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Linear Combinations

Explore the concept of linear combinations by learning how scalars multiply vectors and matrices to form new objects. Understand how to generate infinite combinations from vectors and how this applies to data science tasks such as image processing and matrix operations. Gain practical skills with Python code examples to manipulate and visualize linear combinations.

What’s a linear combination?

If x1\bold{x_1} and x2\bold{x_2} are any two objects and α1\alpha_1 and α2\alpha_2 are any two scalars, then α1x1+α2x2\alpha_1\bold{x_1}+\alpha_2\bold{x_2} is a linear combination of x1\bold{x_1} and x2\bold{x_2}. We can have several linear combinations of x1\bold{x_1} and x2\bold{x_2} by varying α1\alpha_1 and α2\alpha_2.

Example

Find any three linear combinations of x1=[359]\bold{x_1} = \begin{bmatrix} 3\\ 5\\ 9 \end{bmatrix} and x2=[121]\bold{x_2} = \begin{bmatrix} 1 \\ 2 \\ 1 \end{bmatrix}.

Note: Objects like column-vectors, such as [359]\begin{bmatrix} 3\\ 5\\ 9 \end{bmatrix} , are commonly used to represent points in space. We’ll discuss the vectors and vector spaces in detail in upcoming lessons, but for now, it’s okay to simply view these objects as arrays.

Solution:

y1=2[359]+3[121]=[91621]whereα1=2,α2=3\bold{y_1}=2\begin{bmatrix} 3 \\ 5 \\ 9 \end{bmatrix}+3 \begin{bmatrix} 1\\ 2\\ 1 \end{bmatrix}=\begin{bmatrix} 9\\ 16\\ 21 \end{bmatrix} \hspace{5mm} \text{where} \quad \alpha _1 = 2, \alpha _2 = 3 ...