• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.344-350
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• 2006

The software GPS receivers based on the SDR technology provide the ability to easily adapt the other signal processing algorithms without changing or modifying the hardware of the GPS receiver. However, it is difficult to implement the software GPS receivers using a commercial processor because of the heavy computational burden for processing the GPS signals in real-time. This paper proposes an efficient GPS signal processing scheme to reduce the computational burden for processing the GPS signals in the software GPS receiver, which uses a fundamental notion compressing the replica signals and the encoded look-up table method to generate correlation values between GPS signals and replica signals. In this paper, it is explained that the computational burden of the proposed scheme is much smaller than that of the typical GPS signal processing scheme. Finally, the processing time of the proposed scheme is compared with that of the typical scheme, and the improvement in the aspect of the computational burden is also shown.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.277-280
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• 2001

The preprocessing is very important course in speech signal processing. It influence the compression-rate in speech coding and the recognition-rate in speech recognition etc. In this paper, we propose that minimizing window-influence method with pitch period and start points. The proposed method is available for voiced detection and word labeling.

• Journal of Biomedical Engineering Research
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• v.16 no.1
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• pp.17-24
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• 1995

This paper presents a new compression method (or ECG data using iterated contractive transformations. The method represents any range of ECG signal by piecewise self-afrine fractal Interpolation (PSAFI). The piecewise self-afrine rractal model is used where a discrete data set is viewed as being composed of contractive arfine transformation of pieces of itself. This algorithm was evaluated using MIT/BIH arrhythmia database. PSAFI is found to yield a relatively low reconstruction error for a given compression ratio than conventional direct compression methods. The compression ratio achieved was 883.9 bits per second (bps) - an average percent rms difference (AFRD) of 5.39 percent -with the original 12b ECG samples digitized at 400 Hz.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.129-133
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• 2023

Image compression is a fundamental technique in the field of digital image processing, which will help to decrease the storage space and to transmit the files efficiently. Recently many deep learning techniques have been proposed to promise results on image compression field. Since many image compression techniques have artifact problems, this paper has compared two deep learning approaches to verify their performance experimentally to solve the problems. One of the approaches is a deep autoencoder technique, and another is a deep convolutional neural network (CNN). For those results in the performance of peak signal-to-noise and root mean square error, this paper shows that deep autoencoder method has more advantages than deep CNN approach.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.67-74
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• 2015

BTC (Block Truncation Coding) image compression is simple to implement by hardware and has excellent edge retention capability of image, image compression techniques are widely used in LCD overdrive. In this paper, to maintain high visual quality and has high compression rate, Multi-Mode BTC (MM-BTC) algorithm is proposed. The MM-BTC has high compression rate using advanced Y-based BTC method and has high visual quality using improved 2-level and 4-level BTC method in this paper. As shown in simulation results, MM-BTC improves still image PSNR (Peak Signal to Noise Ratio) up to 2.34 dB as compared with other algorithms. When the MM-BTC is applied to LCD overdrive, MM-BTC improves moving picture PSNR up to 2.33 dB as compared with other algorithms in literature.

• The Journal of the Korea Contents Association
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• v.18 no.3
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• pp.299-308
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• 2018

This study focused on the fact that medical images that are issued at different hospitals may affect image quality on PACS when different software is used. A university hospital image was copied to the DICOM file and registered on the PACS of the university hospital B. The capacity and image quality of the software used in the university hospital were evaluated by SNR, CNR and histogram. As the compression ratio increased, SNR and CNR tended to decrease. Note that Lossless Compression decreased the data size by half compared to No Compression, but SNR and CNR did not change. As a result of the histogram analysis, the information loss due to the underflow phenomenon was conspicuous. When moving to another hospital, No compression or lossless compression method should be used. In conclusion, it is useful to use the lossless compression method, considering waiting time and economic efficiency in uploading.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.6 s.312
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• pp.76-82
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• 2006

In this paper, the biomedical signal compression method, which is combined with the multi-stage vector quantization and wavelet lifting scheme, is proposed. It utilizes the property of wavelet coefficients that give emphasis on approximation coefficients. The transmitted codebook index consists of the code vectors obtained by wavelet lifting coefficients of ECG and error signals from the 1024 block length, respectively. Each codebook is adaptively updated by the method comparing to the distance of input codevectors with candidate codevectors by using an pre-defined threshold value. The proposed compression method showed blow 3% in term of PRD and 276.62 bits/sec in term of CDR.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.653-659
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• 2011

In general, electrocardiogram(ECG) signals are sampled with a frequency over 200Hz and stored for a long time. It is required to compress data efficiently for storing and transmitting them. In this paper, a method for compression of ECG data is proposed, using by Non Uniform B-spline approximation, which has been widely used to approximation theory of applied mathematics and geometric modeling. ECG signals are compressed and reconstructed using B-spline basis function which curve has local controllability and control a shape and curve in part. The proposed method selected additional knot with each step for minimizing reconstruction error and reduced time complexity. It is established that the proposed method using B-spline approximation has good compression ratio and reconstruct besides preserving all feature point of ECG signals, through the experimental results from MIT-BIH Arrhythmia database.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.8 no.4
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• pp.145-150
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• 1983

The runlength coding algorithm widely used for graphic data compression is extended for multi-level general images. It is applied to the quantized prediction error signal obtained by a simple predictor and quantizer. It is shown that this DPCM/RLC algorithm of a modest complexity performs much better than the conventional discrete consine transform and DPCM methods.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2262-2264
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• 1998

This paper propose a new method for the discrete signal : Discrete Wavelet Transform(DWT). This paper is a brief introduction to the DWT and applies the DWT coding for the audio data as an example. We can have a number of hint about the compression algorithm of multimedia resources and the high performance of transmission and storage.