Graduate Engineering - Linear Algebra (Graham Schmidt + more)

In summary: Just remember that for the third vector you need to subtract off its projection onto the first two. As for applications in engineering, Gram-Schmidt is often used in signal processing, image compression, and other fields where orthogonal bases are useful. It's a fundamental tool in linear algebra.In summary, the conversation discusses how to use the Graham Schmidt procedure to solve a problem involving linearly independent vectors. The process involves creating an orthogonal set of vectors that has the same span as the original set. This procedure has applications in engineering, particularly in signal processing and image compression.
  • #1
Koolaidbrah
3
0

Homework Statement


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No idea how to solve this using graham schmidt. I know how to do graham schmidt and how to solve this problem if I didn't have to use graham schmidt, but I have no idea where to start in order to get my vectors to add to V


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Found c to be 87 by using vector addition/subtraction and making it linearly dependent on other two.
However, not sure how to find two vectors that are in span and perpendicular that add up to V just like in #1



bjieko.jpg

For b., as long as A is invertable, wouldn't it be all of the b vectors?


Homework Equations


Graham Schmidt...



The Attempt at a Solution


Posted above
 
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  • #2
Well, if the question was not asking you to use the procedure, you could easily solve the augmented system and exhibit a solution.

The point of the gram process though, is to take a set of linearly independent vectors say S, in your space and to form a orthogonal set of vectors T by using the process. The span of the new set of vectors will be equivalent to the span of your original set.

That is, span{T} = span{S}.

You could go even further and form an orthonormal set out of the vectors of T, but it's not required here. Finding the set T should be sufficient.
 
  • #3
Zondrina said:
Well, if the question was not asking you to use the procedure, you could easily solve the augmented system and exhibit a solution.

The point of the gram process though, is to take a set of linearly independent vectors say S, in your space and to form a orthogonal set of vectors T by using the process. The span of the new set of vectors will be equivalent to the span of your original set.

That is, span{T} = span{S}.

You could go even further and form an orthonormal set out of the vectors of T, but it's not required here. Finding the set T should be sufficient.

Should I use my first two vectors in my set to find the first orthogonal vectors and the third as {1 2 3} to find the vector V2 perpindicular to my span? From there {1 2 3} minus the V2 vector to get my V1

I'm just confused as to how I use V1 is in span, V2 is perp to span and V1+V2 = {1 2 3}
 
  • #4
Out of curiosity (I'm learning gram schmidt for the first time in my LA class), what application does this have to engineering? (Thinking of going into engineering)
 
  • #5
Koolaidbrah said:
Should I use my first two vectors in my set to find the first orthogonal vectors and the third as {1 2 3} to find the vector V2 perpindicular to my span? From there {1 2 3} minus the V2 vector to get my V1

I'm just confused as to how I use V1 is in span, V2 is perp to span and V1+V2 = {1 2 3}
Yeah, that'll work if you're planning to do what I think you're saying.
 

1. What is the purpose of learning linear algebra in graduate engineering?

Linear algebra is a fundamental mathematical tool that is widely used in many areas of engineering. It provides a powerful framework for solving complex problems involving systems of linear equations, optimization, and data analysis. In graduate engineering, linear algebra is particularly important for understanding advanced topics such as machine learning, signal processing, and control systems.

2. What is the difference between Graham Schmidt and other methods of solving linear algebra problems?

The Graham Schmidt process is a specific method for finding an orthonormal basis for a vector space. It is particularly useful for solving problems involving orthogonal projections, least squares approximations, and orthogonal transformations. Other methods, such as LU decomposition and QR decomposition, have different applications and computational advantages.

3. How is linear algebra used in real-world engineering applications?

Linear algebra is used extensively in various fields of engineering, such as mechanical engineering, electrical engineering, and computer science. It is used in designing and analyzing structures, systems, and algorithms. For example, in mechanical engineering, linear algebra is used to model and analyze the stress and strain of materials, while in electrical engineering, it is used in circuit analysis and design.

4. What is the best way to approach learning linear algebra in graduate engineering?

The best way to learn linear algebra is to practice solving problems and gaining an intuitive understanding of the underlying concepts. It is also helpful to have a strong foundation in algebra and calculus. Additionally, utilizing resources such as textbooks, online tutorials, and practice problems can aid in the learning process.

5. Are there any specific prerequisites for studying linear algebra in graduate engineering?

Most graduate engineering programs require students to have a strong background in mathematics, including knowledge of algebra, calculus, and basic matrix operations. Some programs may also require prior coursework in linear algebra or related subjects. It is important to check the specific requirements of your program before enrolling in a graduate engineering course on linear algebra.

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