Naperian - Definition. Was ist Naperian
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Was (wer) ist Naperian - definition

MATHEMATICAL FUNCTION
Napier's logarithm; Naperian logarithm; Naperian system of logarithms
  • A plot of the Napierian logarithm for inputs between 0 and 10<sup>8</sup>.
  • The 19 degree pages from Napier's 1614 table of logarithms of trigonometric functions ''[[Mirifici Logarithmorum Canonis Descriptio]]''

Naperian      
·adj Of, pertaining to, or discovered by, Napier, or Naper.
Napierian logarithm         
[ne?'p??r??n]
¦ noun another term for natural logarithm.
Origin
C19: named after the Scottish mathematician John Napier (1550-1617).
Napierian logarithm         
The term Napierian logarithm or Naperian logarithm, named after John Napier, is often used to mean the natural logarithm. Napier did not introduce this natural logarithmic function, although it is named after him.

Wikipedia

Napierian logarithm

The term Napierian logarithm or Naperian logarithm, named after John Napier, is often used to mean the natural logarithm. Napier did not introduce this natural logarithmic function, although it is named after him. However, if it is taken to mean the "logarithms" as originally produced by Napier, it is a function given by (in terms of the modern natural logarithm):

N a p L o g ( x ) = 10 7 ln ( x / 10 7 ) {\displaystyle \mathrm {NapLog} (x)=-10^{7}\ln(x/10^{7})}

The Napierian logarithm satisfies identities quite similar to the modern logarithm, such as

N a p L o g ( x y ) N a p L o g ( x ) + N a p L o g ( y ) 161180956 {\displaystyle \mathrm {NapLog} (xy)\approx \mathrm {NapLog} (x)+\mathrm {NapLog} (y)-161180956}

or

N a p L o g ( x y / 10 7 ) = N a p L o g ( x ) + N a p L o g ( y ) {\displaystyle \mathrm {NapLog} (xy/10^{7})=\mathrm {NapLog} (x)+\mathrm {NapLog} (y)}

In Napier's 1614 Mirifici Logarithmorum Canonis Descriptio, he provides tables of logarithms of sines for 0 to 90°, where the values given (columns 3 and 5) are

N a p L o g ( θ ) = 10 7 ln ( sin ( θ ) ) {\displaystyle \mathrm {NapLog} (\theta )=-10^{7}\ln(\sin(\theta ))}