• 한국통신학회논문지
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• 제28권10C호
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• pp.1007-1012
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• 2003

Multilayer perceptrons (MLPs)를 위한 일반적인 BP 알고리즘의 학습 속도를 개선하기 위하여 제약을 갖는 최적화 기술을 제안하고 이를 backpropagation (BP) 알고리즘에 적용한다. 먼저 잡음 제약을 갖는 LMS (noise constrained least mean square : NCLMS) 알고리즘과 영잡음 제약 LMS (ZNCLMS) 알고리즘을 BP 알고리즘에 적용한다. 이러한 알고리즘들은 다음과 같은 가정을 반드시 필요로 하여 알고리즘의 이용에 많은 제약을 갖는다. NCLMS 알고리즘을 이용한 NCBP 알고리즘은 정확한 잡음 전력을 알고 있다고 가정한다. 또한 ZNCLMS 알고리즘을 이용한 ZNCBP 알고리즘은 잡음의 전력을 0으로 가정, 즉 잡음을 무시하고 학습을 진행한다. 본 논문에서는 확장된(augmented) Lagrangian multiplier를 이용하여, 비용함수(cost function)를 변형한다. 이를 통하여 잡음에 대한 가정을 제거하고 ZNCBP와 NCBP 알고리즘을 확장, 일반화하여 적응 오류 제약 BP(adaptive error constrained BP : AECBP) 알고리즘을 유도, 제안한다. 제안한 알고리즘들의 수렴 속도는 일반적인 BP 알고리즘보다 약 30배정도 빠른 학습 속도를 나타내었으며, 일반적인 선형 필터와 거의 같은 수렴속도를 나타내었다.

• ETRI Journal
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• 제26권5호
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• pp.432-436
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• 2004

In this paper, we propose the modified uniformly most powerful (UMP) belief-propagation (BP)-based decoding algorithm which utilizes multiplicative and additive factors to diminish the errors introduced by the approximation of the soft values given by a previously proposed UMP BP-based algorithm. This modified UMP BP-based algorithm shows better performance than that of the normalized UMP BP-based algorithm, i.e., it has an error performance closer to BP than that of the normalized UMP BP-based algorithm on the additive white Gaussian noise channel for low density parity check codes. Also, this algorithm has the same complexity in its implementation as the normalized UMP BP-based algorithm.

• 대한임베디드공학회논문지
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• 제4권4호
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• pp.195-200
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• 2009

As 4G mobile communication systems require high transmission rates with reliability, the need for efficient error correcting code is increasing. In this paper, a novel LDPC (Low Density Parity Check) decoder is introduced. The LDPC code is one of the most popular error correcting codes. In order to improve performance of the LDPC decoder, we use SNR (Signal-to-Noise Ratio) estimation results to adjust coefficients of modified UMP-BP (Uniformly Most Probable Belief Propagation) algorithm which is one of widely-used LDPC decoding algorithms. An advantage of Modified UMP-BP is that it is amenable to implement in hardware. We generate the optimal values by simulation for various SNRs and coefficients, and the values are stored in a look-up table. The proposed decoder decides coefficients of the modified UMP-BP based on SNR information. The simulation results show that the BER (Bit Error Rate) performance of the proposed LDPC decoder is better than an LDPC decoder using a conventional modified UMP-BP.

• 전기전자학회논문지
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• 제26권4호
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• pp.686-692
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• 2022

본 논문에서는 스테레오 영상정합을 위하여 개선된 영역기반, 에너지 기반 알고리즘, 학습기반 구조의 정합 오류율을 비교하였다. 영역기반으로 census transform(CT), 에너지 기반으로 belief propagation(BP) 알고리즘을 선정하였다. 기존 알고리즘을 개선하고 모바일 시스템에서 스테레오 영상정합에 활용가능 하도록 임베디드 프로세서 환경에서 구현하였다. 비교 대상이 되는 학습기반의 경우에 도 적은 규모의 파라메터를 활용하는 신경망 구조를 채택하였다. 세 가지 정합방법의 오류율 비교를 위해 테스트 이미지로 Middlebury 데이터 세트 가운데 Tsukuba를 선정하고 정합 성능의 정확한 비교를 위해 비폐색, 불연속, 시차 오류율 등으로 세분화하였다. 실험 결과 CT 매칭의 오차율은 기존 알고리즘과 수정된 알고리즘으로 비교하였을 때 약 11% 성능 개선되었다. BP 매칭은 오류율에서 기존 CT 에 비하여 약 87% 우수하였다. 신경망을 이용한 학습기반과 비교 하였을 때 BP 매칭이 약 31% 우수함을 보였다.

