• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.225-228
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• 1996

ECG data are used for the diagnostic purposes with many clinical situations, especially heart disease. In this paper, an efficient ECG data compression technique by wavelet transform and high-speed vector quantization on PMS-B algorithm is proposed. In general, ECG data compression techniques are divided into two categories: direct and transform methods. The direct data compression techniques are AZTEC, TP, CORTES, FAN and SAPA algorithms, besides the transform methods include K-L, Fourier, Walsh, and wavelet transforms. In this paper, we applied wavelet analysis to the ECG data. In particular, vector quantization on PMS-B algorithm to the wavelet coefficients in the higher frequency regions, but scalar quantized in the lower frequency regions by PCM. Finally, the quantized indices were compressed by LZW lossless entropy encoder. As the result of simulation, it turns out to get sufficient compression ratio while keeping clinically acceptable PRD.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.10A
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• pp.1764-1771
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• 2001

It has developed a PCM signal acquisition(PCMA) system which can analyze status of signals in order to establish rapid diagnosing in TDX-families signaling service equipment. We develop the quick Fourier transform(QFT) for length 2$\^$M/ data to analyze the power spectral of the PCMA system. This algorithm can reduces the number of floating-point operations necessary to compute the DFT by a factor of two or four over direct methods or Goertzels method for prime lengths. In the experimental results, the system classifies the type of signals and finally discriminates the digit.

• Journal of Power Electronics
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• v.16 no.3
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• pp.823-831
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• 2016

A high-efficiency method is proposed to suppress magnetic core imbalance in phase-shifted full-bridge (PSFB) converters. Compared with conventional solutions, such as controlling peak current mode (PCM) or adding DC blocking capacitance, the proposed method has several advantages, such as lower power loss and smaller size, because the additional current sensor or blocking capacitor is removed. A time domain model of the secondary side is built to analyze the relationship between transformer core imbalance and cathode voltage of secondary side rectifiers. An approximate control algorithm is designed to achieve asymmetric phase control, which reduces the effects of imbalance. A 60 V/15 A prototype is built to verify the proposed method. Experimental results show that the numerical difference of primary side peak currents between two adjacent cycles is suppressed from 2 A to approximately 0 A. Meanwhile, compared with the PCM solution, the efficiency of the PSFB converter is slightly improved from 93% to 93.2%.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.36-40
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• 1997

In speech signal processing, it is necessary and important to detect exactly the pitch. The algorithms of pitch extraction which have been proposed until now are difficult exactly pitches over wide range speech signals. In this paper, thus, we proposed a new pitch detection algorithm that finds the fundamental period of speech signal in the residual signal quantized by the uniform quantizer as PCM. The proposed method shows little gross error of average 0.25% for clean speech and average 3.39% for SNR of 0dB. It also achieves results of the pitch contours, improving the accuracy of pitch detection in transient phonemes and noise environments.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1295-1297
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• 1996

CCITT G.721, G.723 standard ADPCM algorithm is implemented by using TI's fixed point DSP start kit (DSK). ADPCM can be implemented on a various rates, such as 16K, 24K, 32K and 40K. The ADPCM is sample based compression technique and its complexity is not so high as the other speech compression techniques such as CELP, VSELP and GSM, etc. ADPCM is widely applicable to most of the low cost speech compression application and they are tapeless answering machine, simultaneous voice and fax modem, digital phone, etc. TMS320C50 DSP is a low cost fixed point DSP chip and C50 DSK system has an AIC (analog interface chip) which operates as a single chip A/D and D/A converter with 14 bit resolution, C50 DSP chip with on-chip memory of 10K and RS232C interface module. ADPCM C code is compiled by TI C50 C-compiler and implemented on the DSK on-chip memory. Speech signal input is converted into 14 bit linear PCM data and encoded into ADPCM data and the data is sent to PC through RS232C. The ADPCM data on PC is received by the DSK through RS232C and then decoded to generate the 14 bit linear PCM data and converted into the speech signal. The DSK system has audio in/out jack and we can input and out the speech signal.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.30-32
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• 2014

