Large-Scale Dwell Time Algorithm for MRF

Author(s):  
Li Longxiang ◽  
Zhang Xuejun
2011 ◽  
Vol 23 (12) ◽  
pp. 3207-3212
Author(s):  
罗丽丽 Luo Lili ◽  
何建国 He Jianguo ◽  
王亚军 Wang Yajun ◽  
张云飞 Zhang Yunfei ◽  
黄文 Huang Wen ◽  
...  

Micromachines ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 471
Author(s):  
Yajun Wang ◽  
Yunfei Zhang ◽  
Renke Kang ◽  
Fang Ji

The dwell time algorithm is one of the key technologies that determines the accuracy of a workpiece in the field of ultra-precision computer-controlled optical surfacing. Existing algorithms mainly consider meticulous mathematics theory and high convergence rates, making the computation process more uneven, and the flatness cannot be further improved. In this paper, a reasonable elementary approximation algorithm of dwell time is proposed on the basis of the theoretical requirement of a removal function in the subaperture polishing and single-peak rotational symmetry character of its practical distribution. Then, the algorithm is well discussed with theoretical analysis and numerical simulation in cases of one-dimension and two-dimensions. In contrast to conventional dwell time algorithms, this proposed algorithm transforms superposition and coupling features of the deconvolution problem into an elementary approximation issue of function value. Compared with the conventional methods, it has obvious advantages for improving calculation efficiency and flatness, and is of great significance for the efficient computation of large-aperture optical polishing. The flatness of φ150 mm and φ100 mm workpieces have achieved PVr150 = 0.028 λ and PVcr100 = 0.014 λ respectively.


2001 ◽  
Vol 38 (A) ◽  
pp. 142-157 ◽  
Author(s):  
John Sansom ◽  
Peter Thomson

The paper proposes a hidden semi-Markov model for breakpoint rainfall data that consist of both the times at which rain-rate changes and the steady rates between such changes. The model builds on and extends the seminal work of Ferguson (1980) on variable duration models for speech. For the rainfall data the observations are modelled as mixtures of log-normal distributions within unobserved states where the states evolve in time according to a semi-Markov process. For the latter, parametric forms need to be specified for the state transition probabilities and dwell-time distributions.Recursions for constructing the likelihood are developed and the EM algorithm used to fit the parameters of the model. The choice of dwell-time distribution is discussed with a mixture of distributions over disjoint domains providing a flexible alternative. The methods are also extended to deal with censored data. An application of the model to a large-scale bivariate dataset of breakpoint rainfall measurements at Wellington, New Zealand, is discussed.


2010 ◽  
Author(s):  
Yunfei Zhang ◽  
Yang Wang ◽  
Yajun Wang ◽  
Jianguo He ◽  
Fang Ji ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document