[M] The covariance matrix below was obtained from a Landsat image of the Columbia River in Washington, using data from three spectral bands. Let X1. X,, Xz denote the spectral components of each pixel in the image. Find a new variable of the form yı = c1x1 + C2x2 + C3.X3 that has maximum possible variance, subject to the constraint that c? + c; +c = 1. What percentage of the total variance in the data is explained by y1? 29.64 18.38 5.00 18.38 20.82 14.06 5.00 14.06 29.21

Advanced Engineering Mathematics
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Chapter2: Second-order Linear Odes
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[M] The covariance matrix below was obtained from a Landsat image of the Columbia River in Washington, using data
from three spectral bands. Let X1. X,, Xz denote the spectral components of each pixel in the image. Find a new
variable of the form yı = c1x1 + C2x2 + C3.X3 that has maximum possible variance, subject to the constraint
that c? + c; +c = 1. What percentage of the total variance in the data is explained by y1?
29.64
18.38
5.00
18.38
20.82
14.06
5.00
14.06
29.21
Transcribed Image Text:[M] The covariance matrix below was obtained from a Landsat image of the Columbia River in Washington, using data from three spectral bands. Let X1. X,, Xz denote the spectral components of each pixel in the image. Find a new variable of the form yı = c1x1 + C2x2 + C3.X3 that has maximum possible variance, subject to the constraint that c? + c; +c = 1. What percentage of the total variance in the data is explained by y1? 29.64 18.38 5.00 18.38 20.82 14.06 5.00 14.06 29.21
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