Tokyo/Formulation/5.stochastic differential equation model with poisson random variables
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<br>[[Image:expression5-1.jpg|500px|left|thumb|Ex 5-1]][[Image:parameter4-1.jpg|150px|none|thumb|Table 5]] | <br>[[Image:expression5-1.jpg|500px|left|thumb|Ex 5-1]][[Image:parameter4-1.jpg|150px|none|thumb|Table 5]] | ||
- | <br>The values of parameters in the right table were used and the results of simulation were shown in Fig 5.1-3.where α2 = 1(μM) in Fig 5.1,α2 = 2.7(μM) in Fig 5.2,α2 = 4(μM) in Fig 5.3. and it has been estimated that 1(μM) = 1000 molecules (count). | + | <br>The values of parameters in the right table were used and the results of simulation were shown in Fig 5.1-3. |
+ | <br>where α2 = 1(μM) in Fig 5.1,α2 = 2.7(μM) in Fig 5.2,α2 = 4(μM) in Fig 5.3. and it has been estimated that 1(μM) = 1000 molecules (count). | ||
[[Image:3d-1-0.2.JPG|270px|left|thumb|Figure 5.1.A t=0.2(min)]] | [[Image:3d-1-0.2.JPG|270px|left|thumb|Figure 5.1.A t=0.2(min)]] |
Revision as of 09:11, 24 October 2007
we introduced the terms of Ex 4-1 into a stochastic process to simulate the sthochastic behavior.we used Poisson random variables as a sthochastic process. Threfore,a stochastic differential equations were given as
The values of parameters in the right table were used and the results of simulation were shown in Fig 5.1-3.
where α2 = 1(μM) in Fig 5.1,α2 = 2.7(μM) in Fig 5.2,α2 = 4(μM) in Fig 5.3. and it has been estimated that 1(μM) = 1000 molecules (count).
パラメータを3種類使ってシミュレーションした結果が以下である.
これとstep4のdetermineの相平面とを比べるとこうですよ.