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Row Reduction

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A matrix is in (Row) Echelon Form (REF) if: All nonzero rows are above any rows of all zeros. ... corresponds to a leading entry in an echelon form of A. ... – PowerPoint PPT presentation

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Title: Row Reduction


1
Row Reduction Echelon FormsBasic Definitions
01/24/2008
  • A matrix is in (Row) Echelon Form (REF) if
  • All nonzero rows are above any rows of all zeros.
  • Each leading (nonzero) entry of a row is in a
    column to the right of the leading entry of the
    row above it.
  • All entries in a column below a leading entry are
    zero.

1
2
Row Reduction Echelon FormsBasic Definitions
  • A matrix is in (Row) Echelon Form (REF) if
  • All nonzero rows are above any rows of all zeros.
  • Each leading (nonzero) entry of a row is in a
    column to the right of the leading entry of the
    row above it.
  • All entries in a column below a leading entry are
    zero.
  • A matrix is in Reduced (Row) Echelon Form (RREF)
  • if it is in echelon form and in addition
  • The leading entry in each nonzero row is 1.
  • Each leading 1 is the only nonzero entry in its
    column.

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Row Reduction Echelon FormsBasic Definitions
  • (Row) Echelon Form
  • Reduced (Row) Echelon Form

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4
Row Reduction Echelon FormsBasic Definitions
  • A matrix is in (Row) Echelon Form (REF) if
  • All nonzero rows are above any rows of all zeros.
  • Each leading (nonzero) entry of a row is in a
    column to the right of the leading entry of the
    row above it.
  • All entries in a column below a leading entry are
    zero.
  • A matrix is in Reduced (Row) Echelon Form (RREF)
  • if it is in echelon form and in addition
  • The leading entry in each nonzero row is 1.
  • Each leading 1 is the only nonzero entry in its
    column.
  • Uniqueness Each matrix is row equivalent to one
  • and only one reduced row echelon matrix.

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5
Row Reduction Echelon FormsWhich are in REF?
In RREF?
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6
Row Reduction Echelon FormsBasic Definitions
  • A matrix is in (Row) Echelon Form (REF) if
  • All nonzero rows are above any rows of all zeros.
  • Each leading (nonzero) entry of a row is in a
    column to the right of the leading entry of the
    row above it.
  • All entries in a column below a leading entry are
    zero.
  • A Pivot Position in a matrix A is a location in A
    that
  • corresponds to a leading entry in an echelon form
    of A.
  • A Pivot Column is a column containing a pivot
    position.

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Row Reduction Echelon FormsBasic Definitions
  • A Pivot Position in a matrix A is a location in A
    that
  • corresponds to a leading entry in an echelon form
    of A.
  • A Pivot Column is a column containing a pivot
    position.
  • The variables in a linear system are classified
    as
  • Basic Variables if they correspond to pivot
    columns
  • Free Variables if they correspond to non-pivot
    columns of the coefficient matrix

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Row Reduction Echelon FormsBasic Definitions
  • A Pivot Position in a matrix A is a location in
    A that corresponds to a leading entry in an
    echelon form of A.A Pivot Column is a column
    containing a pivot position.
  • The variables in a linear system are classified
    as
  • Basic Variables if they correspond to pivot
    columns
  • Free Variables if they correspond to non-pivot
    columns of the coefficient matrix
  • The General Solution of a linear system is
    obtained by
  • Finding the RREF of its augmented matrix
  • Solving each equation in the associated system
    for its leading (basic) variable in terms of the
    free variables
  • Stating which variables are the free variables.

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Row Reduction Echelon FormsExample (text, page
21)
  • The variables in a linear system are classified
    as
  • Basic Variables if they correspond to pivot
    columns
  • Free Variables if they correspond to non-pivot
    columns of the coefficient matrix
  • Find the general solution of the linear system
    whose augmented matrix has been reduced to
  • Basic Variables
  • Free Variables

9
10
Row Reduction Echelon FormsExample
  • The General Solution of a linear system is
    obtained by
  • Finding the RREF of its augmented matrix
  • Solving each equation in the associated system
    for its leading (basic) variable in terms of the
    free variables
  • Stating which variables are the free variables.
  • Basic Variables x1, x3, x5
  • Free Variables x2, x4

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Row Reduction Echelon FormsExample
  • The General Solution of a linear system is
    obtained by
  • Finding the RREF of its augmented matrix
  • Note that the symbols separating the matrices are
    tildes (meaning is equivalent to) and NOT
    equal signs (meaning is the same matrix as)

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Row Reduction Echelon FormsExample
  • The General Solution of a linear system is
    obtained by
  • Solving each equation in the associated system
    for its leading (basic) variable in terms of the
    free variables
  • Basic Variables x1, x3, x5
  • Free Variables x2, x4
  • Associated System

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Row Reduction Echelon FormsExample
  • The General Solution of a linear system is
    obtained by
  • Solving each equation in the associated system
    for its leading (basic) variable in terms of the
    free variables
  • Associated System General or Parametric
    Solution

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Existence and Uniqueness Questions
  • How can we tell from the augmented matrix of a
    system
  • Existence If there are any solutions?
  • Uniqueness If there is a solution, is it unique
    or are there infinitely many solutions?
  • A linear system is consistent if and only if
  • The rightmost column of the augmented matrix is
    not a pivot column.
  • The echelon form of the augmented matrix has no
    row of the form
  • 0 0 . . . 0 b with b nonzero.
  • If a linear system is consistent, the solution
    set contains
  • A unique solution when there are no free
    variables
  • Infinitely many solutions when there is at least
    one free variable

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