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Eigenvalues and eigenvectors (eig) in MATLAB - Mini Project: Build & Apply

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Eigenvalues and eigenvectors (eig)
📖 Scenario: You are working as a data analyst and need to understand the properties of a matrix representing some data relationships. Eigenvalues and eigenvectors help you find important directions and strengths in the data.
🎯 Goal: Learn how to calculate eigenvalues and eigenvectors of a matrix using MATLAB's eig function.
📋 What You'll Learn
Create a 2x2 matrix with specific values
Define a variable to hold the matrix size
Use the eig function to find eigenvalues and eigenvectors
Display the eigenvalues and eigenvectors
💡 Why This Matters
🌍 Real World
Eigenvalues and eigenvectors are used in data analysis, physics, and engineering to understand system behaviors and transformations.
💼 Career
Knowing how to compute and interpret eigenvalues and eigenvectors is important for roles in data science, machine learning, and scientific computing.
Progress0 / 4 steps
1
Create the matrix
Create a 2x2 matrix called A with these exact values: 4, 2 in the first row and 1, 3 in the second row.
MATLAB
Hint

Use square brackets and semicolon to separate rows in MATLAB.

2
Define matrix size
Create a variable called n that stores the size of matrix A using the size function.
MATLAB
Hint

Use size(A,1) to get the number of rows.

3
Calculate eigenvalues and eigenvectors
Use the eig function to calculate eigenvalues and eigenvectors of matrix A. Store eigenvectors in V and eigenvalues in D.
MATLAB
Hint

Use [V,D] = eig(A) to get eigenvectors and eigenvalues.

4
Display the results
Display the eigenvalues stored in D and eigenvectors stored in V using disp.
MATLAB
Hint

Use disp('Eigenvalues:') and disp(D) to show eigenvalues, similarly for eigenvectors.

Practice

(1/5)
1. What does the MATLAB function eig return when applied to a square matrix?
easy
A. Eigenvalues and eigenvectors of the matrix
B. Only the eigenvalues of the matrix
C. Only the eigenvectors of the matrix
D. The inverse of the matrix

Solution

  1. Step 1: Understand the purpose of eig

    The eig function in MATLAB is designed to compute eigenvalues and eigenvectors of a square matrix.
  2. Step 2: Recall the output of eig

    When called with two output arguments, [V,D] = eig(A), it returns eigenvectors in V and eigenvalues in diagonal matrix D.
  3. Final Answer:

    Eigenvalues and eigenvectors of the matrix -> Option A
  4. Quick Check:

    eig returns eigenvalues and eigenvectors [OK]
Hint: Remember: eig returns both eigenvalues and eigenvectors [OK]
Common Mistakes:
  • Thinking eig returns only eigenvalues
  • Confusing eig with inverse function
  • Assuming eig returns a scalar
2. Which of the following is the correct syntax to get eigenvalues and eigenvectors of matrix A in MATLAB?
easy
A. [V,D] = eig(A);
B. eig = [V,D](A);
C. V, D = eig(A);
D. eig(A) -> [V,D];

Solution

  1. Step 1: Recall MATLAB function call syntax

    In MATLAB, functions return outputs using square brackets for multiple outputs, e.g., [out1, out2] = function(input);.
  2. Step 2: Match correct syntax for eig

    The correct way to get eigenvectors V and eigenvalues D is [V,D] = eig(A);.
  3. Final Answer:

    [V,D] = eig(A); -> Option A
  4. Quick Check:

    Use square brackets for multiple outputs [OK]
Hint: Use square brackets for multiple outputs in MATLAB [OK]
Common Mistakes:
  • Using commas instead of brackets for outputs
  • Assigning outputs incorrectly
  • Using arrow notation which is invalid in MATLAB
3. Given the matrix A = [2 0; 0 3];, what is the output of [V,D] = eig(A); D?
medium
A. [[5 0]; [0 0]]
B. [[3 0]; [0 2]]
C. [[2 0]; [0 3]]
D. [[0 2]; [3 0]]

Solution

  1. Step 1: Identify eigenvalues of matrix A

    Matrix A is diagonal with entries 2 and 3, so eigenvalues are 2 and 3.
  2. Step 2: Understand output of D from eig

    D is a diagonal matrix with eigenvalues on the diagonal, so D = [2 0; 0 3].
  3. Final Answer:

    [[2 0]; [0 3]] -> Option C
  4. Quick Check:

    Diagonal matrix D has eigenvalues 2 and 3 [OK]
Hint: Eigenvalues of diagonal matrix are diagonal entries [OK]
Common Mistakes:
  • Mixing order of eigenvalues
  • Confusing eigenvalues with eigenvectors
  • Expecting eigenvalues as a vector instead of diagonal matrix
4. What is wrong with this MATLAB code snippet to get eigenvalues of matrix A?
eigenvalues = eig(A, 'vector');
medium
A. The matrix A must be square and symmetric
B. The variable name eigenvalues is invalid
C. The function eig requires three output arguments
D. The eig function does not accept 'vector' as a second argument

Solution

  1. Step 1: Check eig function arguments

    The MATLAB eig function does not take a second argument like 'vector'. It only takes the matrix as input.
  2. Step 2: Identify correct usage to get eigenvalues as vector

    To get eigenvalues as a vector, simply call eig(A) without extra arguments.
  3. Final Answer:

    The eig function does not accept 'vector' as a second argument -> Option D
  4. Quick Check:

    Check function syntax carefully [OK]
Hint: Check MATLAB function syntax in docs before adding arguments [OK]
Common Mistakes:
  • Adding unsupported arguments to eig
  • Assuming eig returns vector by default without output assignment
  • Confusing eig with other functions
5. You have a matrix A = [4 1 0; 1 4 1; 0 1 4];. How can you find the eigenvector corresponding to the largest eigenvalue using MATLAB?
hard
A. largestVec = eig(A);
B. [V,D] = eig(A); [~, idx] = max(diag(D)); largestVec = V(:, idx);
C. [V,D] = eig(A); largestVec = D(:,1);
D. [V,D] = eig(A); largestVec = max(V);

Solution

  1. Step 1: Compute eigenvalues and eigenvectors

    Use [V,D] = eig(A); to get eigenvectors V and eigenvalues in diagonal matrix D.
  2. Step 2: Find index of largest eigenvalue

    Extract eigenvalues with diag(D), then find index of max eigenvalue with [~, idx] = max(diag(D));.
  3. Step 3: Select eigenvector corresponding to largest eigenvalue

    Use index to get eigenvector: largestVec = V(:, idx);.
  4. Final Answer:

    [V,D] = eig(A); [~, idx] = max(diag(D)); largestVec = V(:, idx); -> Option B
  5. Quick Check:

    Index max eigenvalue, select eigenvector column [OK]
Hint: Use max(diag(D)) to find largest eigenvalue index [OK]
Common Mistakes:
  • Using eigenvalues matrix D as vector directly
  • Selecting wrong column of eigenvectors
  • Confusing eigenvalues with eigenvectors
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