• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권3호
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• pp.471-489
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• 2013

Data compression at the transport layer could both reduce transmitted bytes over network links and increase the transmitted application data (TCP PDU) in one RTT at the same network conditions. Therefore, it is able to improve transmission efficiency on Internet, especially on the networks with limited bandwidth or long delay links. In this paper, we propose an on-the-fly TCP data compression scheme, i.e., the TCPComp, to enhance TCP performance. This scheme is primarily composed of the compression decision mechanism and the compression ratio estimation algorithm. When the application data arrives at the transport layer, the compression decision mechanism is applied to determine which data block could be compressed. The compression ratio estimation algorithm is employed to predict compression ratios of upcoming application data for determining the proper size of the next data block so as to maximize compression efficiency. Furthermore, the assessment criteria for TCP data compression scheme are systematically developed. Experimental results show that the scheme can effectively reduce transmitted TCP segments and bytes, leading to greater transmission efficiency compared with the standard TCP and other TCP compression schemes.

• 대한의용생체공학회:의공학회지
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• 제12권3호
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• pp.191-202
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• 1991

This paper describes ECG data compression algorithm using neural network. As a learning method, we use back error propagation algorithm. ECG data compression is performed using learning ability of neural network. CSE database, which is sampled 12bit digitized at 500samp1e/sec, is selected as a input signal. In order to reduce unit number of input layer, we modify sampling ratio 250samples/sec in QRS complex, 125samples/sec in P & T wave respectively. hs a input pattern of neural network, from 35 points backward to 45 points forward sample Points of R peak are used.

• 대한음성학회지:말소리
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• 제55권
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• pp.143-158
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• 2005

The adequate compression algorithm is essential to achieve high quality embedded TTS system. in this paper, we Propose waveform interpolation coder for TTS corpus compression after many speech coder investigation. Unlike speech coders in communication system, compression rate and anality are more important factors in TTS DB compression than other performance criteria. Thus we select waveform interpolation algorithm because it provides good speech quality under high compression rate at the cost of complexity. The implemented coder has bit rate 6kbps with quality degradation 0.47. The performance indicates that the waveform interpolation is adequate for TTS DB compression with some further study.

• 한국통신학회논문지
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• 제22권6호
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• pp.1127-1136
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• 1997

A vector timestamp is used to satisfy message ordering in a group communications. In this paper, we propose a new vector timestamp compression method which is applicable to a single process group environment where one process belongs to only one precess group. An existing compression method compares the fields of the previously sent vector timestamp with thouse of the currently updated vector timestamp, then sends only the modified fields of the vector timestamp. Unlike the previous one, a proposed compression method performs individual compression for each process using the locally maintained vector timestamp information on other processes. Also, we logicallyproved the causal ordering algorithm using the new compression method and compared the performance of the proposed method with one of the previous compression method by computer simulation. Using the proposed compression method, the message overhead required for causal ordering can be reduced.

• 디지털산업정보학회논문지
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• 제5권3호
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• pp.141-145
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• 2009

In this paper, we propose an efficient lossless compression algorithm using spatial and temporal information. The proposed method obtains higher lossless compression of images than other lossless compression techniques. It is divided into two parts, a motion adaptation based predictor part and a residual error coding part. The proposed nonlinear predictor can reduce prediction error by learning from its past prediction errors. The predictor decides the proper selection of the spatial and temporal prediction values according to each past prediction error. The reduced error is coded by existing context coding method. Experimental results show that the proposed algorithm has better performance than those of existing context modeling methods.

• 대한전기학회논문지:전력기술부문A
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• 제53권11호
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• pp.581-588
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• 2004

Power qualify monitoring system is devoted to more concern than before, because the innovation of industrial technology needs more accurate instruments and more advanced power quality. This paper was studied on using data of the protective relay by Power Quality Monitor. This paper was proposed the wave storage condition and monitoring clauses of the protective relay as a power quality monitoring device. The protective relay will have problem to save data for PQM analysis because the protective relay memory is limited. Therefore this paper was proposed new a data compression of data got from the protective relay. This method is wave compression comparison algorithm using the DFT. The compression rate is higher than any other established method. This method can be real time storage. This algorithm is verified using the comparison among other compression rate and proved by Real Time Digital Simulator (RTDS).

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1996년도 추계학술대회
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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.

• 대한의용생체공학회:의공학회지
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• 제13권4호
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• pp.323-330
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• 1992

A Study of Image Compression Algorithm using DCT This paper describes the system that implement a JPEG(Joint Photographic Experts Group) algorithm based on DCT(Discrete Cosine Transform) uslng CCD kameva, Image Grabber, and IBM PC. After cosine transforms the acquisited image, this algorithm quantize and entropy encode the coefficients by JPEG code table. The coefficients are reconstructed by the Huffman decoding, dequantized procedure, and Inverse cosine transform. The results obtained from the impleulented system are as follows. (1) For effcient storage and easy implementation, this system save Image as a PCX formal (2) Thls system get 7:1 compression ratio(3.8 RMSE value) without large distortion. (3) With a low pass filtering, thls system eliminate high frequency components and get 20% enhanced compression ratio. (4) Thls system enhance the reconstructed Image using histogram modeling.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제10권3호
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• pp.243-250
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• 2004

본 논문은 실용화 레벨에서의 디지털 영상기록 (Digital Video Recording: DVR) 구현을 기술한다. 또한 입력 영상을 배경과 목표물 영역의 두 가지 영역으로 분리 처리하여 분리된 영역별로 중요도를 고려하여 서로 다른 압축 기법을 적용함으로써 효율적인 압축부호화를 수행할 수 있는 방안을 제안한다. 본 알고리즘은 영상 압축 부호화 기법으로서 영역분할을 통해 Macro block 단위로 물체 영역과 배경 영역을 재구성해서 부호화에 이용하는 방식이다. 제안된 알고리즘은 매우 효율적인 압축 성능을 보여주며, 저 전송률 상황에서도 높은 질의 영상을 복원할 수 있다.

• The Journal of the Acoustical Society of Korea
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• 제16권1E호
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• pp.35-40
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• 1997

The LZW algorithm has some redundancies for voice traffic. Thus, the V-LZW(Voice LZW) algorithm that decreases the redundancies of the LZW algorithm is suggested for efficent compression of voice. The V-LZW algorithm uses the differential method that reduces the codeword size as well as the length of repeated string. According to the simulation results, it could be seen teat the performance of V-LZW algorithm is better by 35% to 44% in voice compression ratio than that of the conventional modified LZW algorithm. Compared with conventional 32 kbps ADPCM coding with 26 dB SNR, V-LZW has 21 kbps transmission rate, no additional quantization error and simple hardware complexity.