• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.5
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• pp.44-50
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• 2012

ECMA-392 is the first CR (cognitive radio) specification for personal/portable devices in TV white space. In ECMA-392, in addition to the long preamble of 2 OFDM symbols, 4 pilot sub-carriers per OFDM symbol are repeatedly transmitted with the period of 13 OFDM symbols. In this paper, we consider channel estimation schemes using both long preamble and pilot sub-carriers: we propose channel estimation schemes in which a first order recursive filter is used, and present a method for reducing channel estimation delay. Computer simulation results indicate that the proposed schemes perform well over slow Rayleigh fading channels.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.10
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• pp.43-48
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• 2010

In general, in order to reduce an initial cell searching time, W-CDMA systems adopt a three-step cell search scheme: slot synchronization, frame synchronization, and primary scrambling code identification. We consider the second step (frame synchronization), in which a coherent detection using P-SCH (primary synchronization channel) is possible. In this paper, we propose a new coherent detection scheme, where a first order recursive filter is used to enhance channel estimation performance. Computer simulation results indicate that the detection performance of the proposed scheme can be robust over large range of frequency offset.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.360-367
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• 2002

In this paper, genetic algorithm based adaptive image enhancement filtering scheme is proposed and Implemented on FPGA board. Conventional filtering methods require a priori noise information for image enhancement. In general, if a priori information of noise is not available, heuristic intuition or time consuming recursive calculations are required for image enhancement. Contrary to the conventional filtering methods, the proposed filter system can find optimal combination of filters as well as their sequent order and parameter values adaptively to unknown noise types using structured genetic algorithms. The proposed image enhancement filter system is mainly composed of two blocks. The first block consists of genetic algorithm part and fitness evaluation part. And the second block consists of four types of filters. The first block (genetic algorithms and fitness evaluation blocks) is implemented on host computer using C code, and the second block is implemented on re-configurabe FPGA board. For gray scale control, smoothing and deblurring, four types of filters(median filter, histogram equalization filter, local enhancement filter, and 2D FIR filter) are implemented on FPGA. For evaluation, three types of noises are used and experimental results show that the Proposed scheme can generate optimal set of filters adaptively without a pioi noise information.

• The Journal of the Acoustical Society of Korea
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• v.17 no.4E
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• pp.3-10
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• 1998

This paper concerns the dynamical behavior, in probabilistic sense, of a feedforward neural network performing auto association for novelty. Networks of retinotopic topology having a one-to-one correspondence between and output units can be readily trained using back-propagation algorithm, to perform autoassociative mappings. A novelty filter is obtained by subtracting the network output from the input vector. Then the presentation of a "familiar" pattern tends to evoke a null response ; but any anomalous component is enhanced. Such a behavior exhibits a promising feature for enhancement of weak signals in additive noise. As an analysis of the novelty filtering, this paper shows that the probability density function of the weigh converges to Gaussian when the input time series is statistically characterized by nonsymmetrical probability density functions. After output units are locally linearized, the recursive relation for updating the weight of the neural network is converted into a first-order random differential equation. Based on this equation it is shown that the probability density function of the weight satisfies the Fokker-Planck equation. By solving the Fokker-Planck equation, it is found that the weight is Gaussian distributed with time dependent mean and variance.

• Smart Structures and Systems
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• v.31 no.2
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• pp.131-140
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• 2023

As well-known, the extended Kalman filter (EKF) is a powerful tool for parameter identification with limited measurements. However, traditional EKF is not applicable when the external excitation is unknown. By using least-squares estimation (LSE) for force identification, an EKF with unknown input (EKF-UI) approach was recently proposed by the authors. In this approach, to ensure the influence matrix be of full column rank, the sensors have to be deployed at all the degrees-of-freedom (DOFs) corresponding to the unknown excitation, saying collocated measurements are required. However, it is not easy to guarantee that the sensors can be installed at all these locations. To circumvent this limitation, based on the idea of first-order-holder discretization (FOHD), an improved EKF with unknown input (IEKF-UI) approach is proposed in this study for the simultaneous identification of structural parameters and unknown excitation. By using projection matrix, an improved observation equation is obtained. Few displacement measurements are fused into the observation equation to avoid the so-called low-frequency drift. To avoid the ill-conditioning problem for force identification without collocated measurements, the idea of FOHD is employed. The recursive solution of the structural states and unknown loads is then analytically derived. The effectiveness of the proposed approach is validated via several numerical examples. Results show that the proposed approach is capable of satisfactorily identifying the parameters of linear and nonlinear structures and the unknown excitation applied to them.

• Korean Journal of Applied Biomechanics
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• v.17 no.4
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• pp.149-156
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• 2007

The purpose of this study was to compare the world class women's hurdlers with kinematic variables Lee Yeon-Kyoung's in the 100m hurdle. Among korea elite female hurdler, Lee Yeon-Kyoung was participated as a subject. Eight JVC video cameras(GR-HD1KR) were used to film the performance of Lee Yeon-Kyoung at a frame rate of 60fields/s. The real-life three-dimensional coordinate data of digitized body landmarks were smoothed using a fourth order Butterworth low pass recursive digital filter with an estimated optimum cutoff frequency of 7.4Hz. After analyzing and comparing Lee Yeon Kyung's kinematic variables with the world top class hurdlers in the woman's 100m hurdle run, the following conclusions were obtained. 1. Lee should be able to increase the speed with over 5.4m/s from start to first hurdle and then maintain the speed range from 8.33m/s to 8.67m/s until 10th hurdle. Lee should have to maintain the speed with 8.51m/s from 10th hurdle to finish line. 2. Lee has to reach her maximum running speed at 5th hurdle and then has to shorten running time with 0.5sec between hurdles. 3. Lee should be able to run around 2.5sec from start to frist hurdle and then maintain under 1.00sec following phases. Lee should be able to maintain under 1.10sec from 10th hurdle to finish line. 4. Lee needs to control a consistent takeoff and landing distance pattern, Lee needs to lower the height of the center of gravity of the body with 0.33m when she clears the hurdles.