13 993 487 639.992 496 77 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 13 993 487 639.992 496 77(10) to 32 bit single precision IEEE 754 binary floating point representation standard (1 bit for sign, 8 bits for exponent, 23 bits for mantissa)

What are the steps to convert decimal number
13 993 487 639.992 496 77(10) to 32 bit single precision IEEE 754 binary floating point representation (1 bit for sign, 8 bits for exponent, 23 bits for mantissa)

1. First, convert to binary (in base 2) the integer part: 13 993 487 639.
Divide the number repeatedly by 2.

Keep track of each remainder.

We stop when we get a quotient that is equal to zero.


  • division = quotient + remainder;
  • 13 993 487 639 ÷ 2 = 6 996 743 819 + 1;
  • 6 996 743 819 ÷ 2 = 3 498 371 909 + 1;
  • 3 498 371 909 ÷ 2 = 1 749 185 954 + 1;
  • 1 749 185 954 ÷ 2 = 874 592 977 + 0;
  • 874 592 977 ÷ 2 = 437 296 488 + 1;
  • 437 296 488 ÷ 2 = 218 648 244 + 0;
  • 218 648 244 ÷ 2 = 109 324 122 + 0;
  • 109 324 122 ÷ 2 = 54 662 061 + 0;
  • 54 662 061 ÷ 2 = 27 331 030 + 1;
  • 27 331 030 ÷ 2 = 13 665 515 + 0;
  • 13 665 515 ÷ 2 = 6 832 757 + 1;
  • 6 832 757 ÷ 2 = 3 416 378 + 1;
  • 3 416 378 ÷ 2 = 1 708 189 + 0;
  • 1 708 189 ÷ 2 = 854 094 + 1;
  • 854 094 ÷ 2 = 427 047 + 0;
  • 427 047 ÷ 2 = 213 523 + 1;
  • 213 523 ÷ 2 = 106 761 + 1;
  • 106 761 ÷ 2 = 53 380 + 1;
  • 53 380 ÷ 2 = 26 690 + 0;
  • 26 690 ÷ 2 = 13 345 + 0;
  • 13 345 ÷ 2 = 6 672 + 1;
  • 6 672 ÷ 2 = 3 336 + 0;
  • 3 336 ÷ 2 = 1 668 + 0;
  • 1 668 ÷ 2 = 834 + 0;
  • 834 ÷ 2 = 417 + 0;
  • 417 ÷ 2 = 208 + 1;
  • 208 ÷ 2 = 104 + 0;
  • 104 ÷ 2 = 52 + 0;
  • 52 ÷ 2 = 26 + 0;
  • 26 ÷ 2 = 13 + 0;
  • 13 ÷ 2 = 6 + 1;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

2. Construct the base 2 representation of the integer part of the number.

Take all the remainders starting from the bottom of the list constructed above.

13 993 487 639(10) =


11 0100 0010 0001 0011 1010 1101 0001 0111(2)


3. Convert to binary (base 2) the fractional part: 0.992 496 77.

Multiply it repeatedly by 2.


Keep track of each integer part of the results.


Stop when we get a fractional part that is equal to zero.


  • #) multiplying = integer + fractional part;
  • 1) 0.992 496 77 × 2 = 1 + 0.984 993 54;
  • 2) 0.984 993 54 × 2 = 1 + 0.969 987 08;
  • 3) 0.969 987 08 × 2 = 1 + 0.939 974 16;
  • 4) 0.939 974 16 × 2 = 1 + 0.879 948 32;
  • 5) 0.879 948 32 × 2 = 1 + 0.759 896 64;
  • 6) 0.759 896 64 × 2 = 1 + 0.519 793 28;
  • 7) 0.519 793 28 × 2 = 1 + 0.039 586 56;
  • 8) 0.039 586 56 × 2 = 0 + 0.079 173 12;
  • 9) 0.079 173 12 × 2 = 0 + 0.158 346 24;
  • 10) 0.158 346 24 × 2 = 0 + 0.316 692 48;
  • 11) 0.316 692 48 × 2 = 0 + 0.633 384 96;
  • 12) 0.633 384 96 × 2 = 1 + 0.266 769 92;
  • 13) 0.266 769 92 × 2 = 0 + 0.533 539 84;
  • 14) 0.533 539 84 × 2 = 1 + 0.067 079 68;
  • 15) 0.067 079 68 × 2 = 0 + 0.134 159 36;
  • 16) 0.134 159 36 × 2 = 0 + 0.268 318 72;
  • 17) 0.268 318 72 × 2 = 0 + 0.536 637 44;
  • 18) 0.536 637 44 × 2 = 1 + 0.073 274 88;
  • 19) 0.073 274 88 × 2 = 0 + 0.146 549 76;
  • 20) 0.146 549 76 × 2 = 0 + 0.293 099 52;
  • 21) 0.293 099 52 × 2 = 0 + 0.586 199 04;
  • 22) 0.586 199 04 × 2 = 1 + 0.172 398 08;
  • 23) 0.172 398 08 × 2 = 0 + 0.344 796 16;
  • 24) 0.344 796 16 × 2 = 0 + 0.689 592 32;

