3D SLAM Method Based on Improved Regionalized Gaussian Process Map Construction

2021 ◽  
pp. 3545-3557
Author(s):  
Bo Li ◽  
Jianyuan Ruan ◽  
Yu Zhang ◽  
Wenjie Zhao
2020 ◽  
Vol 44 (6) ◽  
pp. 947-967 ◽  
Author(s):  
Bo Li ◽  
Yingqiang Wang ◽  
Yu Zhang ◽  
Wenjie Zhao ◽  
Jianyuan Ruan ◽  
...  
Keyword(s):  

Author(s):  
Xiangyu Wang ◽  
Xuyu Wang ◽  
Shiwen Mao ◽  
Jian Zhang ◽  
Senthilkumar C. G. Periaswamy ◽  
...  

2021 ◽  
Author(s):  
Yi-Qun Xu ◽  
Bangning Zhang ◽  
Xiaokai Zhang ◽  
Jingming Hu ◽  
Daoxing Guo

2020 ◽  
Vol 44 (6) ◽  
pp. 969-969
Author(s):  
Bo Li ◽  
Yingqiang Wang ◽  
Yu Zhang ◽  
Wenjie Zhao ◽  
Jianyuan Ruan ◽  
...  
Keyword(s):  

2007 ◽  
Vol 44 (02) ◽  
pp. 393-408 ◽  
Author(s):  
Allan Sly

Multifractional Brownian motion is a Gaussian process which has changing scaling properties generated by varying the local Hölder exponent. We show that multifractional Brownian motion is very sensitive to changes in the selected Hölder exponent and has extreme changes in magnitude. We suggest an alternative stochastic process, called integrated fractional white noise, which retains the important local properties but avoids the undesirable oscillations in magnitude. We also show how the Hölder exponent can be estimated locally from discrete data in this model.


1987 ◽  
Vol 26 (03) ◽  
pp. 117-123
Author(s):  
P. Tautu ◽  
G. Wagner

SummaryA continuous parameter, stationary Gaussian process is introduced as a first approach to the probabilistic representation of the phenotype inheritance process. With some specific assumptions about the components of the covariance function, it may describe the temporal behaviour of the “cancer-proneness phenotype” (CPF) as a quantitative continuous trait. Upcrossing a fixed level (“threshold”) u and reaching level zero are the extremes of the Gaussian process considered; it is assumed that they might be interpreted as the transformation of CPF into a “neoplastic disease phenotype” or as the non-proneness to cancer, respectively.


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