• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.772-774
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• 2008

A navigation system for virtual environments using low-quality HMD(head mounted display)must quantize images when the system presents true-color image with restricted number of colors. Such navigation system quantizes an image by using fixed palette. If the system represents an image by using a variable palette which is made considering a region around the viewpoint then user can perceive a virtual environments more vividly because human visual system is sensitive to the colors variation in the region around the viewpoint. In this paper we propose a color quantization algorithm that quantize a region around the viewpoint more finely than other regions at each variation of viewpoint for virtual environments navigation system and compose virtual environments navigation system using proposed algorithm. The system quantizes an image at each variation of viewpoint and shows a quantized image to user through HMD. We tested user preferences for our proposed system and the results show that users preferred our system.

• Proceedings of the IEEK Conference
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• 2003.11c
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• pp.289-292
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• 2003

이 논문은 WCDMA 와 안테나 배열 시스템에서 저 레벨 양자화와 MUSIC 알고리즘을 사용하여 신호의 방향을 추정하는 방법을 제안한다. 추가의 Power-Up Function 이 필요 없는 방향각 방법으로 이동가입자의 위치를 알아내기 위해 안테나 배열을 이용하여, WCDMA 시스템에서 역확산 코드로 다수의 신호를 분리하고, 각 신호를 저 레벨로 양자화 시켜 MUSIC 으로 신호의 방향각을 추정하였다. 이 방법을 이용하면 단말기의 안테나 출력파워가 낮더라도 기존 방법의 에러율과 비슷함을 시뮬레이션 결과로 알 수 있고, 양자화 비트를 처리하기 위해 필요한 메모리 또한 줄일 수 있어 하드웨어의 비용을 줄일 수 있을 것이다.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.50-56
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• 2001

As the fuzzy control is applied to servo system, the hardware implementation of the fuzzy information systems requires the high speed operations, short real time control and the small size systems. The aims of this study is to develop hardware of the fuzzy information systems to be apply to servo system. In this paper, we propose a calculation method of approximate reasoning for fuzzy control based on $\alpha$ -level set decomposition of fuzzy sets by quantize $\alpha$ -cuts. This method can be easily implemented with analog hardware. The influence of quantization Bevels of $\alpha$-cuts on output from fuzzy inference engine is investigated. It is concluded that 4 quantization levels give sufficient result for fuzzy control performance of dc servo system. The hardware implementation of proposed operation method and of the defuzzification by gravity center method which is directly converted to PWM actuating signal is also presented. It is verified useful with experiment for dc servo system.

• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.157-165
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• 2020

In this paper. we propose an effective compensation scheme to the quantization error arisen from quantized learning in a machine learning on an embedded system. In the machine learning based on a gradient descent or nonlinear signal processing, the quantization error generates early vanishing of a gradient and occurs the degradation of learning performance. To compensate such quantization error, we derive an orthogonal compensation vector with respect to a maximum component of the gradient vector. Moreover, instead of the conventional constant learning rate, we propose the adaptive learning rate algorithm without any inner loop to select the step size, based on a nonlinear optimization technique. The simulation results show that the optimization solver based on the proposed quantized method represents sufficient learning performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.133-138
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• 2015

This paper presents a performance improvement of gray level co-occurrence matrix(GLCM) based on the nonuniform quantization, which is generally used to analyze the texture of images. The nonuniform quantization is given by Lloyd algorithm of recursive technique by minimizing the mean square error. The nonlinear intensity levels by performing nonuniformly the quantization of image have been used to decrease the dimension of GLCM, that is applied to reduce the computation loads as a results of generating the GLCM and calculating the texture parameters by using GLCM. The proposed method has been applied to 30 images of $120{\times}120$ pixels with 256-gray level for analyzing the texture by calculating the 6 parameters, such as angular second moment, contrast, variance, entropy, correlation, inverse difference moment. The experimental results show that the proposed method has a superior computation time and memory to the conventional 256-level GLCM method without performing the quantization. Especially, 16-gray level by using the nonuniform quantization has the superior performance for analyzing textures to another levels of 48, 32, 12, and 8 levels.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.409-412
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• 2000

본 논문에서는 기존의 결정론적 볼츠만 머신의 학습알고리듬을 수정하여 양자화결합을 갖는 볼츠만 머신에도 적용할 수 있는 알고리듬을 제안하였다. 제안한 알고리듬은 2-입력 XOR문제와 3-입력 패리티문제에 적용하여 성능을 분석하였다. 그 결과 하중이 대폭적으로 양자화된 네트워크도 학습이 가능하다는 것은 은닉 뉴런수를 증가시키면 한정된 하중값의 범위로 유지할 수 있다는 것을 보여주었다. 또한 1회에 갱신하는 하중의 개수 m$_{s}$를 제어함으로써 학습계수를 제어하는 효과가 얻어지는 것을 확인하였다..

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12A
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• pp.1146-1152
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• 2005

In this paper, we propose a compressed quantized channel state information (CQCSI) feedback scheme for multi-carrier mobile communication systems. The proposed CQCSI figures out the contiguous subsequences of equal QCSI's as separate types of runs across the subcarriers, and then encodes the types of runs using a truncated Huffman coding algorithm. Computer simulation shows that the proposed algorithm can reduce the QCSI feedback up to one tenth of the uncompressed, while providing a comparable performance with the conventional QCSI feedback schemes. To cope with special cases when the frequency selective fading is very high, we also propose a restricted CQCSI feedback scheme. The restricted CQCSI feedback has been proved under vehicular B channel model.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.429-435
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• 2003

In this paper, we propose improved binary tree vector quantization with consideration of spatial sensitivity which is one of the human visual properties. We combine weights in consideration with the responsibility of human visual system according to changes of three primary color in blocks of images with the process of splitting nodes using eigenvector in binary tree vector quantization. Also we propose the novel quality measure of the quantization images that applies MTF(modulation transfer function) to luminance value of quantization error of color image. The test results show that the proposed method generates the quantized images with fine color and performs better than the conventional method in terms of clustering the similar regions. Also the proposed method can get less quantized level images and can reduce the resource occupied by the quantized image.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.592-593
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• 2018

사물 인터넷 환경에서 제어 시스템이 네트워크에 연결되면서 정밀 제어를 위한 양자화에 대한 고려가 중요해 지고 있다. 본 연구에서는 프로세스 잡음이 존재하는 이산 시불변 선형 시스템에서 실용적 관찰성을 달성하기 위해서 필요로 하는 데이터 양에 대한 조건을 제시한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.534-535
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• 2023

최근 CNN 기반 객체인식 시스템은 고정밀도 모델을 기반으로 정확도를 높이고 있다. 하지만 고정밀도 모델일수록 모델의 크기가 늘어나고 더 많은 하드웨어 자원을 필요로 한다. 따라서 모델 경량화 기술이 많이 연구되고 있으며, 그 중에 대표적인 경량화 기술이 양자화 기술이다. 양자화 기술은 파라미터의 크기와 연산 오버헤드를 줄이지만, 정확도 역시 줄어들게 된다. 영자화와 정확도의 상관관계를 분석하기 위해서 본 논문에서는 INT8 과 FP32 을 이용한 Mixed precision CNN 을 실행시키기 위한 프레임워크를 구성하고, 임베디드 시스템 환경에서의 INT8 연산에 기반하여 맞추어 각 layer 별 Mixed Precision 연산을 수행하여 보고, 모델의 정확도를 측정하여 분석하여 보았다.