• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.93.3-93
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• 2001

We propose the cascade PID type fuzzy control method for a good performance such as robustness. The one of proposed method, the first stage have two input variables of an error and a derivative error, and one output variable, and the next stage have two input variables of the output of first stage and an integral error, and one output variable, have two stages. The other, the first stage has one input of an error, and one output variable, and the second stage have two input of the output of first stage and a derivative error, and one output variable, and the third stage have two input of the output of the second stage and an integer error, and one output variable ...

• Land and Housing Review
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• v.9 no.4
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• pp.33-42
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• 2018

As a radiant heating panel gets more popularity, the need to study on evaluation method of thermal output of the panel also becomes increasing. Generally, the chamber using method is applied to evaluate the thermal output through an experiment. However, the chamber using method cannot be used due to the limitations on space and cost. EN1264 addresses the test equipment to evaluate the thermal output by using simpler experimental setup, and introduces application method in detail. However, there is not enough description of control methods to meet the experiment condition, and it is difficult to meet this when practical experiment. Therefore, this paper analysed the control error factors of when the thermal output experiment is performed. When EN1264 method is applied to evaluate the thermal output of the radiant floor heating panel, the error factor which is caused by the characteristic of test equipment cannot be removed by the control methods of chamber using method. In addition, the error factor can be occurred at the element which is located out of the control system. These possible error factors are defined as the characteristic error factors.

• Journal of the Korean Society of Safety
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• v.39 no.2
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• pp.65-74
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• 2024

We analyzed the relationship between the normal measurement of the seismic accelerometer (SA) and the error rate of the output voltage linear ratio to propose an evaluation method to determine whether the SA in use is measuring normally. Utilizing a test bed, the regular operation of SA in use was evaluated using acceleration data measured through impact tests since there are no regulations regarding performance testing of SA in use. For the used SA, the error rate of the output voltage linear ratio, which is a major performance criterion, was evaluated. We analyzed common characteristics of the SA that satisfied the impact test and the performance criteria of the output voltage linear ratio error rate. The results indicated that we must consider the decreasing trend and convergence of the error rate as the measurement angle increases, ensuring that the average value of the output voltage linear ratio error rate is within 1%.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1285-1288
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• 1998

In this paper, we propose a new learning algorithm for multilayer neural networks. In the error backpropagation that is widely used for training multilayer neural networks, weights are adjusted to reduce the error function that is sum of squared error for all the neurons in the output layer of the network. In the proposed learning algorithm, we consider each output of the output layer as a function of weights and adjust the weights directly so that the output neurons produce the desired outputs. Experiments show that the proposed algorithm outperforms the backpropagation learning algorithm.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.1
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• pp.34-42
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• 1992

This paper presents two fast least-squares lattice algorithms for adaptive nonlinear filters equipped with bilinear system models. The lattice filters perform a Gram-Schmidt orthogonalization of the input data and have very good numerical properties. Furthermore, the computational complexity of the algorithms is an order of magnitude snaller than previously algorithm is an order of magnitude smaller than previously available methods. The first of the two approaches is an equation error algorithm that uses the measured desired response signal directly to comprte the adaptive filter outputs. This method is conceptually very simple`however, it will result in biased system models in the presence of measurement noise. The second approach is an approximate least-squares output error solution. In this case, the past samples of the output of the adaptive system itself are used to produce the filter output at the current time. Results of several experiments that demonstrate and compare the properties of the adaptive bilinear filters are also presented in this paper. These results indicate that the output error algorithm is less sensitive to output measurement noise than the squation error method.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.316-318
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• 1992

The proposed algorithm uses a modified adaptive law which consists of switching -modification, normalized augmented error and low-pass filtered signal of output tracking error, furthermore, the proportional term that is a product of the output tracking error and the bounded signal having an information of output tracking error is added to the conventional control law for improvement of robustness and performance of an adaptive system. For the arbitrary nth order system, mathematical analysis and computer simulation are used to demonstrate improvement of output error characteristics, guaranteeing boundedness of all signals in the overall system.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.169-172
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• 1996

A modified output error method developed by the authors are presented, and an example of its application on an air accident is shown. In order to obtain the aerodynamic coefficients of an aircraft, the maximum likelihood method and the output error method are often employee However, in the case of an air accident, there is only one flight data available. The newly devised modified output error method by authors seems to have shown fine performance. By employing this method and processing the flight data, unstational aerodynamic coefficients are obtained. The contradiction between the recorded flight data and the circumstantial evidence was reasonably explained.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.217-221
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• 2007

This paper deals with the robust nonlinear controller design using output feedback for a Chua circuit which is one of the well-known nonlinear models. First, an exosystem for reference signal tracking is defined, and error dynamic equations are derived from the differentiation of the output tracking error equation. The normal sliding surface is modified using the integral type servo compensator. The parameters in the equations of the modified sliding surface and servo compensator are determined by using the Hurwitz condition of stability. Especially the error signals can't be obtained directly from the output because all parameters are assumed unknown. So instead, a high gain observer is designed. From this estimated error signals, a stabilizing controller is designed. Simulation is done for demonstrating the effectiveness of the suggested algorithm.

• The Journal of the Acoustical Society of Korea
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• v.21 no.3E
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• pp.119-125
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• 2002

In the conventional generalized side-lobe canceller (GSC), the output is an estimated error signal that causes the adaptive filter weights do not converge to the optimal value. This paper presents a new side-lobe canceller with adaptive compensator th it reduces the misadjustment of the adaptive filter coefficients for the structural problem in the GSC. The adaptive compensator separates the output signal from the estimated error. The newly estimated error signal converges to the zero while the output signal tracks the target signal. This paper shows improvement of the performance by comparing the computer simulation of the output signal of GSC with the output signal of the proposed algorithm.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.5
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• pp.235-242
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• 2020

This paper analyzes the effect of reduced output width of the truncated logarithmic multiplication and application to inferences using convolutional neural networks (CNNs). For small hardware overhead, output width is reduced in the truncated Mitchell multiplier, so that fractional bits in multiplication output are minimized in error-resilient applications. This analysis shows that when reducing output width in the truncated Mitchell multiplier, even though worst-case relative error increases, average relative error can be kept small. When adopting 8 fractional bits in multiplication output in the evaluations, there is no significant performance degradation in target CNNs compared to existing exact and original Mitchell multipliers.