• 제목/요약/키워드: optimal iterative methods

검색결과 91건 처리시간 0.022초

An importance sampling for a function of a multivariate random variable

  • Jae-Yeol Park;Hee-Geon Kang;Sunggon Kim
    • Communications for Statistical Applications and Methods
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    • 제31권1호
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    • pp.65-85
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    • 2024
  • The tail probability of a function of a multivariate random variable is not easy to estimate by the crude Monte Carlo simulation. When the occurrence of the function value over a threshold is rare, the accurate estimation of the corresponding probability requires a huge number of samples. When the explicit form of the cumulative distribution function of each component of the variable is known, the inverse transform likelihood ratio method is directly applicable scheme to estimate the tail probability efficiently. The method is a type of the importance sampling and its efficiency depends on the selection of the importance sampling distribution. When the cumulative distribution of the multivariate random variable is represented by a copula and its marginal distributions, we develop an iterative algorithm to find the optimal importance sampling distribution, and show the convergence of the algorithm. The performance of the proposed scheme is compared with the crude Monte Carlo simulation numerically.

Deep Learning-Based Inverse Design for Engineering Systems: A Study on Supervised and Unsupervised Learning Models

  • Seong-Sin Kim
    • International Journal of Internet, Broadcasting and Communication
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    • 제16권2호
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    • pp.127-135
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    • 2024
  • Recent studies have shown that inverse design using deep learning has the potential to rapidly generate the optimal design that satisfies the target performance without the need for iterative optimization processes. Unlike traditional methods, deep learning allows the network to rapidly generate a large number of solution candidates for the same objective after a single training, and enables the generation of diverse designs tailored to the objectives of inverse design. These inverse design techniques are expected to significantly enhance the efficiency and innovation of design processes in various fields such as aerospace, biology, medical, and engineering. We analyzes inverse design models that are mainly utilized in the nano and chemical fields, and proposes inverse design models based on supervised and unsupervised learning that can be applied to the engineering system. It is expected to present the possibility of effectively applying inverse design methodologies to the design optimization problem in the field of engineering according to each specific objective.

A comparative study of low-complexity MMSE signal detection for massive MIMO systems

  • Zhao, Shufeng;Shen, Bin;Hua, Quan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권4호
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    • pp.1504-1526
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    • 2018
  • For uplink multi-user massive MIMO systems, conventional minimum mean square error (MMSE) linear detection method achieves near-optimal performance when the number of antennas at base station is much larger than that of the single-antenna users. However, MMSE detection involves complicated matrix inversion, thus making it cumbersome to be implemented cost-effectively and rapidly. In this paper, we first summarize in detail the state-of-the-art simplified MMSE detection algorithms that circumvent the complicated matrix inversion and hence reduce the computation complexity from ${\mathcal{O}}(K^3)$ to ${\mathcal{O}}(K^2)$ or ${\mathcal{O}}(NK)$ with some certain performance sacrifice. Meanwhile, we divide the simplified algorithms into two categories, namely the matrix inversion approximation and the classical iterative linear equation solving methods, and make comparisons between them in terms of detection performance and computation complexity. In order to further optimize the detection performance of the existing detection algorithms, we propose more proper solutions to set the initial values and relaxation parameters, and present a new way of reconstructing the exact effective noise variance to accelerate the convergence speed. Analysis and simulation results verify that with the help of proper initial values and parameters, the simplified matrix inversion based detection algorithms can achieve detection performance quite close to that of the ideal matrix inversion based MMSE algorithm with only a small number of series expansions or iterations.

수정된 generalized Landweber 방법을 이용한 ECT 영상 복원 (Image reconstruction in electrical capacitance tomography based on modified generalized Landweber method)

  • 이성훈;장재덕;김용성;김경연;최봉열
    • 전자공학회논문지SC
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    • 제43권5호
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    • pp.68-79
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    • 2006
  • ECT는 측정된 커패시턴스 값을 이용하여 유전 물체의 유전율 분포를 가시화하기 위해 사용되는 비접촉 영상 복원 기술이다. 영상 복원시 수렴 속도 개선과 영상의 질 향상을 위해 다양한 반복적 영상 복원 방법들이 있으며, Landweber 방법은 널리 사용되고 있는 ECT의 영상 복원 방법 중 하나이다. 본 논문에서는 ECT 영상 복원에서 수렴 속도를 개선하기 위해 수정된 generalized Landweber 방법을 제안한다. 특히, Shaping 행렬을 가지는 generalized Landweber 방법에 가속항을 추가하고 최적화 계수를 해석적으로 결정한다. 다양한 컴퓨터 모의 실험을 통해 제안한 방법의 타당성을 입증한다.

