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Integration

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Integration Integration Problem: An experiment has measured the number of particles entering a counter per unit time dN(t)/dt, as a function of time. – PowerPoint PPT presentation

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Title: Integration


1
Integration
2
Integration
  • Problem
  • An experiment has measured the number of
    particles entering a counter per unit time
    dN(t)/dt, as a function of time. The problem may
    be to determine the number of particles that
    entered in the first second.

3
Integration
  • Problem
  • An experiment has measured the number of
    particles entering a counter per unit time
    dN(t)/dt, as a function of time. The problem may
    be to determine the number of particles that
    entered in the first second.

4
Integration
  • Integration is an important in Physics.
  • used to determine the rate of growth in bacteria
    or to find the distance given the velocity (s
    ?vdt) as well as many other uses.
  • The most familiar practical (probably the 1st
    usage) use of integration is to calculate the
    area.

5
Integration
  • Generally we use formulae to determine the
    integral of a function
  • F(x) can be found if its antiderivative, f(x) is
    known.

6
Integration
  • when the antiderivative is unknown we are
    required to determine f(x) numerically.

7
Integration
  • when the antiderivative is unknown we are
    required to determine f(x) numerically.
  • To determine the definite integral we find the
    area between the curve and the x-axis.
  • This is the principle of numerical integration.

8
Integration
  • The traditional way to find the area is to divide
    the area into boxes and count the number of
    boxes or quadrilaterals.

9
Integration
  • One simple way to find the area is to integrate
    using midpoints.

10
Integration
Figure shows the area under a curve using the
midpoints
11
Integration
  • One simple way to find the area is to integrate
    using midpoints.
  • The midpoint rule uses a Riemann sum where the
    subinterval representatives are the midpoints of
    the subintervals.
  • For some functions it may be easy to choose a
    partition that more closely approximates the
    definite integral using midpoints.

12
Integration
  • The integral of the function is approximated by a
    summation of the strips or boxes.
  • where

13
Integration
  • Practically this is dividing the interval (a, b)
    into vertical strips and adding the area of these
    strips.

Figure shows the area under a curve using the
midpoints
14
Integration
  • The width of the strips is often made equal but
    this is not always required.

15
Integration
  • There are various integration methods Trapezoid,
    Simpsons, Milne, Gaussian Quadrature for
    example.
  • Well be looking in detail at the Trapezoid and
    variants of the Simpsons method.

16
Trapezoidal Rule
17
Trapezoidal Rule
  • is an improvement on the midpoint implementation.

18
Trapezoidal Rule
  • is an improvement on the midpoint implementation.
  • the midpoints is inaccurate in that there are
    pieces of the boxes above and below the curve
    (over and under estimates).

19
Trapezoidal Rule
  • Instead the curve is approximated using a
    sequence of straight lines, slanted to match
    the curve.

fi1
fi
20
Trapezoidal Rule
  • By doing this we approximate the curve by a
    polynomial of degree-1.

21
Trapezoidal Rule
  • Clearly the area of one rectangular strip from xi
    to xi1 is given by

22
Trapezoidal Rule
  • Clearly the area of one rectangular strip from xi
    to xi1 is given by
  • Generally is used. h is
    the width of a strip.

23
Trapezoidal Rule
  • The composite Trapezium rule is obtained by
    applying the equation .1 over all the intervals
    of interest.

24
Trapezoidal Rule
  • The composite Trapezium rule is obtained by
    applying the equation .1 over all the intervals
    of interest.
  • Thus,
  • ,if the interval h is the same for each
    strip.

25
Trapezoidal Rule
  • Note that each internal point is counted and
    therefore has a weight h, while end points are
    counted once and have a weight of h/2.

26
Trapezoidal Rule
  • Given the data in the following table use the
    trapezoid rule to estimate the integral from x
    1.8 to x 3.4. The data in the table are for ex
    and the true value is 23.9144.

27
Trapezoidal Rule
  • As an exercise show that the approximation given
    by the trapezium rule gives 23.9944.

28
Simpsons Rule
29
Simpsons Rule
  • The midpoint rule was first improved upon by the
    trapezium rule.

30
Simpsons Rule
  • The midpoint rule was first improved upon by the
    trapezium rule.
  • A further improvement is the Simpson's rule.

31
Simpsons Rule
  • The midpoint rule was first improved upon by the
    trapezium rule.
  • A further improvement is the Simpson's rule.
  • Instead of approximating the curve by a straight
    line, we approximate it by a quadratic or cubic
    function.

32
Simpsons Rule
  • Diagram showing approximation using Simpsons
    Rule.

33
Simpsons Rule
  • There are two variations of the rule Simpsons
    1/3 rule and Simpsons 3/8 rule.

34
Simpsons Rule
  • The formula for the Simpsons 1/3,

35
Simpsons Rule
  • The integration is over pairs of intervals and
    requires that total number of intervals be even
    of the total number of points N be odd.

36
Simpsons Rule
  • The formula for the Simpsons 3/8,

37
Simpsons Rule
  • If the number of strips is divisible by three we
    can use the 3/8 rule.

38
Simpsons Rule
  • http//metric.ma.ic.ac.uk/integration/techniques/d
    efinite/numerical-methods/exploration/index.html
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