• Journal of Advanced Navigation Technology
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• v.25 no.4
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• pp.293-298
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• 2021

In general, the guided weapon seeker and the guided control device process the target, search, recognition, and capture information to indicate the state of the guided missile, and play a role in controlling the operation and control of the guided weapon. The signals required for guided weapons are gaze change rate, visual signal, and end-stage fuselage orientation signal. In order to process the complex and difficult-to-process missile signals of recent missiles in real time, it is necessary to increase the data processing speed of the missiles. This study showed the processing speed after applying the stop and go and inverse enumeration algorithm among the parallel algorithm methods of PINQ and comparing the processing speed of the signal data required for the guided missile in real time using the guided missile inspection program. Based on the derived data processing results, we propose an effective method for processing missile data when applying a parallel processing algorithm by comparing the processing speed of the multi-core processing method and the single-core processing method, and the CPU core utilization rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.575-583
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• 2000

Pulse oximetry is a well established non-invasive optical technique for monitoring the $SpO_2$ during anaesthesia, recovery and intensive care. Pulse oximeters determine the oxygen saturation level of blood by measuring the light absorption of arterial blood. In the measurement of the hemoglobin oxygen saturation, conventional method has required the technique of filtering of remove the noise, and of complex signal processing algorithm. So much time have been required to signal processing. In this research, we separate AC signal and DC signal in the stage of signal detection. Therefore we simplify the calculation algorithm for $SpO_2$. The implemented system have the high performance such an accuracy and a processing time than the traditional method.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.6
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• pp.168-176
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• 1996

A diagnosis system which can monitor tool breakage and chipping in real time was developed using a DSP(Digital Signal Processor) board in face milling operation. AR modelling and band energy method were used to extract the feature of tool states from cutting force signals. Artificial neural network embedded on DSP board discriminates different patterns from features got after signal processing. The features extracted from AR modelling are more accurate for the malfunction of a process than those from band energy method, even though the computing speed of the former is slow. From the processed features, we can construct the real time diagnosis system which monitors malfunction by using a DSP board having a parallel processing capability.

• Journal of Positioning, Navigation, and Timing
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• v.5 no.3
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• pp.109-118
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• 2016

The present paper proposes a method that can estimate a roll rate of spinning vehicles utilizing GPS receivers. The proposed method analyzes a relation between received signal and correlation value and utilizes a phenomenon that received signal power that changes according to a signal incident direction affects a correlation value. That is, a roll-rate estimation method using zero crossing detection method for correlation value, which has sinusoidal periodicity according to rotations of vehicles, is proposed. A correlation value in real environments experiences a jitter so that the proposed method includes a pre-processing filter and detection threshold setting way is also considered to reduce the effect of received signal power. In order to verify the operation of the proposed method and analyze the performance, a signal generator and software-defined receiver (SDR) are designed. The signal generator generates intermediate frequency (IF) signal by taking the rotation of vehicles, antenna gain, and signal power into consideration, and a correlation value is acquired by taking the generated IF signals into consideration. Using the generated correlation value, the operation of the proposed roll rate estimation method is verified and the performance is analyzed.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.3
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• pp.225-231
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• 2013

This paper presents an improved signal processing technique in the square-wave-type voltage injection method for IPMSM sensorless drives. Since the sensorless method based on the square-wave voltage injection does not use low-pass filters to get an error signal for estimating rotor position and allows the frequency of the injected voltage signal to be high, the sensorless drive system may achieve an enhanced control bandwidth and reduced acoustic noise. However, this sensorless method still requires low-pass and band-pass filters to extract the fundamental component current and the injected frequency component current from the motor current, respectively. In this paper, these filters are replaced by simple arithmetic operations so that the time delay for estimating the rotor position can be effectively reduced to only one current sampling. Hence, the proposed technique can simplify its whole signal process for the IPMSM sensorless control using the square-wave-type voltage injection. The proposed technique is verified by the experiment on the 800W IPMSM drive system.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.933-946
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• 2021

In the non-orthogonal multiple access (NOMA) system, multiple user signals on the single carrier are superimposed in a non-orthogonal manner, which results in the interference between non-orthogonal users and noise interference in the channel. To solve this problem, an improved algorithm combining regularized zero-forcing (RZF) precoding with minimum mean square error-serial interference cancellation (MMSE-SIC) detection is proposed. The algorithm uses RZF precoding combined with successive over-relaxation (SOR) method at the base station to preprocess the source signal, which can balance the effects of non-orthogonal inter-user interference and noise interference, and generate a precoded signal suitable for transmission in the channel. At the receiver, the MMSE-SIC detection algorithm is used to further eliminate the interference in the signal for the received superimposed signal, and reduce the calculation complexity through the QR decomposition of the matrix. The simulation results show that the proposed joint detection algorithm has good applicability to eliminate the interference of non-orthogonal users, and it has low complexity and fast convergence speed. Compared with other traditional method, the improved method has lower error rate under different signal-to-interference and noise ratio (SINR).

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.167.3-167
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• 2001

In this paper, a single degree-of freedom gimbal-structured micro gyroscope and signal processing part including capacitive sensing circuits and filters are designed, fabricated and experimented. We use capacitive sensing method with excitation signal, i.e. sensing excitation signal, to measure the displacement of the moving plate. So, Sensing Output Signal is modulated twice by the excitation signal and driving signal, which is profitable to decouple the driving and sensing mode, to reduce the effect of the acceleration, and to curtail the noises due to parasitic capacitance and driving signal. To reduce driving noises and to improve linearity, the excitation signals and driving signals are modified. Through frequency response analyses ...

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.294-294
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• 2000

In this paper, we would like to discuss the signal processing and the algorithm for ECG analysis. The ECG gives us information about the condition of the heart muscle, because myocardial abnormality or infarction is inscribed on the ECG during myocardial depolarization and repolarization. Analyzing the ECG signal, we can find heart disease, for example, arrhythmia and myocardial infarction, etc. Particularly, detecting arrhythmia is more important, because serious arrhythmia can take away the life from patients within ten minutes. The wavelet transform decomposes the ECG signal into high and low frequency component using wavelet function. Recomposing high frequency bands including QRS complex, we can detect QRS complex and eliminate the noise from the original ECG signal. To recognize the ECG signal pattern, we adopted the curve-fitting partially and statistical method. The ECG signal is divided into small parts based on QRS complex, and then, each part is approximated to the polynomials. Comparing the approximated ECG pattern with some kinds of heart disease ECG pattern, we can detect and classify the kind of heart disease.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.137-143
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• 2007

The P-ECLMS algorithm adapted the existing Post-Processing method occurs the distortion of the near-end signal at the double-talk situation. To solve this problem, we propose the SP-ECLMS algorithm which makes the Post-Processing coefficient differently at the case of the single-talk and the double-talk. When the correlation level is not output less than 30%, the proposed algorithm output the original signal to prevent the signal's distortion.

• 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.