• 제목/요약/키워드: projection matrix

검색결과 181건 처리시간 0.03초

Affine Projection 알고리즘을 이용한 표면 부착형 영구자석 전동기의 온라인 파라미터 추정 (Online Parameter Estimation of SPMSM using Affine Projection Algorithm)

  • 문병훈;김형우;최준영
    • 전력전자학회논문지
    • /
    • 제23권1호
    • /
    • pp.66-71
    • /
    • 2018
  • We propose an online parameter estimation method for surface-mounted permanent-magnet synchronous motor (SPMSM) using an affine projection algorithm (APA). The proposed method estimates parameters with two APAs based on the discrete-time model equation of SPMSM during motor operation. The first APA is designed to estimate inductance, and the second APA is designed to estimate resistance and flux linkage. However, in case when the d-axis current is controlled to 0A, the second APA cannot estimate resistance and flux linkage simultaneously because the matrix rank in APA becomes deficient. To overcome this problem, we temporarily inject a negative reference current input to the d-axis control loop, and the matrix in the APA then becomes full rank, which enables the simultaneous estimation of resistance and flux linkage. The proposed method is verified by PSIM simulation and an actual experiment, and the results reveal that SPMSM parameters can be estimated online during motor operation.

Nonnegative variance component estimation for mixed-effects models

  • Choi, Jaesung
    • Communications for Statistical Applications and Methods
    • /
    • 제27권5호
    • /
    • pp.523-533
    • /
    • 2020
  • This paper suggests three available methods for finding nonnegative estimates of variance components of the random effects in mixed models. The three proposed methods based on the concepts of projections are called projection method I, II, and III. Each method derives sums of squares uniquely based on its own method of projections. All the sums of squares in quadratic forms are calculated as the squared lengths of projections of an observation vector; therefore, there is discussion on the decomposition of the observation vector into the sum of orthogonal projections for establishing a projection model. The projection model in matrix form is constructed by ascertaining the orthogonal projections defined on vector subspaces. Nonnegative estimates are then obtained by the projection model where all the coefficient matrices of the effects in the model are orthogonal to each other. Each method provides its own system of linear equations in a different way for the estimation of variance components; however, the estimates are given as the same regardless of the methods, whichever is used. Hartley's synthesis is used as a method for finding the coefficients of variance components.

STOCHASTIC GRADIENT METHODS FOR L2-WASSERSTEIN LEAST SQUARES PROBLEM OF GAUSSIAN MEASURES

  • YUN, SANGWOON;SUN, XIANG;CHOI, JUNG-IL
    • Journal of the Korean Society for Industrial and Applied Mathematics
    • /
    • 제25권4호
    • /
    • pp.162-172
    • /
    • 2021
  • This paper proposes stochastic methods to find an approximate solution for the L2-Wasserstein least squares problem of Gaussian measures. The variable for the problem is in a set of positive definite matrices. The first proposed stochastic method is a type of classical stochastic gradient methods combined with projection and the second one is a type of variance reduced methods with projection. Their global convergence are analyzed by using the framework of proximal stochastic gradient methods. The convergence of the classical stochastic gradient method combined with projection is established by using diminishing learning rate rule in which the learning rate decreases as the epoch increases but that of the variance reduced method with projection can be established by using constant learning rate. The numerical results show that the present algorithms with a proper learning rate outperforms a gradient projection method.

