program using the Keras library was written and a simulation was performed to verify the attenuation performance for nonlinear noise. As a result of the simulation, it can be seen that the noise attenuation performance of this system is significantly improved when the FNN filter is used instead of the Wiener filter even when nonlinear noise is included. This is because the complex structure of the FNN filter expresses any type of nonlinear characteristics well.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.10
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• pp.1012-1015
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• 2011

The decision-directed blind equalization algorithm is often used due to its simplicity and good convergence property when the eye pattern is open. However, in a channel where the eye pattern is closed, the decision-directed algorithm is not guaranteed to converge. Hence, a modified Bussgang-type algorithm using a hyperbolic tangent function for zero-memory nonlinear(ZNL) function has been proposed and applied to avoid this problem by Filho et al. But application of this algorithm includes the calculation of hyperbolic tangent function and its derivative or a look-up table which may need a large amount of memory due to channel variations. To reduce the computational and/or hardware complexity of Filho's algorithm, in this paper, an improved method for the decision-directed algorithm is proposed. In the proposed scheme, the ZNL function and its derivative are respectively set to be the original signum function and a narrow rectangular pulse which is an approximation of Dirac delta function. It is shown that the proposed scheme, when it is combined with decision-directed algorithm, reduces the computational complexity drastically while it retains the convergence and steady-state performance of the Filho's algorithm.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.258-264
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• 2016

In this paper, we propose a computationally efficient direction of arrival (DoA) estimation algorithm based on propagator method with non-uniform array. While the co-prime array techniques can improve the resolution of DoA, they generally lead to high computational complexity as the length of the coarray aperture. To reduce the complexity we use the propagator method that does not require singular value decomposition (SVD). Through simulations, we compare MUSIC with uniform lineary array, propagator method with uniform linear array, MUSIC with co-prime array, and the proposed scheme and observe that the performance of the proposed scheme is significantly better than MUSIC or propagator method with uniform linear array while it is slightly worse than computationally much more expensive co-prime array MUSIC scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5A
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• pp.305-315
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• 2003

MC-CDMA(Multicarrier code division multiple access), which is based on a combination of OFDM(orthogonal frequency division multiplexing) and CDMA(code division multiple access), has gained a lot of interests in wireless multimedia communications, as high speed data transmission is required for mobile services. MC-CDMA has many advantages for broadband high speed data transmission in multipath environment because it can offer both advantages of the CDMA and the OFDM. However, A high PAPR(peak to average power ratio) problem, which is a major drawback of OFDM, is also shown in the MC-CDMA. In this paper, we propose a new phase factor optimization scheme to reduce complexity in PTS(partial transmit sequence) to reduce PAPR. We also analyze the performance of the MC-CDMA with various PTS schemes to investigate the relations between PAPR characteristics and effect of nonlinear distortion of a high power amplifier. Our simulation results reveal that the proposed PTS scheme reduces PAPR about 0.2∼0.5 dB even with 25% reduced- complexity compared to the conventional scheme.

• The Magazine of the IEIE
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• v.18 no.10
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• pp.29-38
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• 1991

제6세대 컴퓨터로 불리는 신경컴퓨터는 학습과 병렬처리에 의해 인간의 두뇌 기능을 모방한다. 인간의 두뇌는 시각 인식, 음성인식, 촉각 감지등 패턴 인식뿐 아니라 인간의 복잡한 신체구조를 시각, 촉각 같은 감각기관의 도움을 얻어 움직이는 중요한 역할도 한다. 바로 이 모터제어(motor control)역시 신경회로가 담당하기 때문에 이를 기계적 신체에 해당하는 로봇 또는 광범위하게 기계, 비행기, 산업공정에 응용하는 것은 매우 자연스럽게 보인다. 이처럼 신경회로가 제어에 응용되는 것을 신경제어(neurocontrol)라 하고 이를 이용한 기계를 지능기계(intelligent machinery)라 한다. 지능기계는 기본적으로 인간처럼 경험축적, 학습, 불확실한 환경에서의 적응, 자기진단 등의 장점을 가지고 있다. 신경회로의 지극히 광범위한 응용분야중 신경제어는 가장 먼저 실현될 가능성이 높다. 실제로 로봇나 공정제어(process control)처럼 복잡한 비선형 시스템의 제어는 다량의 센서 정보에 기초한 실시한 제어를 필수로 하며 이는 신경회로를 사용함으로써 가장 효율적, 경제적으로 구현할 수 있다. 실제로 신경제어는 전세계적으로 이미 시스템 제어에 응용되어 좋은 결과를 내고 있다. 신경회로의 로봇나 자동화 응용은 학술적인 측면에서는 복잡한 비선형 시스템의 지능제어(intelligent control)문제에 대한 신선한 해결책을 마련해줄 뿐 아니라 산업자동화라는 막대한 시장을 뒤로 하고 있어 이론에서 실제에 걸쳐 가장 광범위한 파급효과를 가지는 최첨단 기술로 보여진다. 고부가가치 상품을 통한 국제경쟁력 제고의 차원에서도 정부, 기업 등의 과감한 연구 개발투자가 선행되어야 한다. 특히 이 분야의 연구는 선진국도 최근에 시작한 점으로 보아 정부, 기업이 이에 대한 연구개발 투자를 현명하게 할 경우에 세계적 기술 경쟁력도 확보할 수 있을 것이다. 본 해설에서는 로봇 및 시스템 제어에 관한 기초 이론과 신경회로 적용기술을 소개하고 기존방법과 비교했을 때의 우월성, 전세계적인 응용연구, 국내외 연구개발 현황, 상업화 가능성, 산업계 응용례, 기술상의 문제점, 향후 전망 등을 다루기로 한다.