[ Here 21 is the dot product of (3, 1, 2, 5) with (2, 3, 1, 2), and 31 is the dot product of
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1 . Matrices A matrix is any rectangular array of numbers. For example is 3 4 matrix, i.e. a rectangular array of numbers with three rows four columns. We usually use capital letters for matrices, e.g. A, B, C, with lowercase letters reserved for scalars. A vector is actually a special type of matrix, namely a matrix with only one column. In particular, a vector from R n is the same thing as an n matrix. In general, the product of an m n matrix with a vector from R n is a vector in R m. Multiplying a Matrix a Vector To multiply a matrix a vector, we take the dot product of each row of the matrix with the vector. For example, [ [ Here is the dot product of (3,,, 5) with (, 3,, ), 3 is the dot product of (, 4, 3, 7) with (, 3,, ). Note that a matrix A can only be multiplied by a vector v if each row of A has the same size as v. For example, we can only multiply a 5 8 matrix with a vector from R 8, the resulting product will be a vector in R 5. 3 Multiplying Matrices There is an operation called matrix multiplication that generalizes the product of a matrix a vector. Given two matrices A B, the product AB is the matrix obtained by taking the dot product of each row of A with each column of B. For example, if A B are matrices, then there are four dot products to compute: [ [ [ [ [ [ [ [ [ [ [ [ 4 7 This product only makes sense if the rows of A the columns of B have the same size. The result always has one row for each row of A one column for each column of B. Here A is a 3 4 matrix B is 4 matrix, so AB will be a 3 matrix. EXAMPLE Compute AB if A B 6 3.
2 MATRICES SOLUTION We must take the dot product of each row of A with each column of B Unlike multiplication of scalars, matrix multiplication is not commutative. That is, AB BA are not necessarily the same. For example, [ [ [ [ [ [ However, matrix multiplication is associative. That is, for any matrices A, B, C. A(BC) (AB)C Matrix subtraction is defined in a similar way. Addition Scalar Multiplication There are two more basic operations involving matrices: addition scalar multiplication. Matrix addition works just like vector addition, with corresponding entries of the two matrices added together: [ [ [ Only two matrices of the same size can be added. Matrix multiplication distributes over addition from both the left the right, i.e. A(B + C) AB + AC (A + B)C AC + BC Scalar multiplication for matrices is also quite similar to scalar multiplication for vectors: [ [ This has a variety of obvious properties, e.g. k(a + B) ka + kb k(ab) (ka)b A(kB) for any scalar k matrices A B.
3 MATRICES 3 Square Matrices A matrix is called square if it has the same number of rows columns. For example, matrices are square, as are 3 3 matrices, more generally n n matrices. We can take the determinant of any square matrix A, which we write as det(a). For example, if [ 5 A 3 4 then det(a) 4. The product of two square matrices of the same size is another square matrix of that size. For example, The determinant of a matrix product is equal to the product of the determinants: det(ab) det(a) det(b). A square matrix is called diagonal if all of its nonzero entries lie along the diagonal that goes from the upper left to the lower right. For example, [ are diagonal matrices. The determinant of a diagonal matrix is equal to the product if the entries along the diagonal: Note that we use square brackets for matrices vertical lines for determinants. a b ab, a b c abc. Inverse Matrices A diagonal matrix with ones along the diagonal is called an identity matrix: We usually use the letter I to denote an identity matrix. [ Multiplying by an identity matrix has no effect: [ [ [ [ [ [ Two square matrices are called inverses if their product is the identity matrix. For example [ [
4 MATRICES 4 are inverses, since [ 3 [ [ A matrix can have only one inverse. If A is a square matrix, its inverse is denoted A. There is a simple formula for the inverse of a matrix: Inverse of a Matrix There is no simple analog of this formula for 3 3 or larger matrices. [ a b c d [ ad bc d c b a [ a b Note that ad bc is the determinant of. c d EXAMPLE Find the inverse of the matrix 4 6. SOLUTION This simplifies to The determinant of this matrix is, so the inverse is / A square matrix is called invertible if it has an inverse. From the formula above, we see that a matrix is invertible as long as its determinant is not zero. This rule works for matrices of any size: A square matrix A is invertible if only if det(a). Representing Linear Systems We can use matrices to write any linear system as a single vector equation of the form Ax b where A is the coefficient matrix, x is the vector of unknowns, b is the vector of constant terms. For example, the linear system x + 5y 3x + 4y 3 can be written in vector form as [ [ x y [ 3
5 MATRICES 5 We can use inverse matrices to solve n n linear systems. Given a linear system of the form Ax b where A is an invertible square matrix, we can multiply both sides of the equation by A to get x A b EXAMPLE 3 Use an inverse matrix to solve the system 3x + y 7 x + 4y 5 SOLUTION We can write this system as 3 4 x y 7 5 But so x y Thus x.8 y.8. EXERCISES 4 Multiply [ Find the values of x y for which [ x 4 [ y [ 8.
6 MATRICES Multiply. 6. [ [ [ [ [ [ 7 [ Compute the inverse of the given matrix. [ [ [ 3 3. [ Does the matrix have an inverse? Explain. 3 [ 5. Compute 5A + 6A if A. 6. (a) Write the linear system x 3y 5 3x + 4y as an equation of the form Ax b. (b) Use an inverse matrix to solve your equation from part (a). 7. Given that the matrices are inverses, solve the following linear system: x 5x + 3x 3 x 4 3 x + x x 3 + x 4 x 3x + x 3 + x 4 3x 8x + 6x 3 + x 4
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