• 센서학회지
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• 제17권2호
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• pp.87-94
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• 2008

Blood pressure (BP), one of the most important vital signs, is used to identify an emergency state and reflects the blood flow characteristics of the cardiovascular system. The conventional noninvasive method of measuring BP is inconvenient because patients must wear a cuff on their arm and the measurement process takes time. This paper proposes an algorithm for estimating the BP using the pulse transit time (PTT) of the photoplethysmography (PPG) and pressure pulse from finger at the same time as a more convenient way to measure the BP. After recording the electrocardiogram (ECG), measuring the pressure pulse, and performing PPG, we calculated the PTT from the acquired signals. Then, we used a multiple regression analysis to measure the systolic and diastolic BP indirectly. Comparing the BP measured indirectly using the proposed algorithm and the real BP measured with a sphygmomanometer, the systolic pressure had a mean error of ${\pm}3.240$ mmHg and a standard deviation of 2.530 mmHg, while the diastolic pressure had a satisfactory result, i.e., a mean error of ${\pm}1.807$ mmHg and a standard deviation of 1.396 mmHg. These results are more superior than existing method estimating blood pressure using the one PTT and satisfy the ANSI/AAMI regulations for certifying a sphygmomanometer i.e., the measurement error should be within a mean error of ${\pm}5$ mmHg and a standard deviation of 8 mmHg. These results suggest the possibility of applying our method to a portable, long-term BP monitoring system.

• 기본간호학회지
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• 제23권3호
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• pp.275-282
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• 2016

Purpose: This study was done to examine the relationship between nursing students' hearing levels and accuracy of blood pressure (BP) measurements. Methods: Participants were 107 students who had finished their fundamental nursing practice and clinical practicum and who used earphones. Data were collected from October 13 to November 30, 2014 and from April 30 to May 19, 2015. Students' hearing thresholds were examined using an audiometer. Students were assigned to take two BP measurements on BP measurement training simulators, but only the second measurement was used for analysis. Results: All nursing students' hearing levels were within normal range, and there was no significant difference found among the settings for diastolic blood pressure. However, there were significant differences between low systolic blood pressure (SBP) (below 120mmHg) and high SBP (over 140mmHg) (z=9.02, p=.011). Measurement error in SBP showed a positive correlation with hearing threshold in the right ear at frequencies of 1000Hz and 500Hz. Conclusion: Findings indicate that BP measurement error is correlated with hearing threshold at some frequencies. To reduce measurement error, nursing students should be provided with health education about hearing and to improve training for students, further studies need to examine other factors influencing BP measurement error.

• ETRI Journal
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• 제34권5호
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• pp.719-726
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• 2012

Messages are generally selected with the same probability in the encoding scheme of rateless codes for equal error protection. In addition, a belief propagation (BP) decoding scheme is generally used because of the low computational complexity. However, the probability of recovering a new message by BP decoding is reduced if both the recovered and unrecovered messages are selected uniformly. Thus, more codeword symbols than expected are required for the perfect recovery of message symbols. Therefore, a new encoding scheme with a nonuniform selection of messages is proposed in this paper. In addition, a BP-Gaussian elimination hybrid decoding scheme that complements the drawback of the BP decoding scheme is proposed. The performances of the proposed schemes are analyzed and compared with those of the conventional schemes.

• International journal of advanced smart convergence
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• 제10권2호
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• pp.175-186
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• 2021

We have studied the speed regulation of the permanent magnet synchronous motor (PMSM) servo system in this paper. To optimize the PMSM servo system's speed-control performance with disturbances, a non-linear speed-control technique using a back-propagation neural network (BP-NN) algorithm forthe controller design of the PMSM speed loop is introduced. To solve the slow convergence speed and easy to fall into the local minimum problem of BP-NN, we develope an improved BP-NN control algorithm by limiting the range of neural network outputs of the proportional coefficient Kp, integral coefficient Ki of the controller, and add adaptive gain factor β, that is the internal gain correction ratio. Compared with the conventional PI control method, our improved BP-NN control algorithm makes the settling time faster without static error, overshoot or oscillation. Simulation comparisons have been made for our improved BP-NN control method and the conventional PI control method to verify the proposed method's effectiveness.

• 한국통신학회논문지
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• 제29권9C호
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• pp.1227-1234
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• 2004

본 논문에서는 LDPC 부호의 복호 알고리즘의 하나인 Normalized-BP 알고리즘의 각각의 비트에 업데이트되는 값에 대한 신뢰도에 따라 복호 알고리즘에 필요한 표준화 인수값을 달리함으로써 성능을 향상시킬 수 있는 복호 알고리즘을 제안하였다. 제안된 복호 알고리즘은 기존의 Normalized-BP 알고리즘에 비하여 복잡도를 거의 증가시키지 않으면서 LLR-BP 알고리즘의 BER 성능에 약 0.02dB 정도까지 근접하는 성능을 나타냄을 컴퓨터 모의실험을 통하여 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.853-858
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• 1993

The error back-propagation(BP) algorithm is widely used for finding optimum weights of multi-layer neural networks. However, the critical drawback of the BP algorithm is its slow convergence of error. The major reason for this slow convergence is the premature saturation which is a phenomenon that the error of a neural network stays almost constant for some period time during learning. An inappropriate selections of initial weights cause each neuron to be trapped in the premature saturation state, which brings in slow convergence speed of the multi-layer neural network. In this paper, to overcome the above problem, Micro-Genetic algorithms(.mu.-GAs) which can allow to find the near-optimal values, are used to select the proper weights and slopes of activation function of neurons. The effectiveness of the proposed algorithms will be demonstrated by some computer simulations of two d.o.f planar robot manipulator.