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Mathematics 1 /Matematik 1
Lesson 3 โ Functions and their solutions Lektion3 โ Funktioner och deras lรถsningar
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Solution, Lรถsning If you have an equation that you can not directly solve it may become solvable by substituting Example: ๐ฆ=๐ ๐ฅ 4 +๐ ๐ฅ 2 +๐ can be solved if you substitute ๐ง= ๐ฅ 2 , the equation becomes quadratic ๐ฆ=๐ ๐ง 2 +๐๐ง+๐ Example: ๐ฆ=lnโก( ๐ฅ 2 +๐), substitute ๐ง= ๐ฅ 2 +๐, the equation becomes ๐ฆ= ln ๐ง and has a solution for ๐ง=๐ Om du har en ekvation som du inte kan direkt lรถser kan den bli lรถsbart genom substitution. Exempel: ๐ฆ=๐ ๐ฅ 4 +๐ ๐ฅ 2 +๐ kan bli lรถst genom substitution av ๐ง= ๐ฅ 2 , ekvationen blir kvadratisk ๐ฆ=๐ ๐ง 2 +๐๐ง+๐ Exempel: ๐ฆ=lnโก( ๐ฅ 2 +๐), substituerar ๐ง= ๐ฅ 2 +๐, ekvationen ๐ฆ= ln ๐ง har en lรถsning fรถr ๐ง=๐
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Equations systems (gauss elemination)
Assume equations ๐ 1 = ๐ 1 ๐ง+ ๐ 1 ๐ฆ+ ๐ 1 ๐ฅ and ๐ 2 = ๐ 2 ๐ง+ ๐ 2 ๐ฆ+ ๐ 2 ๐ฅ You can multiply any equation with any constant other than zero without changing it. You like to multiply with a value that is such that a subsequent subtraction of the two equations removes z because its coefficient becomes zero. Example: multiply ๐ 2 ๐ค๐๐กโ ๐ 1 ๐ 2 and you get ๐ 2 ๐ 1 ๐ 2 = ๐ 1 ๐ง+ ๐ 2 ๐ 1 ๐ 2 ๐ฆ+ ๐ 2 ๐ 1 ๐ 2 ๐ฅ if the equations are now subtracted you get ( ๐ 2 โ ๐ 1 )= ๐ 2 ๐ 1 ๐ 2 โ ๐ 2 = (๐ 2 ๐ 1 ๐ 2 โ ๐ 1 )๐ฆ+ (๐ 2 ๐ 1 ๐ 2 โ ๐ 1 )๐ฅ You have (gauss) eliminated variable z Antar ekvationer ๐ 1 = ๐ 1 ๐ง+ ๐ 1 ๐ฆ+ ๐ 1 ๐ฅ och ๐ 2 = ๐ 2 ๐ง+ ๐ 2 ๐ฆ+ ๐ 2 ๐ฅdu kan multiplicerar alla ekvationer med en konstant annat รคn noll utan att รคndra ekvationen. Du multiplicerar med en vรคrde sรฅdant att en efterfรถljande subtraktion raderar z fรถr att dess koeffcient blir noll. Exempel: multiplicerar ๐ 2 ๐๐๐ ๐ 1 ๐ 2 och du fรฅ ๐ 2 ๐ 1 ๐ 2 = ๐ 1 ๐ง+ ๐ 2 ๐ 1 ๐ 2 ๐ฆ+ ๐ 2 ๐ 1 ๐ 2 ๐ฅ om d subtraherar nu ekavtionerna fรฅs ( ๐ 2 โ ๐ 1 )= ๐ 2 ๐ 1 ๐ 2 โ ๐ 2 = (๐ 2 ๐ 1 ๐ 2 โ ๐ 1 )๐ฆ+ (๐ 2 ๐ 1 ๐ 2 โ ๐ 1 )๐ฅ Du har nu (gauss) eliminerad variabel z
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Equation linearization (substition)
Assume you have a nonlinear model and collect data [y,t]. Extracting model parameters can be easier if the model is linearized. Example: ๐ฆ=๐ด ๐ ๐ต๐ก can be linearized to ๐๐ ๐ฆ ๐ด =๐ต๐ก= ln ๐ฆ โ ln ๐ด . A linear model is then ๐=๐๐ฅ+๐ with ๐= ln ๐ฆ , a=B, x=t, b=ln(A) This is fasted done in excel or similar Antar att du har en ickelinjรคr model och samlar data [y,t]. Extraktion av modelparameter kan vara lรคttare om modellen lineariseras. Exempel: ๐ฆ=๐ด ๐ ๐ต๐ก kan blir lineariserad till ๐๐ ๐ฆ ๐ด =๐ต๐ก= ln ๐ฆ โ ln ๐ด . En linjรคr model รคr sedan ๐=๐๐ฅ+๐ med ๐= ln ๐ฆ , a=B, x=t, b=ln(A) Detta gรถr snabbast i excel eller liknade.
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