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==Problem 1 Critique== | ==Problem 1 Critique== | ||

+ | a) and b) are as same as mine which I think are probably correct | ||

+ | |||

+ | For part c), the solution is almost the same just need to follow what the instruction said in terms of <math>\lambda_n</math>, <math>\lambda_n^b</math>, and <math>\lambda_n^d</math> | ||

+ | |||

+ | For part d). I am not sure what the correct curve should be. | ||

+ | |||

+ | ==Problem 2 Critique== | ||

+ | For this problem, I consider that part b is not the correct way to prove positive semi-definite. To prove a matrix A is p.s.d, need an arbitrary vector x and prove that<math>x^tAx \geq 0</math>. Prove <math>\Sigma^2 \geq 0</math> is not enough. |

## Latest revision as of 20:27, 9 July 2019

## Problem 1 Critique

a) and b) are as same as mine which I think are probably correct

For part c), the solution is almost the same just need to follow what the instruction said in terms of $ \lambda_n $, $ \lambda_n^b $, and $ \lambda_n^d $

For part d). I am not sure what the correct curve should be.

## Problem 2 Critique

For this problem, I consider that part b is not the correct way to prove positive semi-definite. To prove a matrix A is p.s.d, need an arbitrary vector x and prove that$ x^tAx \geq 0 $. Prove $ \Sigma^2 \geq 0 $ is not enough.