We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit) and at least one integer that was different from zero => FULL STOP (Losing precision - the converted number we get in the end will be just a very good approximation of the initial one).


4. Construct the base 2 representation of the fractional part of the number.

Take all the integer parts of the multiplying operations, starting from the top of the constructed list above:


0.992 496 77(10) =


0.1111 1110 0001 0100 0100 0100(2)

5. Positive number before normalization:

13 993 487 639.992 496 77(10) =


11 0100 0010 0001 0011 1010 1101 0001 0111.1111 1110 0001 0100 0100 0100(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 33 positions to the left, so that only one non zero digit remains to the left of it:


13 993 487 639.992 496 77(10) =


11 0100 0010 0001 0011 1010 1101 0001 0111.1111 1110 0001 0100 0100 0100(2) =


11 0100 0010 0001 0011 1010 1101 0001 0111.1111 1110 0001 0100 0100 0100(2) × 20 =


1.1010 0001 0000 1001 1101 0110 1000 1011 1111 1111 0000 1010 0010 0010 0(2) × 233


7. Up to this moment, there are the following elements that would feed into the 32 bit single precision IEEE 754 binary floating point representation:

Sign 0 (a positive number)


Exponent (unadjusted): 33


Mantissa (not normalized):
1.1010 0001 0000 1001 1101 0110 1000 1011 1111 1111 0000 1010 0010 0010 0


8. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(8-1) - 1 =


33 + 2(8-1) - 1 =


(33 + 127)(10) =


160(10)


9. Convert the adjusted exponent from the decimal (base 10) to 8 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 160 ÷ 2 = 80 + 0;
  • 80 ÷ 2 = 40 + 0;
  • 40 ÷ 2 = 20 + 0;
  • 20 ÷ 2 = 10 + 0;
  • 10 ÷ 2 = 5 + 0;
  • 5 ÷ 2 = 2 + 1;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

10. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


160(10) =


1010 0000(2)


11. Normalize the mantissa.

a) Remove the leading (the leftmost) bit, since it's allways 1, and the decimal point, if the case.


b) Adjust its length to 23 bits, by removing the excess bits, from the right (if any of the excess bits is set on 1, we are losing precision...).


Mantissa (normalized) =


1. 101 0000 1000 0100 1110 1011 01 0001 0111 1111 1110 0001 0100 0100 0100 =


101 0000 1000 0100 1110 1011


12. The three elements that make up the number's 32 bit single precision IEEE 754 binary floating point representation:

Sign (1 bit) =
0 (a positive number)


Exponent (8 bits) =
1010 0000


Mantissa (23 bits) =
101 0000 1000 0100 1110 1011


Decimal number 13 993 487 639.992 496 77 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1010 0000 - 101 0000 1000 0100 1110 1011


How to convert decimal numbers from base ten to 32 bit single precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 32 bit single precision IEEE 754 binary floating point:

  • 1. If the number to be converted is negative, start with its the positive version.
  • 2. First convert the integer part. Divide repeatedly by 2 the base ten positive representation of the integer number that is to be converted to binary, until we get a quotient that is equal to zero, keeping track of each remainder.
  • 3. Construct the base 2 representation of the positive integer part of the number, by taking all the remainders of the previous dividing operations, starting from the bottom of the list constructed above. Thus, the last remainder of the divisions becomes the first symbol (the leftmost) of the base two number, while the first remainder becomes the last symbol (the rightmost).
  • 4. Then convert the fractional part. Multiply the number repeatedly by 2, until we get a fractional part that is equal to zero, keeping track of each integer part of the results.
  • 5. Construct the base 2 representation of the fractional part of the number by taking all the integer parts of the previous multiplying operations, starting from the top of the constructed list above (they should appear in the binary representation, from left to right, in the order they have been calculated).
  • 6. Normalize the binary representation of the number, by shifting the decimal point (or if you prefer, the decimal mark) "n" positions either to the left or to the right, so that only one non zero digit remains to the left of the decimal point.
  • 7. Adjust the exponent in 8 bit excess/bias notation and then convert it from decimal (base 10) to 8 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(8-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign if the case) and adjust its length to 23 bits, either by removing the excess bits from the right (losing precision...) or by adding extra '0' bits to the right.
  • 9. Sign (it takes 1 bit) is either 1 for a negative or 0 for a positive number.

