Участник:DataDrafter (Rcgvmunt&DataDrafter)

${\overline {B_{0}}}={\frac {\mu _{0}I}{\pi R}}({\frac {\sqrt {R^{2}-a^{2}}}{R}}+\arcsin {\frac {a}{R}}).$

$B={\frac {4\pi IN\mu _{1}\mu _{2}}{c(2d\mu _{1}\mu _{2}+{\frac {L}{2}}-d)(\mu _{1}+\mu _{2}))}}.$

$k_{1},k_{2}$
$sgn(k_{1})=1,sgn(k_{2})=-1,|k_{1}|<|k_{2}|$ к примеру k1=1, k2=-20. $k_{1}$
$k_{2}$


$H=\prod _{i=1}^{n}(1+H_{i})-1$
$H=\prod _{i=1}^{n}(1+H_{i})-1$

$H_{i}$

$H_{0}=(1.065)^{n}-1$

$Expected=Positive/(H+1)$

$Expected=(1,04121^{n})\cdot x\cdot k_{1}+(n\cdot 0.0001)\cdot (0.9389^{n})\cdot x\cdot k_{2}$

$Positive=(0.9999^{n})\cdot ((1.109^{n})\cdot x)\cdot k_{1}+(1-0.9999^{n})\cdot k_{2}\cdot x$

$Positive=(0.99999^{n})\cdot ((1.126^{n})\cdot x)\cdot k_{1}+(n\cdot 0.00001)\cdot k_{2}\cdot x$

$Expected=(1.0572^{n})\cdot x\cdot k_{1}+(1-0.99999^{n})\cdot (0.9389^{n})\cdot x\cdot k_{2};$

$Positive=(0.9^{n})\cdot ((1.23^{n})\cdot x)\cdot k_{1}+(1-0.9^{n})\cdot k_{2}\cdot x$

$Expected=Positive\cdot (0.9389^{n})$

$Expected=(0.9^{n})\cdot ((1.23^{n})\cdot x)\cdot k_{1}+(1-0.9^{n})\cdot k_{2}\cdot (0.9389^{n})$

${\displaystyle }$

$E_{b}=(1,04121^{n})\cdot x\cdot k_{1}+(n\cdot 0.0001)\cdot (0.9389^{n})\cdot x\cdot k_{2}$

$E_{n}=(1.0572^{n})\cdot x\cdot k_{1}+(1-0.99999^{n})\cdot (0.9389^{n})\cdot x\cdot k_{2};$

$E_{m}=(0.9^{n})\cdot ((1.23^{n})\cdot x)\cdot k_{1}+(1-0.9^{n})\cdot k_{2}\cdot (0.9389^{n})$

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