Second derivative of f(x) ≈ f(x−6)−2ƒ(x)+ƒ(x+8) Computationally, the function is represented as an array f(n), n = 1,2,3,... To numerically locate the minima of the second derivative, look at ƒ (n − 1) − 2ƒ(n) + f(n + 1) and find the values of n where it's most negative. Do this as an array function (avoid loops) Second derivative is minimized (most negative) when x = μ. Create a vector that represents f(n-1) - 2f(n) + f(n+1) and loop through values to find local minima. Those local minima will be the means for our Gaussians. We can also use the value of the second derivative to estimate the standard deviations.
Second derivative of f(x) ≈ f(x−6)−2ƒ(x)+ƒ(x+8) Computationally, the function is represented as an array f(n), n = 1,2,3,... To numerically locate the minima of the second derivative, look at ƒ (n − 1) − 2ƒ(n) + f(n + 1) and find the values of n where it's most negative. Do this as an array function (avoid loops) Second derivative is minimized (most negative) when x = μ. Create a vector that represents f(n-1) - 2f(n) + f(n+1) and loop through values to find local minima. Those local minima will be the means for our Gaussians. We can also use the value of the second derivative to estimate the standard deviations.
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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PLEASE DO IN RSTUDIO (R
Data Set:
| 890.776 | 890.519 | 890.263 | 890.006 | 889.749 | 889.493 | 889.236 | 888.979 | ||
| -4.25909 | -6.9024 | 9845 | 9608 | 9782 | 9708 | 9661 | 9609 | 9832 | 9753 |
| -4.25909 | -6.4544 | 9507 | 9340 | 9337 | 9325 | 9441 | 9300 | 9470 | 9143 |
| -4.25909 | -6.0064 | 9576 | 9201 | 9252 | 9238 | 9217 | 9298 | 9217 | 9224 |
| -4.25909 | -5.5584 | 9604 | 9301 | 9467 | 9279 | 9457 | 9438 | 9395 | 9310 |
Transcribed Image Text:ƒ(x−8)−2ƒ(x)+ƒ(x+6)
Second derivative of f(x)
Computationally, the function is represented as an array f(n), n = 1,2,3,...
To numerically locate the minima of the second derivative, look at f(n-1) − 2ƒ(n) + f(n + 1) and
find the values of n where it's most negative.
Do this as an array function (avoid loops)
Second derivative is minimized (most negative) when x = μ.
Create a vector that represents f(n-1) − 2f(n) + f(n + 1) and loop through values to find local
minima. Those local minima will be the means for our Gaussians. We can also use the value of the
second derivative to estimate the standard deviations.
Transcribed Image Text:Create an R script that:
•
Reads in the data as an array from a .txt file (make the txt file name be a variable)
Extract the first row as the set of wavelengths (store as a vector) and remove first row
from data.
Loop through the rows of the array. Find minima of second derivative as described
above
Store the minimum values and their indices (n) in two different arrays.
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