• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.242-251
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• 2020

Recently, many deep convolutional neural networks for image super-resolution have been studied. Existing deep learning-based super-resolution algorithms are architecture that up-samples the resolution at the end of the network. The post-upsampling architecture has an inefficient structure at large scaling factor result of predicting a lot of information for mapping from low-resolution to high-resolution at once. In this paper, we propose a single image super-resolution using Channel Attention Residual Dense Block based on an iterative up-down sampling architecture. The proposed algorithm efficiently predicts the mapping relationship between low-resolution and high-resolution, and shows up to 0.14dB performance improvement and enhanced subjective image quality compared to the existing algorithm at large scaling factor result.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.191-196
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• 2005

Knowing the time of the process change could lead to quicker identification of the responsible special cause and less process down time, and it could help to reduce the probability of incorrectly identifying the special cause. In this paper, we propose a MLE of the process change point when control charts with the fixed sampling rate (FSR) scheme or the variable sampling rate (VSR) scheme monitor a process to detect changes in the process mean and/or variance of a normal quality variable.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.136-139
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• 2004

This thesis is realization of embedded system that of MPEG-2 down conversion using IDCT. A method for down conversion of MPEG compressed video is to perform low-pass filtering and sub-sampling after full decompression. However, this method is need large memory and high computational complexity. Recent research has been focussed on the down conversion in the DCT domain. But DCT method is reduced image qualify. The embedded system is require low complexity, and high speed algorithm. When applied to embedded system that down conversion method, DCT method is played average 29 frame per second, and better 25% than spatial-domain down conversion.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.9
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• pp.9-18
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• 1998

A single RF transceiver chip for an extended GSM handset application was designedm, fabricated and evaluated. A RFIC was fabricated by using silicon BiCMOS process, and then packaged in 80 pin TQFP of $10 {\times} 10 mm^{2}$ in size. As a result, it was achieved guite reasonable integraty and good RF performance at the operation voltage of 3.3V. This paper describes development results of RF receiver section of the RFIC, which includes LNA, down conversion mixer, AGC, switched capacitor filter and down sampling mixer. The test results show that RF receiver section is well operated within frequency range of 925 ~960 MHz, which is defined on the extended GSM specification (E-GSM). The receiver section also reveals moderate power consumption of 67 mA and minimum detectable signal of -105 dBm.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.4
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• pp.483-488
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• 2015

This paper implements a long-term monitoring system (LMS) for ship's engine performance analysis (SEPA) based on the web, for the purpose of the communication speed and engine maintenance. This system is composed of a simulator, monitoring module with a multi channel A/D converter, monitoring computer, network attached storage (NAS), RS485 serial and wireless internet communication system. The existing products monitor the information transmitted from pressure sensors installed in the upper parts of each of engines in the local or web computer, but have a delay in the communication speed and errors in long-term monitoring due to the large volume of sampling pressure data. To improve these problems, the monitoring computer saves the sampling pressure data received from the pressure sensors in NAS, monitors the long-term sampling data generated by the sectional down sampling method on a local computer, and transmits them to the web for long-term monitoring. Because this method has one tenth of the original sampling data, it will use memory with small capacity, save communication cost, monitor the long-term sampling data for 30 days, and as a result, make a great contribution to engine maintenance.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.6
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• pp.876-877
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• 1995

The techniques for the estimation of motion vector from the image sequence assume implicitly that the intensity of image is constant through the time. But this assumption can be distored by such causes as the added noises and the sub-pel motion following the sampling, and the errors can be generated on the motion estimation by the change of intensity. In this paper, we analyzed theoretically the effect of the change of intensity by the noise on the motion estimation with the white Gaussian noise. We know a fact that the signal may be fluctuated to reduce the effect of the noise and so the sampling rate have to make down. Also we confirmed the theoretically analysis through the experiments which investigated the relation between the noises and the sampling rates.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.107-108
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• 2007

In this paper, a cosine-modulated filter bank with a modified synthesis part is proposed for arbitrary scaling of images, whereby down/up-sampling kernels based on a compactly supported sampling function (CSSF) are utilized. Also, an optimized adaptive interpolation technique is incorporated into the filter bank structure to compensate for quality degradation arising in scaled images. Finally, simulation results verify that high quality images with arbitrary sizes can be obtained by applying the proposed approach.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.115-123
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• 2000

In this paper, a block FIR(Finite Impulse Response) filtering architecture is proposed for IF digital down converter. Digital down converter consists of digital mixers. decimation filters and down samplers. In this proposed structure, it is shown that a efficient parallel decimation filter architecture can be produced by cancellation of inherent up sampling of the block filter and following down sampler Furthermore. it is shown that computational complexity of the proposed architecture is reduced by exploiting the block FIR structure and zero values of the digital mixers.

• ETRI Journal
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• v.26 no.6
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• pp.555-559
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• 2004

We propose an efficient digital IF down converter architecture for dual-mode WCDMA/cdma2000 based on the concept of software defined radio. Multi-rate digital filters and fractional frequency conversion techniques are adopted to implement the front end of a dual-mode receiver for WCDMA and cdma2000. A sub-sampled digital IF stage was proposed to support both WCDMA and cdma2000 while lowering the sampling frequency. Use of a CIC filter and ISOP filter combined with proper arrangement of multi-rate filters and common filter blocks resulted in optimized hardware implementation of the front end block in 292k logic gates.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.171-177
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• 2011

Accuracy and computing time are considerable issues in machine learning. In general, the computing time for data analysis is increased in proportion to the size of given data. So, we need a sampling approach to reduce the size of training data. But, the accuracy of constructed model is decreased by going down the data size simultaneously. To solve this problem, we propose a new statistical sampling method having similar performance to the total data. We suggest a rule to select optimal sampling techniques according to given data structure. This paper shows a sampling method for reducing computing time with keeping the most of accuracy using cluster sampling, stratified sampling, and systematic sampling. We verify improved performance of proposed method by accuracy and computing time between sample data and total data using objective machine learning data sets.