• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.3
• /
• pp.471-489
• /
• 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.

• Journal of Biomedical Engineering Research
• /
• v.12 no.3
• /
• pp.191-202
• /
• 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.

• MALSORI
• /
• v.55
• /
• pp.143-158
• /
• 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.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.6
• /
• pp.1127-1136
• /
• 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.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.5 no.3
• /
• pp.141-145
• /
• 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.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.53 no.11
• /
• pp.581-588
• /
• 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).

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

• Journal of Biomedical Engineering Research
• /
• v.13 no.4
• /
• pp.323-330
• /
• 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.

• Journal of KIISE:Computing Practices and Letters
• /
• v.10 no.3
• /
• pp.243-250
• /
• 2004

We describe a practical implementation of DVR (Digital Video Recording) system. And we propose a new image compression algorithm, that input video signal is divided into two parts, a moving target and a non-moving background part to achieve efficient compression of image sequences. This algorithm reorganizes a target area and a back-ground area by use of Macro Block(MB) unit on encoding scheme. The proposed algorithm allows high quality image reconstruction at low bit rates.

• The Journal of the Acoustical Society of Korea
• /
• v.16 no.1E
• /
• pp.35-40
• /
• 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.