• Proceedings of the KOSOMBE Conference
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• v.1989 no.05
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• pp.19-22
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• 1989

This paper represents a syntactic peak detection algorithm which detects peaks in the ECG signal. In the algorithm, the input waveform is linearly approximated by "split-and-merge" method, and then each line segment is symbolized with primitive set. The peeks in the symbolized input waveform are recognized by the finite-state automata, which the deterministic finite-state language is parsed by. This proposed algorithm correctly detects peaks in a normal ECG signal as well as in the abnormal ECG signal such as tachycardia and the contaminated signal with noise.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.5
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• pp.597-604
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• 1986

This paper describes various mismatch phenomena in differential pulse code modulation (DPCM) coding, such as the mismatch effects of probability density functin(pdf), signal variance, and correlation. At a high transmission rate(i.e., above 32 kbits/s), the performance of DPCM can be improved by matching the pdf shape between the input signal and the quantizer. However, the same gain cannot be obtained at a lower transmission rate. Also, it is shown that the gamma quantizer is realtively robust to the variation of pdf shaper and signal variance. Moreover, as the transmission rate increases, the performance of DPCM for the input signal with large variance is worse than that of DPCM for the signal with small variance due to the increase of overload noise. According to our simuladiton results, the mismatch effects of pdf shape and variance appear to yield more degradatin than that of correlation in a DPCM system.

• Journal of Drive and Control
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• v.14 no.2
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• pp.30-36
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• 2017

This paper presents a sliding mode observer-based fault detection algorithm for steering inputs of an all-terrain crane. All-terrain cranes with multi-axles have several steering modes for various working purposes. Since steering angles at the other axles except the first wheel are controlled by using the information of steering angle at the first wheel, a reliable signal of the first axle's steering angle should be secured for the driving safety of cranes. For the fault detection of steering input signal, a simplified crane model-based sliding mode observer has been used. Using a sliding mode observer with an equivalent output injection signal that represents an actual fault signal, a fault signal in steering input was reconstructed. The road steering mode of the crane's steering system was used to conduct performance evaluations of a proposed algorithm, and an arbitrary fault signal was applied to the steering angle at the first wheel. Since the road steering mode has different steering strategies according to different speed intervals, performance evaluations were conducted based on the curved path scenario with various speed conditions. The design of algorithms and performance evaluations were conducted on Matlab/Simulink environment, and evaluation results reveal that the proposed algorithm is capable of detecting and reconstructing a fault signal reasonably well.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.641-642
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• 1986

We present a method for the estimation of intramuscular electromyographic(EMG) signals from the given surface EMG signals. This method is based on representing the surface EMG signal as an autoregressive(AR) time model with a delayed intramuscular EMG signal as an input. The parameters of the time series model that transforms the intramuscular signal to the surface signal are identified. The identified model is then used in estimating the intramuscular signal from the surface signal.

• The Journal of the Acoustical Society of Korea
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• v.30 no.6
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• pp.353-359
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• 2011

This paper proposes a vocal enhancement technique for improving the performance of vocal pitch detection in polyphonic music signal. The proposed vocal enhancement technique predicts an accompaniment signal from the input signal and generates an accompaniment replica signal according to the vocal power. Then, it removes the accompaniment replica signal from the input signal, resulting in a vocal-enhanced signal. The performance of the proposed method was measured by applying the same vocal pitch extraction method to the original and the vocal-enhanced signal, and the vocal pitch detection accuracy was increased by 7.1 % point in average.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1152-1160
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• 2003

Start The current paper proposes an improved HD(High Definition) monitor that can support a signal input with various resolutions. Due to the inadequate performance of the built-in digital PLL(Phase-locked Loop) of an ADC(Analog to Digital Converter) and poor tolerance of ADC ICs, there are problems in the stable processing of synchronization signals with various input signals. Accordingly, the proposed synchronization signal optimization technique regenerates the horizontal synchronization signal in the vertical blanking interval based on the regularity of the synchronization signal, i.e. the timing of the falling edge signal remains constant, thereby solving the above problem and minimizing the interference of the system. As a result, the proposed system can stabilize various synchronization signals with different resolution modes.