데이터 전송을 위한 최적 FIR 필터 설계 (Design of Optimal FIR Filters for Data Transmission)

  • 이상욱;이용환
    • 한국통신학회논문지
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    • 제18권8호
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    • pp.1226-1237
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    • 1993
  • 제한된 주파수 대역폭을 이용하여 신호를 전송하기 위해서는 여러종류의 특성을 갖는 필터들이 필요하다. 이 논문에서는 이러한 필터들을 효율적으로 설계하기위한 두가지 방식을 제시하였다. 특히 fractionally-spaced(FS) 구조가 사용될때 더욱 효율적으로 필터를 설계할 수 있다. FS 구조의 특성을 최소자승 오차 방식과 결합하여, 출력오차에 영향을 주지않고, 적절한 주파수 특성을 갖는 SF 필터 설계 방식을 제시하였다. 예로, noise 신호들을 적절히 이용하면, 한개의 SF 필터가, QAM 복조에 필요한 phase splitter, 수신 필터 그리고 등화기 기능까지 갖도록 설계할 수 있다. 두번째로 임의의 주파수 특성이 요구되는 필터의 설계 방식을 제시하였다. weighting factor를 이용한 최소자숭법을 iterative하게 사용하여 최적설계를 얻는다. 이를위해 weighting factor를 효율적으로 update하기 위한 새로운 알고리듬을 이용하였다. 마지막으로, 더욱 복잡한 조건을 갖는 필터를, 이 두가지 방식을 같이 이용하여, 효율적으로 설계할 수 있는것을 보였다.

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설계민감도를 이용한 철근콘크리트 뼈대구조의 최적화 (Optimal Design of Reinforced Concrete Frames using Sensitivity Analysis)

  • 변근주;최홍식
    • 대한토목학회논문집
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    • 제9권1호
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    • pp.33-40
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    • 1989
  • 철근 콘크리트 뼈대구조는 설계변수가 많고, 목적함수의 제약조건이 복잡하여 주로 반복적인 재해석에 의하여 최적해에 접근하는 방법이 사용되고 있다. 본 연구에서는 다단계분할(multilevel decomposition)에 의하여 최적화 문제를 형성하여 재해석과정을 줄이고 효과적으로 설계변수를 취할 수 있도록 하였다. 최적화의 단계는 첫째 단계에서 비선형거동에 의한 재분배모멘트의 설계공간을 계산하여 설계모멘트에 대한 제약조건식을 형성하고, 둘째 단계에서는 재분배 모멘트를 최적화하였으며, 셋째 단계에서는 설계단면을 최적화하였다. 이때 재분배 모멘트의 최적화에 따른 첫째 단계의 모멘트의 설계공간의 변화는 부재력 변화량 추정(force approximation technique)에 의하여 수정하도록 하며, 변수를 단계별로 줄여 수렴을 가속화시킬 수 있도록 하였다. 최적화 문제의 목적함수로는 경비함수를 취하였으며 영국 CP110의 한계상태설계법을 이용하여 부재의 응력제약조건식을 유도하고, 설계예를 통하여 본 연구의 타당성과 효율성을 구명하였다.

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센터 필라트림의 FMH 충격성능 향상을 위한 순차적 실험계획법과 인공신경망 기반의 최적설계 (Optimum Design Based on Sequential Design of Experiments and Artificial Neural Network for Enhancing Occupant Head Protection in B-Pillar Trim)

  • 이정환;서명원
    • 대한기계학회논문집A
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    • 제37권11호
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    • pp.1397-1405
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    • 2013
  • 본 연구에서 탑승자 머리 보호를 위한 센터 필라 트림의 리브 패턴 최적설계는 두 가지 방법에 의해 수행된다. 첫째는 실험계획법과 반응표면법을 이용한 근사최적화 기법으로써, 상대적으로 큰 비중을 차지하는 해석비용 저감을 위하여 근사모델 구성에 필요한 최소한의 해석만을 수행하고 실제 최적화 과정에는 구성된 모델을 이용함으로써 근사적으로 최적 점을 찾아가는 방법이다. 하지만 이러한 방법은 시행착오적인 반복과정을 거쳐야 하는 단점이 있다. 따라서 저자들의 선행연구에서 제안한 순차적 실험계획법과 인공신경망을 이용하여 인자의 상한 또는 하한에 걸리지 않는 근사최적 해를 체계적인 반복과정을 통해 도출하고자 하며, 이를 수학적인 예제와 구조물 문제에 적용함으로써 실용성을 확인하고자 한다.

