• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.425-428
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• 2001

In this paper, FMCW radar signal processing technique for the vehicle detection system are studied. And FMCW radar sensor is used as a equipment for vehicle detection. To test the performance of developed algorithm, the evaluation of the algorithm is done by simulation for signal processing technique of vehicle detection system. RADAR signal of a driving vehicle is generated by using the Matlab. Distance and velocity of vehicles are calculated with developed a1gorithm. Also the signal processing procedure is done for the virtual data with FM-AM converted noise.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.748-764
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• 2019

In order to deal with the filtering delay problem of least mean square adaptive filter noise reduction algorithm and music noise problem of spectral subtraction algorithm during the speech signal processing, we combine these two algorithms and propose one novel noise reduction method, showing a strong performance on par or even better than state of the art methods. We first use the least mean square algorithm to reduce the average intensity of noise, and then add spectral subtraction algorithm to reduce remaining noise again. Experiments prove that using the spectral subtraction again after the least mean square adaptive filter algorithm overcomes shortcomings which come from the former two algorithms. Also the novel method increases the signal-to-noise ratio of original speech data and improves the final noise reduction performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1A
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• pp.71-79
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• 2010

The algorithm of multiple channel signal processing requires the flexibility of variable frequency band, efficient allocation of transmission power, and flexible frequency band reallocation to satisfy various service types which requires different transmission rates and frequency band. This paper proposes an improved multiple channel signal processing for converting the frequency band of multiple carrier signals efficiently using a window function and DFT in the time domain. In contrast to the previous algorithm of multiple-channel signal processing performing band-pass signal processing in the frequency domain, the proposed algorithm is a method of block signal processing using a window function in the time domain. In addition, the complexity of proposed algorithm of the window function is lower than that of the previous algorithm performing signal processing in the frequency domain, and it performs the frequency band transform efficiently. The computer simulation result shows that the perfect reconstruction of output signal and the flexible frequency band reallocation is performed efficiently by the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.97-97
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• 2000

In this paper, a signal processing algorithm for software GPS receiver is proposed. The signal processor takes snapshot of the sampled If signal from the RF section of the GPS receiver. All the processing for code and carrier tracking and correlation are implemented using the digital signal processing techniques. In order to achieve fast code acquisition, correlation of the incoming GPS signal is performed using the FFT method, After code acquisition, to reduce the Doppler shift effect and increase the accuracy, the interpolation or the tracking are performed. The performance of the proposed processing algorithm is first evaluated using matlab/simulink. A signal acquisition board for sampling and logging GPS IF signal form the Mitel GPS RF chip set is constructed. In order to analyze the performance of the designed algorithm the experiments are performed and the results are analyzed.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.4
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• pp.291-298
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• 2007

This paper presents a signal processing algorithm to control the dynamic bandwidth of a single-degree-of-freedom (SDF) dynamic sensor system. An accelerometer is a representative SDF sensor system. In this paper, a moire-fringe-based fiber optic accelerometer is newly used for the test of the algorithm. The accelerometer is composed of one mass, one damper and one spring as a SDF dynamic system. In order to increase the dynamic bandwidth of the accelerometer, it is needed to increase the spring constant or decrease the mass. However, there are mechanical difficulties of this adjustment. Therefore, the presented signal processing algorithm is very effective to overcome the difficulties because it is just adjustment in the signal processing software. In this paper, the novel fiber optic accelerometer is introduced shortly, and the algorithm is applied to the fiber optic accelerometer to control its natural frequency and damping ratio. Several simulations and experiments are carried out to prove the performance of the algorithm. As a result, it is shown that the presented signal processing algorithm is a good way to broaden the dynamic bandwidth of the fiber optic accelerometer.

• Journal of the Optical Society of Korea
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• v.4 no.2
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• pp.89-93
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• 2000

Recently a new signal processing algorithm for white light interferometry was presented. In this paper, the proposed signal processing algorithm was applied for absolute temperature measurement using white light interferometry. Stability testing and absolute temperature measurement were demonstrated. Stability test demonstrated the feasibility of absolute temperature measurement with an accuracy of 0.015 fringe. The test also showed that the absolute temperature measurement system using white light interferometry is capable of obtaining the theoretical minimum detectable change (0.0005 fringe), which is consistent with the performance predicted by the proposed signal processing algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.42-46
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• 2018

Adaptive signal processing is quite important in various signal and communication environments. In adaptive signal processing methods since the least mean square(LMS) algorithm is simple and robust, it is used everywhere. As the step is varied in the variable step(VS) LMS algorithm, the fast convergence speed and the small excess mean square error can be obtained. Various variable step LMS algorithms are researched for better performances. But in some of variable step LMS algorithms the computational complexity is quite large for better performances. The fixed step LMS algorithm with a low computational complexity merit and the variable step LMS algorithm with a fast convergence merit are combined in the proposed sporadic step algorithm. As the step is sporadically updated, the performances of the variable step LMS algorithm can be maintained in the low update rate using Fibonacci sequence. The performances of the proposed variable step LMS algorithm are proved in the adaptive equalizer.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.8
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• pp.7-14
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• 1992

This paper persents how the signal is expressed by an implied unit data and the implied unit data is regenerated into the original signal. This shows that the regenerated signal is equal or similar to the original signal depending on the number of chaos prediction. The algorithm quoted above is implemented from the signal composed of 30 data. This algorithm will be applied to the applied science of data communication: information storage, speech processing, CAD, character recognition, etc...

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.742-745
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• 1988

Control algorithm for remote transmission processing system for ECG signals is proposed. Software for the system hardware consists of system control algorithm and signal processing algorithm. Since signal processing algorithm is now under developing, this paper describes the details of system control only.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.942-947
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• 2003

An important signal processing problem in PVDF sensor is the restoration of surface information from electric sensing signals. The objectives of this research are to design a new texture sensing system and to develop a new signal processing algorithm for signals from the sensor to be tangibly displayed by tangible interface systems. The texture sensing system is designed to get surface information with high resolution and dynamic range. First, a PVDF sensor is made of piezoelectric polymer (polyvinylidene fluoride) strips molded in a silicon rubber and attached in a rigid cylinder body. The sensor is mounted to a scanning system for dynamic sensing. Secondly, a new signal processing algorithm is developed to restore surface information. The algorithm consists of the two-dimensional modeling of the sensor using an identification method and inverse filtering from sensing signals into estimated surface information. Finally the two-dimensional surface information can be experimentally reconstructed from sensing signals using the developed signal processing algorithm.