얼굴 인식을 위한 쌍대각 2DLDA 방법 (Bilateral Diagonal 2DLDA Method for Human Face Recognition)

  • 김영길;송영준;김동우;안재형
    • 한국지능시스템학회논문지
    • /
    • 제19권5호
    • /
    • pp.648-654
    • /
    • 2009
  • 본 논문에서는 얼굴을 인식하기 위한 쌍대각 2차원 LDA를 제안하였다. 기존의 Dia2DPCA와 Dia2DLDA가 대각 방향 영상들의 행 변화량과 열 변화량 사이의 상관을 제한하기 위하여 제안되어지고 있다. 그러나 이러한 방법들은 영상들의 행방향으로 동작한다. 제한 방법에 있어서 행방향의 투영 행렬은 기존 방법과 전혀 다르게 대각 방향 얼굴 영상들의 열 변화량을 고려한 클래스 간의 공분산 행렬과 클래스 내의 공분산 행렬을 이용함으로써 얻어진다. 그리고 열방향의 투영 행렬은 대각방향 얼굴 영상들의 행 변화량을 고려한 클래스 간의 공분산 행렬과 클래스 내의 공분산 행렬을 이용함으로써 얻어진다. 좌우 양측의 투영 방법은 투영 행렬들을 좌우로 곱함으로써 적용된다. 그 결과로 특징 행렬의 차원과 계산 시간이 감소된다. ORL 얼굴 데이터베이스에서 수행된 실험들은 Frobenius, Yang, AMD와 같은 3가지 거리 척도를 사용하여 2DPCA, B2DPCA, 2DLDA 등과 같은 다른 얼굴 인식 방법들보다 제안된 방법의 인식률이 높음을 보여준다.

Three Dimensional Target Volume Reconstruction from Multiple Projection Images

  • Cheong, Kwang-Ho;Suh, Tae-Suk;Lee, Hyoung-Koo;Choe, Bo-Young
    • 한국의학물리학회:학술대회논문집
    • /
    • 한국의학물리학회 2002년도 Proceedings
    • /
    • pp.439-441
    • /
    • 2002
  • The aim of this study is to reconstruct the 3D target volume from multiple projection images. It was assumed that we were already aware of the target position exactly, and all processes were performed in Target Coordinates whose origin was the center of the target. We used six projections: two projections were used to make a Reconstruction Box and four projections were for image acquisition. Reconstruction Box was made up of voxels of 3D matrix. Projection images were transformed into 3D volume in this virtual box using geometrical based back-projection method. Algorithm was applied to an ellipsoid model and horse-shoe shaped model. Projection images were created using C program language by geometrical method and reconstruction was also accomplished using C program language and Matlab(The Mathwork Inc., USA). For ellipsoid model, reconstructed volume was slightly overestimated but target shape and position was proved to be correct. For horse-shoe shaped model, reconstructed volume was somewhat different from original target model but there was a considerable improvement in target volume determination.

  • PDF

행렬부호함수를 이용한 이산치 계통의 모델 저차화 (Model-Reduction of Linear Discrete Large-Scale Systems)

  • 천희영;박귀태;이창훈;박승규
    • 대한전기학회논문지
    • /
    • 제35권8호
    • /
    • pp.333-340
    • /
    • 1986
  • This paper presents an approach for determining the discrete reduced-order models for largescale system by using matrix sign function. We define projection operators based on the matrix sign function and develop the algorithm for model-reduction by using them. Simulation studies show that the proposed altgorithm is very useful.

  • PDF

불완전계수의 선형모형에서 추정가능함수 (Estimable functions of less than full rank linear model)

  • 최재성
    • Journal of the Korean Data and Information Science Society
    • /
    • 제24권2호
    • /
    • pp.333-339
    • /
    • 2013
  • 본 논문은 불완전계수의 모형행렬을 갖는 선형모형에서 추정가능함수를 다루고 있다. 고정효과 모형의 모수들은 일반적으로 추정가능한 모수가 아니므로 추정가능한 모수들의 함수를 구하기 위한 방법으로 완전계수의 인자분해 방법을 제시하고 있다. 완전계수의 인자분해 방법으로 구해진 추정가능함수의 타당성을 확인하기 위한 사영행렬은 불완전계수의 모형행렬을 구성하는 행벡터로 생성되는 벡터공간으로의 사영행렬과 동일함을 보여주고 있다. 완전계수의 인자분해로 추정가능함수를 구하는 방법과 모수들의 선형함수가 추정가능함수인 가의 확인을 위한 사영행렬의 이용에 관해 벡터공간의 관점에서 다루어지고 있다. 또한, 추정가능함수의 기저 구성에 관한 구체적 논의가 행해지고 있다.

