• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1663-1669
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• 1995

This paper is a study on the recognition of Korean proverb using neural network and Markov model. The neural network uses, at the stage of training neurons, features such as the rate of zero crossing, short-term energy and PLP-Cepstrum, covering a time of 300ms long. Markov models were generated by the recognized phoneme strings. The recognition of words and proverbs using Markov models have been carried out. Experimental results show that phoneme and word recognition rates are 81. 2%, 94.0% respectively for Korean proverb recognition experiments.

• ETRI Journal
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• v.43 no.1
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• pp.82-94
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• 2021

In this work, six voiced/unvoiced speech classifiers based on the autocorrelation function (ACF), average magnitude difference function (AMDF), cepstrum, weighted ACF (WACF), zero crossing rate and energy of the signal (ZCR-E), and neural networks (NNs) have been simulated and implemented in real time using the TMS320C6713 DSP starter kit. These speech classifiers have been integrated into a linear-predictive-coding-based speech analysis-synthesis system and their performance has been compared in terms of the percentage of the voiced/unvoiced classification accuracy, speech quality, and computation time. The results of the percentage of the voiced/unvoiced classification accuracy and speech quality show that the NN-based speech classifier performs better than the ACF-, AMDF-, cepstrum-, WACF- and ZCR-E-based speech classifiers for both clean and noisy environments. The computation time results show that the AMDF-based speech classifier is computationally simple, and thus its computation time is less than that of other speech classifiers, while that of the NN-based speech classifier is greater compared with other classifiers.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.709-712
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• 1988

Ultrasonic Doppler Diagnostic System utilizes the Doppler effect for measurement of blood velocity. The sign of the Doppler frequency shift represents blood flow direction. CW(Continuous-Wave) Doppler System uses quadrature detection and phase rotation method to produce simultaneous independent audio and velocity signals for forward and reverse blood flow direction in the time-domain, had been fabricated. But time-domain analyzing such as audio evaluation and zero- crossing detection for instantaneous and mean frequnecy measurement do not provide both an accurate and quantitative result. Therefore, it is necessary to adopt frequency-domain technique to improve system performance. In this paper, we describe a unit which is composed of CW Doppler System and real-time spectrum analyzer (installed TMS 32010 DSP Chip). This unit shows time-dependent spectrum variation and mean velocity of Blood signal.

• Journal of Power Electronics
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• v.16 no.1
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• pp.1-8
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• 2016

Dead time is typically incorporated in voltage source inverter systems to prevent short circuit cases. However, dead time causes an error between the output voltage and reference voltage. Hence, voltage equation-based algorithms, such as motor parameter estimation and back electromotive force (EMF)-based sensorless algorithms, are prone to estimation errors. Several dead-time compensation methods have been developed to reduce output voltage errors. However, voltage errors are still common in zero current crossing areas, and an effect of the error is much worse in a low speed region. Therefore, employing voltage equation-based algorithms in low speed regions is difficult. This study analyzes the conventional dead-time compensation method and output voltage errors in low speed operation areas. A current shaping method that can reduce output voltage errors is also proposed. Experimental results prove that the proposed method reduces voltage errors and improves the accuracy of the parameter estimation method and the performance of the back EMF-based sensorless algorithm.

• Journal of Magnetics
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• v.17 no.4
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• pp.298-301
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• 2012

In order to know the effect of surface irregularity in the detection of local wall thinning of pipeline using pulsed eddy current (PEC), the lift-off effects on PEC signal have been investigated. Three kinds of parameters in the PEC signal, which is "peak amplitude", "time to peak amplitude" and "time to zero crossing" are analyzed to separate the lift-off effects in the PEC signal. The distance from sensor to the bottom of sample which is the total thickness of combined insulator and sample is kept constant. The magnitude of the differential peak amplitude is increased with increasing sample thickness, the time to peak amplitude is increased with increasing the sample thickness. To determine the effect of lift-off, a number of balanced transient responses combining wall thinning locations and lift-off distances were plotted.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.216-217
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• 2010

This paper presents a new software-based on-line dead-time compensation technique for single-phase grid-connected photovoltaic (PV) inverter system. To improve the mitigation of dead-time effect around the zero-crossing point of phase current, a selective harmonic elimination of instantaneous feedback current is used as an additional part of conventional current control scheme. Simulation and experimental results are shown to verify the effectiveness of proposed compensation method in the grid-connected power distributed generation systems.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.147-150
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• 2002

This paper describes procedures to implement a real-time pitch analyzer using Matlab. Matlab is a multi-purpose signal-processing tool. Using this tool real-time analysis tool is implemented. To make it real-time we used data acquisition toolbox which comes with Matlab. Autocorrelation method was used as a basic algorithm. The resulting pitch informations are displayed in two different forms, i.e. instantaneous pitch plot and pitch track. V/UV decision is performed using zero crossing rate and energy Informations based on 500 utterances.

• The Journal of the Acoustical Society of Korea
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• v.32 no.5
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• pp.408-414
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• 2013

The famous filtered-x least mean square (FxLMS) algorithm for active noise control (ANC) systems may become unstable in non-stationary noise environment. To solve this problem, Sun's algorithm and Akhtar's algorithm are developed based on modifying the reference signal in update of FxLMS algorithm, but these two algorithms have dissatisfactory stability in dealing with sustaining impulsive noise. In proposed algorithm, probability estimation and zero-crossing rate (ZCR) control are used to improve the stability and performance, at the same time, an optimal parameter selection based on fuzzy system is utilized. Computer simulation results prove the proposed algorithm has faster convergence and better stability in non-stationary noise environment.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.910-916
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• 2015

A sensorless motor control scheme with conventional back-Electro Motive Force (EMF) sensing based on zero crossing point (ZCP) detection has been widely used in various applications. However, there are several problems with the conventional method for effectively driving sensorless brushless motors. For example, a phase mismatch of 30 degrees occurs between the ZCP and commutation time. Additionally, most of the motor speed/current controls are achieved based on a pulse width modulation (PWM) method, which generates significant noise that distracts the back-EMF sensing. Due to the PWM switching, the ZCP is not deterministic, and thus the efficiency of the motor is reduced because the phase transition points become uncertain. Moreover, the motor driving performance is degraded at a low speed range due to the effect of PWM noise. To solve these problems, an improved back-EMF detection method based on a differential line method is proposed in this paper. In addition, the proposed sensorless BLDC driver addresses the problems by using a variable voltage driver generated from a buck converter. The variable voltage driver does not generate the PWM switching noise. Consequently, the proposed sensorless motor driver improves 1) the signal-to-noise ratio of back-EMF, 2) the operation range of a BLDC motor, and 3) the torque characteristics. The proposed sensorless motor driver is verified through simulations and experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.333-342
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• 2012

This paper presents a vowel onset point (VOP) detection method based on the human auditory system. This method maps the "perceptual" frequency scale, i.e. Mel scale onto a linear acoustic frequency, and then establishes a series of Triangular Mel-weighted Filter Bank simulate the function of band pass filtering in human ear. This nonlinear critical-band filter bank helps greatly reduce the data dimensionality, and eliminate the effect of harmonic waves to make the formants more prominent in the nonlinear spaced Mel spectrum. The sum of mel spectrum peaks energy is extracted as feature for each frame, and the instinct at which the energy amplitude starts rising sharply is detected as VOP, by convolving with Gabor window. For the single-word database which contains 12 vowels articulated with different kinds of consonants, the experimental results showed a good average detection rate of 72.73%, higher than other vowel detection methods based on short-time energy and zero-crossing rate.