• The Journal of the Acoustical Society of Korea
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• v.33 no.5
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• pp.335-340
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• 2014

In this paper, we propose a new sign subband adaptive filter to improve the convergence rate of the conventional sign subband adaptive filter which has been proposed to deal with colored input signal under the environment with impulsive noise. The existing sign subband adaptive filter does not increase the convergence speed by increasing the number of subband because each subband input signal is normalized by $l_2-norm$ of all of the subband input signals. We devised a new sign subband adaptive filter that normalizes each subband input signal with $l_2-norm$ of each subband input signal and increases the convergence rate by increasing the number of subband. We carried out a performance comparison of the proposed algorithm with the existing sign subband adaptive filter using a system identification model. It is shown that the proposed algorithm has faster convergence rate than the existing sign subband adaptive filter.

• Journal of IKEEE
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• v.26 no.4
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• pp.568-576
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• 2022

Automatic modulation classification(AMC) is a core technique in Software Defined Radio(SDR) platform that enables smart and flexible spectrum sensing and access in a wide frequency band. In this study, we propose a simple yet accurate deep learning-based method that allows AMC for variable-size radio signals. To this end, we design a classification architecture consisting of two Convolutional Neural Network(CNN)-based models, namely main and small models, which were trained on radio signal datasets with two different signal sizes, respectively. Then, for a received signal input with an arbitrary length, modulation classification is performed by augmenting the input samples using a self-replicating padding technique to fit the input layer size of our model. Experiments using the RadioML 2018.01A dataset demonstrated that the proposed method provides higher accuracy than the existing methods in all signal-to-noise ratio(SNR) domains with less computation overhead.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.12
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• pp.550-557
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• 2006

This paper proposes a dry-type surface myoelectric sensor for the myoelectric hand prosthesis. The designed surface myoelectric sensor is composed of skin interface and processing circuits. The skin interface has one reference and two input electrodes, and the reference electrode is located in the center of two input electrodes. In this paper is proposed two types of sensors with the circle- and bar-shaped reference electrode, but all input electrodes are the bar-shaped. The metal material of the electrodes is the stainless steel (SUS440) that endures sweat and wet conditions. Considering the conduction velocity and the median frequency of the myoelectric signal, the inter-electrode distance (IED) between two input electrodes as 18mm, 20mm, and 22mm is selected. The signal processing circuit consists of a differential amplifier with a band pass filter, a band rejection filter for rejecting 60Hz power-line noise, amplifiers, and a mean absolute value(MAV) circuit. Using SUS440, six prototype skin interface with different reference electrode shape and IED is fabricated, and their output characteristics are evaluated by output signal obtained from the forearm of a healthy subject. The experimental results show that the skin interface with parallel bar shape and the 18mm IED has a good output characteristics. The fabricated dry-type surface myoelectric sensor is evaluated for the upper-limb amputee.

• ETRI Journal
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• v.33 no.5
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• pp.679-688
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• 2011

A new discrete-amplitude pulse width modulation (DAPWM) scheme for a high-efficiency linear power amplifier is proposed. A radio frequency (RF) input signal is divided into an envelope and a phase modulated carrier. The low-frequency envelope is modulated so that it can be represented by a pulse whose area is proportional to its amplitude. The modulated pulse has at least two different pulse amplitude levels in order that the duty ratios of the pulse are kept large for small input. Then, an RF pulse train is generated by mixing the modulated envelope with the phase modulated carrier. The RF pulse train is amplified by a switching-mode power amplifier, and the original RF input signal is restored by a band pass filter. Because duty ratios of the RF pulse train are kept large in spite of a small input envelope, the DAPWM technique can reduce loss from harmonic components. Furthermore, it reduces filtering efforts required to suppress harmonic components. Simulations show that the overall efficiency of the pulsed power amplifier with DAPWM is about 60.3% for a mobile WiMax signal. This is approximately a 73% increase compared to a pulsed power amplifier with PWM.