Question: Computer representation of numbers Please BOX your final results Problem 1 (15 points) In this problem, you will prove that the absolute value of the

 Computer representation of numbers Please BOX your final results Problem 1(15 points) In this problem, you will prove that the absolute valueof the true relative round-off error Et/x associated with the approximate representation

Computer representation of numbers Please BOX your final results Problem 1 (15 points) In this problem, you will prove that the absolute value of the true relative round-off error Et/x associated with the approximate representation of any number x in any normalized floating-point system (binary, decimal, ) that relies on chopping is always less than the machine epsilon of that system. Consider a normalized (regular normalization as described in the textbook, not IEEE normalization) floating-point system with t significant figures: in that system, a number xFp can be represented exactly as where the ni are the t integers of the normalized mantissa, b is the base (which can be anything: 2, 8,10.,..) of the system and e is the exponent of the number. The number x that you are trying to represent can either be among the finite number of xfp values (in which lucky case E,0), or be located in between 2 consecutive xFp values with the same exponent e, xm and xm+1, and it will be chopped to xm, as illustrated below: (5 points) For a given exponent e, express the absolute value of the spacing |Ax in terms of t, b and e. a. b. (5 points) For the same exponent e as in part a), calculate the largest possible value of Ax/x in this normalized system, and express your result in terms of t and b. when (5 points) Use your class notes and part b) to prove that, for any value ofx,E, chopping is used by the systenm c. Please note: although you have derived this result for the textbook normalization, it applies similarly to the IEEE normalization; the only difference in that case is that the IEEE 754 standard relies on rounding, and that the relationship is therefore This important result means that, for any normalized floating-point system, the machine epsilon indicates what the maximum possible relative round-off error is

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