Chapter 4: Problem 11
Let \(\mathbf{u}=\left[\begin{array}{r}3 \\ -1 \\ 0\end{array}\right], \mathbf{v}=\left[\begin{array}{l}4 \\ 0 \\ 1\end{array}\right],\) and \(\mathbf{w}=\left[\begin{array}{c}-1 \\ 1 \\ 5\end{array}\right] .\) In each case, find \(\mathbf{x}\) such that: a. \(3(2 \mathbf{u}+\mathbf{x})+\mathbf{w}=2 \mathbf{x}-\mathbf{v}\) b. \(2(3 \mathbf{v}-\mathbf{x})=5 \mathbf{w}+\mathbf{u}-3 \mathbf{x}\)
Short Answer
Step by step solution
Simplify the Given Equation for Part (a)
Substitute Known Values
Balance the Equation
Solve for \(\mathbf{x}\) in Part (a)
Simplify the Given Equation for Part (b)
Substitute Known Values
Balance the Equation
Solve for \(\mathbf{x}\) in Part (b)
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Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Vector Operations
- Vector Addition: To add two vectors, simply add their corresponding components. For vectors \(\mathbf{a} = \begin{bmatrix} a_1 \ a_2 \ a_3 \end{bmatrix}\) and \(\mathbf{b} = \begin{bmatrix} b_1 \ b_2 \ b_3 \end{bmatrix}\), their sum is \(\mathbf{a} + \mathbf{b} = \begin{bmatrix} a_1 + b_1 \ a_2 + b_2 \ a_3 + b_3 \end{bmatrix}\).
- Scalar Multiplication: Multiplying a vector by a scalar means scaling each component by the scalar. For \(c \cdot \mathbf{a} = \begin{bmatrix} c \cdot a_1 \ c \cdot a_2 \ c \cdot a_3 \end{bmatrix}\).
- Subtraction: Subtracting vector \(\mathbf{b}\) from \(\mathbf{a}\) is the same as adding \(\mathbf{a}\) to the negative of \(\mathbf{b}\), or \(\mathbf{a} - \mathbf{b} = \begin{bmatrix} a_1 - b_1 \ a_2 - b_2 \ a_3 - b_3 \end{bmatrix}\).
Equation Solving
- Isolate the Variable: Aim to have the vector or variable you are solving for on one side of the equation. Processes like combining like terms and using properties of equality are useful strategies. For instance, the equation \( 3(2\mathbf{u}+\mathbf{x})+\mathbf{w}=2\mathbf{x}-\mathbf{v} \) can be simplified by multiplying through and matching like terms.
- Substitution: Replace known vectors with their corresponding elements for clarity. This helps transform the problem into more manageable linear equations you can solve with basic algebra. In our example, replace \(\mathbf{u}, \mathbf{v},\) and \(\mathbf{w}\) with their respective values.
- Solve Component-wise: When reduced to basic linear forms, solve the equations for each component separately. Each resulting equation corresponds to one component of the unknown vector, leading to efficient problem-solving.
Matrix Manipulation
- Matrix Addition: Similar to vectors, add matrices by adding their corresponding elements. This only works if the matrices have the same dimensions.
- Matrix Multiplication: Multiply a matrix by another matrix, or vector, by utilizing the dot product of rows and columns. For matrices \(A\) of dimension \(m \times n\) and \(B\) of dimension \(n \times p\), their product \(AB\) is an \(m \times p\) matrix.
- Inversion and Transposition: These operations are crucial for solving system equations: finding inverses allows for direct solutions of matrix equations like \(AX = B\), while transposing swaps the matrix's rows and columns.