Math Problem Statement
Determine the real number represented by the 16 hexadecimal digit number 6074548800000000 considering it as a 64-bit IEEE 754 format double precision number.
Solution
To determine the real number represented by the hexadecimal value in the IEEE 754 double-precision floating-point format, we need to analyze its structure as per the IEEE 754 standard.
Step-by-Step Solution
-
Convert the Hexadecimal Value to Binary
The hexadecimal number can be broken down into binary:
So, in binary, we have:
-
Break Down the IEEE 754 Double-Precision Format
IEEE 754 double-precision format has:
- 1 sign bit (the first bit),
- 11 exponent bits (the next 11 bits),
- 52 fraction (mantissa) bits (the remaining 52 bits).
For this binary number:
- Sign bit:
0
(indicating a positive number), - Exponent bits:
11000000111
, - Mantissa bits:
0100010101001000100000000000000000000000000000000000
.
-
Interpret the Exponent
The exponent in binary,
11000000111
, converts to decimal:In IEEE 754 format, the exponent is stored with a bias of 1023. Thus, the actual exponent is:
-
Interpret the Mantissa (Fraction)
The mantissa in IEEE 754 format represents the fractional part. Since the exponent is not all 0s or 1s, we have a normalized number, and the mantissa has an implicit leading 1. So the mantissa is:
Converting this binary fraction to decimal:
-
Calculate the Final Value
Putting it all together, the value of the number is:
Substituting in our values:
-
Expressing in Decimal Notation
Calculating gives a very small positive number. This is approximately:
Final Answer
The real number represented by the hexadecimal value in IEEE 754 double precision is approximately:
Would you like a more detailed breakdown of any step, or do you have further questions?
Follow-up Questions
- How is the bias determined in IEEE 754 for different formats (single, double)?
- Why does IEEE 754 include an implicit leading 1 in normalized numbers?
- How does the IEEE 754 format handle extremely large or small numbers, including underflow?
- What is the difference between normalized and denormalized numbers in IEEE 754?
- How does floating-point rounding work, and what impact can it have on calculations?
Tip
For quick calculations involving IEEE 754 formats, you can use online IEEE 754 converters to save time on manual conversion.
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Math Problem Analysis
Mathematical Concepts
IEEE 754 Floating-Point Representation
Binary to Decimal Conversion
Floating-Point Arithmetic
Formulas
(-1)^sign * mantissa * 2^(exponent - bias)
IEEE 754 bias for double-precision: 1023
Theorems
IEEE 754 Standard for Floating-Point Arithmetic
Suitable Grade Level
College Level
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