Example: convert the negative number -25.347 from decimal system (base ten) to 32 bit single precision IEEE 754 binary floating point:

  • 1. Start with the positive version of the number:

    |-25.347| = 25.347

  • 2. First convert the integer part, 25. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 25 ÷ 2 = 12 + 1;
    • 12 ÷ 2 = 6 + 0;
    • 6 ÷ 2 = 3 + 0;
    • 3 ÷ 2 = 1 + 1;
    • 1 ÷ 2 = 0 + 1;
    • We have encountered a quotient that is ZERO => FULL STOP
  • 3. Construct the base 2 representation of the integer part of the number by taking all the remainders of the previous dividing operations, starting from the bottom of the list constructed above:

    25(10) = 1 1001(2)

  • 4. Then convert the fractional part, 0.347. Multiply repeatedly by 2, keeping track of each integer part of the results, until we get a fractional part that is equal to zero:
    • #) multiplying = integer + fractional part;
    • 1) 0.347 × 2 = 0 + 0.694;
    • 2) 0.694 × 2 = 1 + 0.388;
    • 3) 0.388 × 2 = 0 + 0.776;
    • 4) 0.776 × 2 = 1 + 0.552;
    • 5) 0.552 × 2 = 1 + 0.104;
    • 6) 0.104 × 2 = 0 + 0.208;
    • 7) 0.208 × 2 = 0 + 0.416;
    • 8) 0.416 × 2 = 0 + 0.832;
    • 9) 0.832 × 2 = 1 + 0.664;
    • 10) 0.664 × 2 = 1 + 0.328;
    • 11) 0.328 × 2 = 0 + 0.656;
    • 12) 0.656 × 2 = 1 + 0.312;
    • 13) 0.312 × 2 = 0 + 0.624;
    • 14) 0.624 × 2 = 1 + 0.248;
    • 15) 0.248 × 2 = 0 + 0.496;
    • 16) 0.496 × 2 = 0 + 0.992;
    • 17) 0.992 × 2 = 1 + 0.984;
    • 18) 0.984 × 2 = 1 + 0.968;
    • 19) 0.968 × 2 = 1 + 0.936;
    • 20) 0.936 × 2 = 1 + 0.872;
    • 21) 0.872 × 2 = 1 + 0.744;
    • 22) 0.744 × 2 = 1 + 0.488;
    • 23) 0.488 × 2 = 0 + 0.976;
    • 24) 0.976 × 2 = 1 + 0.952;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 23) and at least one integer part that was different from zero => FULL STOP (losing precision...).
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the previous multiplying operations, starting from the top of the constructed list above:

    0.347(10) = 0.0101 1000 1101 0100 1111 1101(2)

  • 6. Summarizing - the positive number before normalization:

    25.347(10) = 1 1001.0101 1000 1101 0100 1111 1101(2)

  • 7. Normalize the binary representation of the number, shifting the decimal point 4 positions to the left so that only one non-zero digit stays to the left of the decimal point:

    25.347(10) =
    1 1001.0101 1000 1101 0100 1111 1101(2) =
    1 1001.0101 1000 1101 0100 1111 1101(2) × 20 =
    1.1001 0101 1000 1101 0100 1111 1101(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 32 bit single precision IEEE 754 binary floating point:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1001 0101 1000 1101 0100 1111 1101

  • 9. Adjust the exponent in 8 bit excess/bias notation and then convert it from decimal (base 10) to 8 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as already demonstrated above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(8-1) - 1 = (4 + 127)(10) = 131(10) =
    1000 0011(2)

  • 10. Normalize the mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal point) and adjust its length to 23 bits, by removing the excess bits from the right (losing precision...):

    Mantissa (not-normalized): 1.1001 0101 1000 1101 0100 1111 1101

    Mantissa (normalized): 100 1010 1100 0110 1010 0111

  • Conclusion:

    Sign (1 bit) = 1 (a negative number)

    Exponent (8 bits) = 1000 0011

    Mantissa (23 bits) = 100 1010 1100 0110 1010 0111

  • Number -25.347, converted from the decimal system (base 10) to 32 bit single precision IEEE 754 binary floating point =
    1 - 1000 0011 - 100 1010 1100 0110 1010 0111