Geolocation Spectrum Database Assisted Optimal Power Allocation: Device-to-Device Communications in TV White Space

  • Xue, Zhen;Shen, Liang;Ding, Guoru;Wu, Qihui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권12호
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    • pp.4835-4855
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    • 2015
  • TV white space (TVWS) is showing promise to become the first widespread practical application of cognitive technology. In fact, regulators worldwide are beginning to allow access to the TV band for secondary users, on the provision that they access the geolocation database. Device-to-device (D2D) can improve the spectrum efficiency, but large-scale D2D communications that underlie TVWS may generate undesirable interference to TV receivers and cause severe mutual interference. In this paper, we use an established geolocation database to investigate the power allocation problem, in order to maximize the total sum throughput of D2D links in TVWS while guaranteeing the quality-of-service (QoS) requirement for both D2D links and TV receivers. Firstly, we formulate an optimization problem based on the system model, which is nonconvex and intractable. Secondly, we use an effective approach to convert the original problem into a series of convex problems and we solve these problems using interior point methods that have polynomial computational complexity. Additionally, we propose an iterative algorithm based on the barrier method to locate the optimal solution. Simulation results show that the proposed algorithm has strong performance with high approximation accuracy for both small and large dimensional problems, and it is superior to both the active set algorithm and genetic algorithm.

Impact of Model-Based Iterative Reconstruction on the Correlation between Computed Tomography Quantification of a Low Lung Attenuation Area and Airway Measurements and Pulmonary Function Test Results in Normal Subjects

  • Kim, Da Jung;Kim, Cherry;Shin, Chol;Lee, Seung Ku;Ko, Chang Sub;Lee, Ki Yeol
    • Korean Journal of Radiology
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    • 제19권6호
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    • pp.1187-1195
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    • 2018
  • Objective: To compare correlations between pulmonary function test (PFT) results and different reconstruction algorithms and to suggest the optimal reconstruction protocol for computed tomography (CT) quantification of low lung attenuation areas and airways in healthy individuals. Materials and Methods: A total of 259 subjects with normal PFT and chest CT results were included. CT scans were reconstructed using filtered back projection, hybrid-iterative reconstruction, and model-based IR (MIR). For quantitative analysis, the emphysema index (EI) and wall area percentage (WA%) were determined. Subgroup analysis according to smoking history was also performed. Results: The EIs of all the reconstruction algorithms correlated significantly with the forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) (all p < 0.001). The EI of MIR showed the strongest correlation with FEV1/FVC (r = -0.437). WA% showed a significant correlation with FEV1 in all the reconstruction algorithms (all p < 0.05) correlated significantly with FEV1/FVC for MIR only (p < 0.001). The WA% of MIR showed the strongest correlations with FEV1 (r = -0.205) and FEV1/FVC (r = -0.250). In subgroup analysis, the EI of MIR had the strongest correlation with PFT in both eversmoker and never-smoker subgroups, although there was no significant difference in the EI between the reconstruction algorithms. WA% of MIR showed a significantly thinner airway thickness than the other algorithms ($49.7{\pm}7.6$ in ever-smokers and $49.5{\pm}7.5$ in never-smokers, all p < 0.001), and also showed the strongest correlation with PFT in both ever-smoker and never-smoker subgroups. Conclusion: CT quantification of low lung attenuation areas and airways by means of MIR showed the strongest correlation with PFT results among the algorithms used, in normal subjects.

Cycle-Consistent Generative Adversarial Network: Effect on Radiation Dose Reduction and Image Quality Improvement in Ultralow-Dose CT for Evaluation of Pulmonary Tuberculosis

  • Chenggong Yan;Jie Lin;Haixia Li;Jun Xu;Tianjing Zhang;Hao Chen;Henry C. Woodruff;Guangyao Wu;Siqi Zhang;Yikai Xu;Philippe Lambin
    • Korean Journal of Radiology
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    • 제22권6호
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    • pp.983-993
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    • 2021
  • Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.