• 전기전자학회논문지
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• 제22권3호
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• pp.558-564
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• 2018

In distributed estimation where each node can collect only partial information on the parameter of interest without communication between nodes and quantize it before transmission to a fusion node which conducts estimation of the parameter, we consider a novel quantization technique employed at local nodes. It should be noted that the performance can be greatly improved if each node can transmit its measurement to one designated node (namely, head node) which can quantize its estimate using the total rate available in the system. For this case, the best strategy at the head node would be simply to partition the parameter space using the generalized Lloyd algorithm, producing the global codewords, one of which is closest to the estimate is transmitted to a fusion node. In this paper, we propose an iterative design algorithm that seeks to efficiently assign the codewords into each of quantization partitions at nodes so as to achieve the performance close to that of the system with the head node. We show through extensive experiments that the proposed algorithm offers a performance improvement in rate-distortion perspective as compared with previous novel techniques.

• 한국음향학회지
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• 제29권4호
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• pp.286-293
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• 2010

기존 데이터 압축 방식에는 크게 resolution-constrained quantization (RCQ) 방식과entropy-constrained quantization (ECQ) 방식이 있다. RCQ 방식은 고정 비트율 전송을 가능하게 하지만 셀 크기의 변화에 따른 이상 신호왜곡이 발생하며, ECQ 방식은 셀 크기가 고정된 대신에 이상 비트율 할당 문제가 발생한다. 본 논문에서는 기존 RCQ 방식의 대표적인 학습기법인 generalized Lloyd algorithm (GLA)을 개선한 cell-size constrained vector quantization (CCVQ) 방식을 제안한다. CCVQ 알고리즘은 셀 크기에 따라 유동적으로 패널티 척도를 주는 방식으로 기존의 RCQ와 ECQ 사이의 soft-decision을 가능하게 한다. 제안 알고리즘을 사용할 경우 기존의 GLA에 비해 약간의 평균왜곡 증가는 발생하나 이상 신호왜곡을 줄일 수 있다.

• 대한전자공학회논문지SP
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• 제49권3호
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• pp.74-80
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• 2012

고정 비트율을 사용하는 resolution-constrained quantization 방식은 입력 데이터 분포에 따라 보로노이 셀의 크기가 달라지므로 이상 신호왜곡 (distortion outliers)을 발생시킨다. 본 논문에서는 generalized Lloyd algorithm (GLA)과 cell-size constrained vector quantization (CCVQ) 방식을 결합하여 이상 신호왜곡을 줄이는 벡터 양자화 방식을 제안한다. 즉, 왜곡에 대한 문턱 값에 따라서 데이터 분포를 내부와 외부영역으로 나누고, 각각 CCVQ와 GLA 방식을 사용하여 학습하도록 한다. 데이터 분포가 높은 내부영역에 CCVQ 방식을 사용하게 됨에 따라 GLA를 사용하는 외부영역에서 사용이 가능한 셀의 개수가 늘어나게 되며, 이로 인해 이상 신호왜곡을 줄일 수 있었다. 또한, 실제 코딩 환경에서는 일반적으로 training과 test 데이터의 분포가 다르게 나타나는 소스 불일치 (source mismatch) 문제가 발생하게 된다. 제안하는 방식은 source mismatch 문제로 인해 일어나는 신호왜곡과 이상 신호왜곡에 대해서도 성능 개선을 가능하게 하였다.

• Journal of information and communication convergence engineering
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• 제12권4호
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• pp.215-220
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• 2014

We consider quantization optimized for distributed estimation, where a set of sensors at different sites collect measurements on the parameter of interest, quantize them, and transmit the quantized data to a fusion node, which then estimates the parameter. Here, we propose an iterative quantizer design algorithm with a weighted distance rule that allows us to reduce a system-wide metric such as the estimation error by constructing quantization partitions with their optimal weights. We show that the search for the weights, the most expensive computational step in the algorithm, can be conducted in a sequential manner without deviating from convergence, leading to a significant reduction in design complexity. Our experments demonstrate that the proposed algorithm achieves improved performance over traditional quantizer designs. The benefit of the proposed technique is further illustrated by the experiments providing similar estimation performance with much lower complexity as compared to the recently published novel algorithms.

• 대한전자공학회논문지
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• 제27권1호
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• pp.105-111
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• 1990

In this paper, fast algorithms to generate the codebook of vector quantization in image coding, are proposed. And an efficient algorithm to guess a initial codebook, namely, binary splitting method, is proposed. We generated the initial codebook by binary splitting method and then reduced the searching time using Iterative Optimization algorithm as an alternate to the generalized Lloyd algorithm and several information from binary splitting method. And the searching time and performance can be traded off by varying the searching range. With this proposed algorithm, the computation time can be reduced by a factor of 60 Without any degradation of image quality.

• Journal of information and communication convergence engineering
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• 제13권3호
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• pp.152-158
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• 2015

We consider the problem of designing independently operating local quantizers at nodes in distributed estimation systems, where many spatially distributed sensor nodes measure a parameter of interest, quantize these measurements, and send the quantized data to a fusion node, which conducts the parameter estimation. Motivated by the discussion that the estimation accuracy can be improved by using the quantized data with a high probability of occurrence, we propose an iterative algorithm with a simple design rule that produces quantizers by searching boundary values with an increased likelihood. We prove that this design rule generates a considerably reduced interval for finding the next boundary values, yielding a low design complexity. We demonstrate through extensive simulations that the proposed algorithm achieves a significant performance gain with respect to traditional quantizer designs. A comparison with the recently published novel algorithms further illustrates the benefit of the proposed technique in terms of performance and design complexity.

• Journal of information and communication convergence engineering
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• 제16권3호
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• pp.142-147
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• 2018

We present a practical design algorithm for quantizers at nodes in distributed systems in which each local measurement is quantized without communication between nodes and transmitted to a fusion node that conducts estimation of the parameter of interest. The benefits of vector quantization (VQ) motivate us to incorporate the VQ strategy into our design and we propose a low-complexity design technique that seeks to assign vector codewords into sets such that each codeword in the sets should be closest to its associated local codeword. In doing so, we introduce new distance metrics to measure the distance between vector codewords and local ones and construct the sets of vector codewords at each node to minimize the average distance, resulting in an efficient and independent encoding of the vector codewords. Through extensive experiments, we show that the proposed algorithm can maintain comparable performance with a substantially reduced design complexity.

• 전기전자학회논문지
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• 제23권2호
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• pp.710-715
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• 2019

We consider parameter estimation in distributed systems in which measurements at local nodes are quantized in a non-regular manner, where multiple codewords are mapped into a single local measurement. For the system with non-regular quantization, to ensure a perfect independent encoding at local nodes, a local measurement can be encoded into a set of a great number of codewords which are transmitted to a fusion node where estimation is conducted with enormous computational cost due to the large cardinality of the sets. In this paper, we propose an efficient estimation technique that can handle the non-regular quantized data by efficiently finding the feasible combination of codewords without searching all of the possible combinations. We conduct experiments to show that the proposed estimation performs well with respect to previous novel techniques with a reasonable complexity.