• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.1014-1022
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• 2012

This paper proposes a modified recursive sliding DFT to measure the phase of a single-tone. The modification is to provide a self error-cancelling mechanism so that it can significantly reduce the numerical error, which is generally introduced and accumulated when a recursive algorithm is implemented in finite wordlength arithmetic. The phase measurement error is analytically derived to suggest optimized distributions of quantization bits. The analytic derivation and the robustness of the algorithm are also verified by computer simulations. It shows that the maximum phase error of less than $5{\times}10^{-2}$ radian is obtained even when the algorithm is coarsely implemented with 4-bit wordlength twiddle factors.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.2
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• pp.177-184
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• 2016

This paper presents a strike velocity estimation using the recursive Bayesian filter that operates both correction and prediction models to probabilistically remove noises of sensors and accurately estimate the strike velocity during the real-time experiments. Four different types of bullets such as 5.56 mm M193, 7.62 mm M80, 5.45 mm 7N10 and 7.62 mm MSC were used to validate the proposed method. Compared to the existing method, the proposed method statistically results in higher stability of the strike velocity estimation as well as its reliability for the ballistic limit velocity computation.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.5 s.170
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• pp.45-54
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• 2005

The purpose of this research is to find a simple and accurate NURBS interpolator for CNC systems such as robot, CMM and CNC machine tools. This paper presents a new design of NURBS interpolator for CNC system. The proposed algorithm used the recursive characteristics of NURBS equation, the previous incremental value and chord length for the sake of a constant chord length. Simulation study was conducted to see the performance of the proposed interpolator with reference-word and reference-pulse method. Consequently, an accurate and simple NURBS interpolator was possible for modem CNC systems.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.9
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• pp.745-751
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• 2016

This paper presents the acceleration and deceleration control of free-form surfaces. A rapid variation of acceleration (or Deceleration) drives the system into a machine shock, resulting in the inaccuracy of the path control of the NURBS curve. The pattern of acceleration control can be established using the curvature of the NURBS curve. The curvature can be easily calculated from the first and second derivative of the NURBS curve used in Taylor's expansion for NURBS interpolation. However, the derivatives are not used in the recursive method for NURBS interpolation. Hence, we attempted the difference-derivatives for calculating the NURBS curvature. Both, Taylor's expansion and the recursive method, are used jointly for controlling the acceleration in the same interpolation algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.715-717
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• 2004

This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on a recursive error back-projection of top-down machine learning. A face is represented by a linear combination of prototypes of shape and texture. With the shape and texture information about the pixels in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes, In addition to, a recursive error back-projection is applied to improve the accuracy of synthesized high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution one captured at a distance.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.43.1-43
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• 2001

We propose two control methods of the Lyapunov exponents for Jordan-type recurrent neural networks. Both the two methods are formulated by a gradient-based learning method. The first method is derived strictly from the definition of the Lyapunov exponents that are represented by the state transition of the recurrent networks. The first method can control the complete set of the exponents, called the Lyapunov spectrum, however, it is computationally expensive because of its inherent recursive way to calculate the changes of the network parameters. Also this recursive calculation causes an unstable control when, at least, one of the exponents is positive, such as the largest Lyapunov exponent in the recurrent networks with chaotic dynamics. To improve stability in the chaotic situation, we propose a non recursive formulation by approximating ...

• Current Optics and Photonics
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• v.2 no.6
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• pp.563-567
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• 2018

We propose and experimentally demonstrate a simple tunable photonic microwave band-pass filter with high resolution using a reflective semiconductor optical amplifier (RSOA) and an optical time-delay line. The RSOA is used as a gain medium for generating cross-gain modulation (XGM) effect as well as an optical source. The optical source provides narrow spectral width by self-injection locking the RSOA in conjunction with a partial reflection filter with specific center wavelength. Then, when the RSOA is operated in the saturation region and the modulated recursive signal is injected into the RSOA, the recursive signal is inversely copied to the injection locked optical source due to the XGM effect. Also, the tunability of the passband of the proposed microwave filter is shown by controlling an optical time-delay line in a recursive loop.

• Journal of Korea Planning Association
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• v.53 no.7
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• pp.67-86
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• 2018

This paper attempted to analyze impacts of transition in electricity generation system on a national economy and environmental level in Korea using a recursive computable general equilibrium(CGE) model. In particular, the paper presented a hybrid model combining the top-down CGE model with the bottom-up model which describes the structure of electricity production in detail. The impacts were analyzed by two policy scenarios base on the basic plan for electricity supply and demand proposed by the Korean government. As a result, the paper specifically showed that there exists a trade-off relationship in the policy-making between economic efficiency and environmental level. The paper also suggested that the transition in electricity generation system should be done more gradually and carefully.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.98-101
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• 2019

At present, deep convolutional neural networks have made a very important contribution in single-image super-resolution. Through the learning of the neural networks, the features of input images are transformed and combined to establish a nonlinear mapping of low-resolution images to high-resolution images. Some previous methods are difficult to train and take up a lot of memory. In this paper, we proposed a simple and compact deep recursive residual network learning the features for single image super resolution. Global residual learning and local residual learning are used to reduce the problems of training deep neural networks. And the recursive structure controls the number of parameters to save memory. Experimental results show that the proposed method improved image qualities that occur in previous methods.

• Journal of the military operations research society of Korea
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• v.13 no.1
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• pp.1-18
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• 1987

This paper presents several adaptive linear predictive coding techniques based upon extension of recursive ladder filters. A 2-D recursive ladder filter is extended to a 3-D case which can adaptively track the variation of both spatial and temporal changes of moving images. Using the 2-D/3-D ladder filter and a previous farme predictor, two types of adaptive predictor-control schemes are proposed in which the prediction error at each pel can be obtained at or close to a minimum level. We also investigate several modifications of the basic encoding methods. Performance of the 2-D/3-D ladder filters, their adaptive control schemes, and variations in coding methods are evaluated by computer simulations on a real sequence and compared to the results of motion compensation and frame differential coders. As a validity test of the ladder filters developed, the error signals for the different predictors are compared and evaluated.