Two-dimensional Markov Chain Simulation of Soil Type Spatial Distribution

2004 ◽  
Vol 68 (5) ◽  
pp. 1479-1490 ◽  
Author(s):  
Weidong Li ◽  
Chuanrong Zhang ◽  
James E. Burt ◽  
A.-Xing Zhu ◽  
Jan Feyen
Keyword(s):  
Spatial Distribution ◽  
Markov Chain ◽  
Soil Type ◽  
Two Dimensional

Application of coherent four-wave mixing for two-dimensional mapping of the spatial distribution of excited atoms in a laser-produced plasma

1997 ◽  
Vol 140 (4-6) ◽  
pp. 259-265 ◽  
Author(s):  
D.A. Akimov ◽  
A.B. Fedotov ◽  
N.I. Koroteev ◽  
A.N. Naumov ◽  
D.A. Sidorov-Biryukov ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Four Wave Mixing ◽  
Wave Mixing ◽  
Two Dimensional ◽  
Excited Atoms ◽  
Laser Produced Plasma ◽  
Dimensional Mapping

Full Two-Dimensional Markov Chain Analysis of Thermal Soft Errors in Subthreshold Nanoscale CMOS Devices

2011 ◽  
Vol 11 (1) ◽  
pp. 50-59 ◽  
Author(s):  
Pooya Jannaty ◽  
Florian Cosmin Sabou ◽  
R. Iris Bahar ◽  
Joseph Mundy ◽  
William R. Patterson ◽  
...  
Keyword(s):  
Markov Chain ◽  
Soft Errors ◽  
Two Dimensional ◽  
Markov Chain Analysis ◽  
Nanoscale Cmos ◽  
Chain Analysis

On ergodicity and recurrence properties of a Markov chain by an application to an open jackson network

1992 ◽  
Vol 24 (02) ◽  
pp. 343-376 ◽  
Author(s):  
Arie Hordijk ◽  
Flora Spieksma
Keyword(s):  
Markov Chain ◽  
Product Form ◽  
Geometric Ergodicity ◽  
Two Dimensional ◽  
Marginal Distributions ◽  
Jackson Network ◽  
Strong Ergodicity ◽  
Key Theorem ◽  
Stieltjes Transforms

This paper gives an overview of recurrence and ergodicity properties of a Markov chain. Two new notions for ergodicity and recurrence are introduced. They are calledμ-geometric ergodicity andμ-geometric recurrence respectively. The first condition generalises geometric as well as strong ergodicity. Our key theorem shows thatμ-geometric ergodicity is equivalent to weakμ-geometric recurrence. The latter condition is verified for the time-discretised two-centre open Jackson network. Hence, the corresponding two-dimensional Markov chain isμ-geometrically and geometrically ergodic, but not strongly ergodic. A consequence ofμ-geometric ergodicity withμof product-form is the convergence of the Laplace-Stieltjes transforms of the marginal distributions. Consequently all moments converge.

A Method for Studying the Distribution of Absorbing Roots of Fruit Trees

1971 ◽  
Vol 7 (4) ◽  
pp. 351-362 ◽  
Author(s):  
F. Weller
Keyword(s):  
Spatial Distribution ◽  
Soil Type ◽  
Soil Management ◽  
Root Systems ◽  
Fruit Trees ◽  
Temporal Variations ◽  
Root Tips ◽  
Apple Trees ◽  
Western Germany ◽  
Absorbing Roots

SUMMARYA method is described for studying the distribution of absorbing roots of fruit trees using the number of light root tips per unit of soil space as a criterion for characterizing the spatial distribution of the absorbing parts of the root systems. As examples of the use of this method, some results are shown from investigations with apple trees in South-Western Germany. They demonstrate the influence of soil-type and soil management on the distribution of absorbing roots. Striking temporal variations in the number of root tips were observed in the same tree.

Analysis of a two-dimensional markov chain

1996 ◽  
Vol 25 (1) ◽  
pp. 75-79 ◽  
Author(s):  
Sharad S. Prabhu ◽  
George C. Runger
Keyword(s):  
Markov Chain ◽  
Two Dimensional
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