Bisection Method in One Dimension

zero-finding problem:

Given a scalar function F(x) : R → R, find a point x∗ ∈ R s.t.
F(x∗) = 0.

Although not all our problems are immediately viewed in this form we can always rewrite them in this way.

Convergence criteria(标准)

Possible conditions to satisfy:
|xn+1 −x∗| < |xn −x∗|
ie. we are getting closer to the root at each step

|F(xn+1)| < |F(xn)|
ie. the function F(x) is reduced at each step

  • These criteria are distinct
  • one does not imply the other
  • Different algorithms may satisfy one of these, rarely both, and often neither

Convergence rate

  • converges linearly(线性收敛): Assume the sequence x0, x1, . . . , xn converges to x∗.
Convergence rate

if there exists 0 < α < 1 and satisfied this formula, Here α is the rate of convergence.
i.e. the error is (eventually) reduced by a constant factor of α after each iteration

If α = 1 the sequence converges sublinearly*(亚线性).

  • Sequence converges superlinearly(序列超线性收敛)
    if for some q > 1 and α > 0
    Sequence converges superlinearly

    If q = 2, we say it converges quadratically(呈二次方收敛).

The Bisection Method

  • condition

  • 1)the function F(x) is continuous

  • 2)Assume we know two points xL and xR, such that
    F(xL) F(xR) ≤ 0
    called the bracket condition for the bracket [xL , xR ]

  • 3)the Intermediate Value Theorem: This implies that there is a solution x∗ ∈ [xL,xR], since the function changes sign over that interval

    The Bisection Method

  • Bisection Method is converges linearly and its converges rate is 1/2

  • Note: The convergence is not monotone(单调) in general.
    i.e. it can happen that for some steps n we have |F(xn+1)| > |F(xn)|.

  • The upper bound above guarantees that eventually lim n→∞ x Cn = x∗ so that limn→∞ F(xCn) = 0.

  • Pros and cons of bisection method

  • Performance:
    Guaranteed to converge to x∗
    Slow (linear convergence rate)

Other issues:

  • We require an initial bracket (2 values), not just an initial guess (1 value)
  • In practice we may have to search for a bracket given one point
  • The initial bracket [xL , xR ] may contain more than one zero and it is not clear which it will compute

The difference of Bisection Method and Newton Method

  • The Bisection Method is usually stopped when |b−a| < TOLx
    for a bracket [a, b].
  • Newton’s Method is usually stopped when
    |F(x)| < TOLF
    TOLx and TOLF are appropriately chosen tolerances
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