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Least Squares Approximations

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Presentation on theme: "Least Squares Approximations"β€” Presentation transcript:

1 Least Squares Approximations
Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB

2 Least Squares Approximations
Suppose you have an inconsistent linear system (i.e. there are no solutions). How do you find a vector that comes close to solving the system? We will use a method called β€œLeast-Squares” Approximation. We have the following system: 𝐴 π‘₯ = 𝑏 Unfortunately there are no exact solutions. We will look for a solution of the related system: 𝐴 π‘₯ = 𝑏 In this equation, is the orthogonal projection of onto the column space of A. In other words, is the vector that A maps to that is β€œclosest” to . 𝑏 𝑏 𝑏 𝑏 Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB

3 Least Squares Approximations
𝐴 π‘₯ = 𝑏 We start with this system, which is inconsistent. 𝐴 π‘₯ = 𝑏 Instead, we will look for a solution of this related system. A least-squares solution will satisfy the equation 𝐴 𝑇 𝐴 π‘₯ = 𝐴 𝑇 𝑏 An example is on the next slide. Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB

4 Least Squares Approximations
Here is an example: We have the following system: 1 2 βˆ’ π‘₯ = 3 βˆ’1 5 Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB

5 Least Squares Approximations
Here is an example: We have the following system: 1 2 βˆ’ π‘₯ = 3 βˆ’1 5 A least-squares solution will satisfy the equation 𝐴 𝑇 𝐴 π‘₯ = 𝐴 𝑇 𝑏 Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB

6 Least Squares Approximations
Here is an example: We have the following system: 1 2 βˆ’ π‘₯ = 3 βˆ’1 5 A least-squares solution will satisfy the equation 𝐴 𝑇 𝐴 π‘₯ = 𝐴 𝑇 𝑏 𝐴 𝑇 𝑏 = 1 βˆ’ βˆ™ 3 βˆ’1 5 = 9 12 Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB

7 Least Squares Approximations
Here is an example: We have the following system: 1 2 βˆ’ π‘₯ = 3 βˆ’1 5 A least-squares solution will satisfy the equation 𝐴 𝑇 𝐴 π‘₯ = 𝐴 𝑇 𝑏 𝐴 𝑇 𝑏 = 1 βˆ’ βˆ™ 3 βˆ’1 5 = 9 12 This is our least-squares solution π‘₯ = β†’ π‘₯ = Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB

8 Least Squares Approximations
Here is an example: We have the following system: 1 2 βˆ’ π‘₯ = 3 βˆ’1 5 A least-squares solution will satisfy the equation 𝐴 𝑇 𝐴 π‘₯ = 𝐴 𝑇 𝑏 This matrix came out diagonal because the columns of the original matrix were orthogonal This is our least-squares solution π‘₯ = β†’ π‘₯ = Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB

9 Least Squares Approximations
Here is an example: We have the following system: 1 2 βˆ’ π‘₯ = 3 βˆ’1 5 π‘₯ = This is our least-squares solution We can find the β€œerror” by comparing this with the original system. Least-Squares Error = 𝑏 βˆ’π΄ π‘₯ 𝑏 βˆ’π΄ π‘₯ =π‘’π‘Ÿπ‘Ÿπ‘œπ‘Ÿ Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB

10 Least Squares Approximations
Here is an example: We have the following system: 1 2 βˆ’ π‘₯ = 3 βˆ’1 5 π‘₯ = This is our least-squares solution We can find the β€œerror” by comparing this with the original system. Least-Squares Error = 𝑏 βˆ’π΄ π‘₯ 𝑏 βˆ’π΄ π‘₯ =π‘’π‘Ÿπ‘Ÿπ‘œπ‘Ÿ 𝑏 βˆ’π΄ π‘₯ = 3 βˆ’1 5 βˆ’ 4 βˆ’1 4 = βˆ’1 0 1 𝑏 βˆ’π΄ π‘₯ = 2 The error in any approximation to the original system will be at least this large. Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB


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