- #1
csand
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Hi,
My understanding in this is limited, but I'm trying to create a set of Gaussian curve response functions that will be convoluted with some signal data. I've dug all around the internet/textbooks but I'm having trouble finding a way to create the curve with the data I have. All I know is the height is bound from 0 to 1 (or at least very very close to 0 for my purposes). I have the center value (x-axis) for every curve I need to generate, and I know the FWHM of every curve. So to generate a curve I will know:
-FWHM for the curve
-The center xaxis value (Denoted by Lambda_Center)
-The height
The only formula I have is unsourced and I'm not sure it's working properly for all cases:
e^( -1*(Lambda - Lambda_Center)^2 / (FWHM/2*sqrt(ln2))^2 )
I have Lambda_Center, and Lambda, if this were to be looped in a program, would increment/decrement by some value X for each point on the gaussian (ex: 0.1,0.2,0.3,0.4,L_C,0.4,0.3,0.2,0.1)
Does anyone recognize this formula/method for creating a gaussian? Can anybody see any big holes in the method? Everything I see online usually involves using sigma/mean.
Thanks,
-Chris
***EDIT***: fixed formula bracketing
My understanding in this is limited, but I'm trying to create a set of Gaussian curve response functions that will be convoluted with some signal data. I've dug all around the internet/textbooks but I'm having trouble finding a way to create the curve with the data I have. All I know is the height is bound from 0 to 1 (or at least very very close to 0 for my purposes). I have the center value (x-axis) for every curve I need to generate, and I know the FWHM of every curve. So to generate a curve I will know:
-FWHM for the curve
-The center xaxis value (Denoted by Lambda_Center)
-The height
The only formula I have is unsourced and I'm not sure it's working properly for all cases:
e^( -1*(Lambda - Lambda_Center)^2 / (FWHM/2*sqrt(ln2))^2 )
I have Lambda_Center, and Lambda, if this were to be looped in a program, would increment/decrement by some value X for each point on the gaussian (ex: 0.1,0.2,0.3,0.4,L_C,0.4,0.3,0.2,0.1)
Does anyone recognize this formula/method for creating a gaussian? Can anybody see any big holes in the method? Everything I see online usually involves using sigma/mean.
Thanks,
-Chris
***EDIT***: fixed formula bracketing
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