최근 낸드 플래시 메모리는 임베디드 저장 장치로 많이 사용되고 있다. 비휘발성인 플래시 메모리는 기존의 하드디스크와 달리 저 전력, 좋은 내충격성 및 집적도 등 많은 장점이 있지만 데이터 업데이트 시 덮어쓰기가 안 되어 쓰기 연산 전 해당 블록을 지우는 작업이 선 진행되어야 하며 이로 인해 부분 페이지 업데이트가 자주 일어난다. 이런 플래시메모리와 더불어 최근 차세대 메모리연구가 많이 진행 중인데, 이 중에서 PCM 이라는 메모리는 비휘발성으로 정전 시 데이터가 날라 가버리는 DRAM에 반해 전원이 공급 안 되더라도 데이터가 보존되는 특성이 있다. 하지만 PCM 역시 플래시 메모리와 마찬가지로 블록 당 쓰기연산 작업이 제한되어 있어서 근래에 DRAM과 같이 사용하는 하이브리드 구조를 채택하여 많은 연구가 진행되고 있다. 따라서 본 논문에서는 플래시 메모리의 문제점을 해결함으로서 수명을 연장시키고 정 전시 데이터가 보존되지 않는 DRAM의 단점을 하이브리드 메모리를 기반으로하여 데이터의 신뢰성을 높이는 FTL알고리즘을 제안한다.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.677-687
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• 2021

The tendency to renewables is one of the consequences of changing attitudes towards energy issues. As a result, solar energy, which is the leader among renewable energies based on availability and potential, plays a crucial role in full filing global needs. Significant problems with the solar thermal power plants (STPP) are the operation time, which is limited by daylight and is approximately half of the power plants with fossil fuels, and the capital cost. Exergy analysis survey of STPP hybrid with PCM storage carried out using Engineering Equation Solver (EES) program with genetic algorithm (GA) for three different scenarios, based on eight decision variables, which led us to decrease final product cost (electricity) in optimized scenario up to 30% compare to base case scenario from 28.99 $/kWh to 20.27 $/kWh for the case study. Also, in the optimal third scenario of this plant, the inner carbon dioxide gas cycle produces 1200 kW power with a thermal efficiency of 59% and also 1000 m3/h water with an exergy efficiency of 23.4% and 79.70 kg/h with an overall exergy efficiency of 34% is produced in the tetrageneration plant.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.889-894
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• 2004

The fuzzy kernel c-means (FKCM) algorithm, which uses a kernel function, can obtain more desirable clustering results than fuzzy c-means (FCM) for not only spherical data but also non-spherical data. However, it can be sensitive to noise as in the FCM algorithm. In this paper, a kernel function is applied to the possibilistic c-means (PCM) algorithm and is shown to be robust for data with additive noise. Several experimental results show that the proposed kernel possibilistic c-means (KPCM) algorithm out performs the FKCM algorithm for general data with additive noise.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.112-121
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• 1997

In this paper, we study a model parameter compensation method for noise-robust speech recognition. We study model parameter compensation on a sentence by sentence and no other informations are used. Parallel model combination(PMC), well known as a model parameter compensation algorithm, is implemented and used for a reference of performance comparision. We also propose a modified PMC method which tunes model parameter with an association factor that controls average variability of gaussian mixtures and variability of single gaussian mixture per state for more robust modeling. We obtain a re-estimation solution of environmental variables based on the expectation-maximization(EM) algorithm in the cepstral domain. To evaluate the performance of the model compensation methods, we perform experiments on speaker-independent isolated word recognition. Noise sources used are white gaussian and driving car noise. To get corrupted speech we added noise to clean speech at various signal-to-noise ratio(SNR). We use noise mean and variance modeled by 3 frame noise data. Experimental result of the VTS approach is superior to other methods. The scheme of the zero order VTS approach is similar to the modified PMC method in adapting mean vector only. But, the recognition rate of the Zero order VTS approach is higher than PMC and modified PMC method based on log-normal approximation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.700-705
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• 2004

Clustering of incomplete data using the Autoencoder and the Fuzzy c-Means(PCM) is proposed in this paper. The Proposed algorithm, called Optimal Completion Autoencoder Fuzzy c-Means(OCAEFCM), utilizes the Autoencoder Neural Network (AENN) and the Gradiant-based FCM (GBFCM) for optimal completion of missing data and clustering of the reconstructed data. The proposed OCAEFCM is applied to the IRIS data and a data set from a financial institution to evaluate the performance. When compared with the existing Optimal Completion Strategy FCM (OCSFCM), the OCAEFCM shows 18％-20％ improvement of performance over OCSFCM.