대역폭 제한 조건과 Gram 행렬의 단위행렬로의 사영을 이용한 압축센싱 능동소나 송신파형 설계 (Transmission waveform design for compressive sensing active sonar using the matrix projection from Gram matrix to identity matrix and a constraint for bandwidth)

  • 이세현;이근화;임준석;정명준
    • 한국음향학회지
    • /
    • 제38권5호
    • /
    • pp.522-533
    • /
    • 2019
  • 거리-도플러 추정을 위한 압축센싱(Compressive Sensing,CS) 모델은 과소결정계인 y = Ax 선형시스템으로 표현할 수 있다. 압축센싱 기법으로 위 선형시스템의 해를 찾으려면 행렬 A가 충분히 비간섭적이고 x가 희소해야 한다. 본 연구는 행렬 A가 비간섭적이도록 행렬 A의 상호간섭성을 낮추는 동시에 소나시스템에서 요구하는 대역폭을 유지하는 송신파형 설계 방법을 제안하였다. 제안한 방법은 행렬사영으로 센싱행렬을 최적화하는 방법과 DFT(Discrete Fourier Transform) 행렬을 이용하여 원하지 않은 주파수밴드를 억압하는 두 가지 방법을 결합한 것이다. 정합필터와 압축센싱 기법을 이용하여 기존파형 LFM(Linear Frequency Modulated)과 설계한 파형의 거리-도플러 추정 성능을 비교하였다. 시뮬레이션을 통해 설계한 송신파형이 기존파형(LFM)보다 탐지성능이 우수함을 보인다.

Convergence Analysis of Noise Robust Modified AP(affine projection) Algorithm

  • Kim, Hyun-Tae;Park, Jang-Sik
    • Journal of information and communication convergence engineering
    • /
    • 제8권1호
    • /
    • pp.23-28
    • /
    • 2010
  • According to increasing projection order, the AP algorithm bas noise amplification problem in large background noise. This phenomenon degrades the performances of the AP algorithm. In this paper, we analyze convergence characteristic of the AP algorithm and then suggest a noise robust modified AP algorithm for reducing this problem. The proposed algorithm normalizes the update equation to reduce noise amplification of AP algorithm, by adding the multiplication of error power and projection order to auto-covariance matrix of input signal. By computer simulation, we show the improved performance than conventional AP algorithm.

One injection for a great projection: a quick and simple procedure for nipple reconstruction

  • Tanini, Sara;Calabrese, Sara;Lucattelli, Elena;Russo, Giulia Lo
    • Archives of Plastic Surgery
    • /
    • 제48권2호
    • /
    • pp.179-184
    • /
    • 2021
  • Women attach great importance to the presence of a three-dimensional nipple upon completion of the breast reconstruction process. To meet patients' expectations, nipple-areolar complex reconstruction should achieve symmetry in position, size, shape, texture, and color, as well as minimizing donor-site morbidity. However, it is well known that regardless of the reconstructive technique, loss of nipple projection can be reasonably expected. We developed and evaluated a quick, simple, and innovative technique using injectable Integra Flowable Wound Matrix to increase nipple projection after reconstruction. Twenty breast cancer patients who underwent nipple reconstruction resulting in unsatisfactory projection were enrolled in our retrospective study. Nipple projection was measured at the time of surgery and after 6 and 12 months. A visual analogue scale was used to assess patients' satisfaction. Our technique yielded reliable results in terms of the long-lasting maintenance of nipple projection. This method is high-priced, but cost-effective, since one kit may suffice for three patients. Furthermore, our patients were very appreciative of this technique as a single-step, minimally invasive, painless procedure with no reported necessity of re-intervention.