-532.234 275 078 338 6 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -532.234 275 078 338 6(10) to 64 bit double precision IEEE 754 binary floating point representation standard (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

What are the steps to convert decimal number
-532.234 275 078 338 6(10) to 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. Start with the positive version of the number:

|-532.234 275 078 338 6| = 532.234 275 078 338 6


2. First, convert to binary (in base 2) the integer part: 532.
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;
  • 532 ÷ 2 = 266 + 0;
  • 266 ÷ 2 = 133 + 0;
  • 133 ÷ 2 = 66 + 1;
  • 66 ÷ 2 = 33 + 0;
  • 33 ÷ 2 = 16 + 1;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

3. 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.

532(10) =


10 0001 0100(2)


4. Convert to binary (base 2) the fractional part: 0.234 275 078 338 6.

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) 0.234 275 078 338 6 × 2 = 0 + 0.468 550 156 677 2;
  • 2) 0.468 550 156 677 2 × 2 = 0 + 0.937 100 313 354 4;
  • 3) 0.937 100 313 354 4 × 2 = 1 + 0.874 200 626 708 8;
  • 4) 0.874 200 626 708 8 × 2 = 1 + 0.748 401 253 417 6;
  • 5) 0.748 401 253 417 6 × 2 = 1 + 0.496 802 506 835 2;
  • 6) 0.496 802 506 835 2 × 2 = 0 + 0.993 605 013 670 4;
  • 7) 0.993 605 013 670 4 × 2 = 1 + 0.987 210 027 340 8;
  • 8) 0.987 210 027 340 8 × 2 = 1 + 0.974 420 054 681 6;
  • 9) 0.974 420 054 681 6 × 2 = 1 + 0.948 840 109 363 2;
  • 10) 0.948 840 109 363 2 × 2 = 1 + 0.897 680 218 726 4;
  • 11) 0.897 680 218 726 4 × 2 = 1 + 0.795 360 437 452 8;
  • 12) 0.795 360 437 452 8 × 2 = 1 + 0.590 720 874 905 6;
  • 13) 0.590 720 874 905 6 × 2 = 1 + 0.181 441 749 811 2;
  • 14) 0.181 441 749 811 2 × 2 = 0 + 0.362 883 499 622 4;
  • 15) 0.362 883 499 622 4 × 2 = 0 + 0.725 766 999 244 8;
  • 16) 0.725 766 999 244 8 × 2 = 1 + 0.451 533 998 489 6;
  • 17) 0.451 533 998 489 6 × 2 = 0 + 0.903 067 996 979 2;
  • 18) 0.903 067 996 979 2 × 2 = 1 + 0.806 135 993 958 4;
  • 19) 0.806 135 993 958 4 × 2 = 1 + 0.612 271 987 916 8;
  • 20) 0.612 271 987 916 8 × 2 = 1 + 0.224 543 975 833 6;
  • 21) 0.224 543 975 833 6 × 2 = 0 + 0.449 087 951 667 2;
  • 22) 0.449 087 951 667 2 × 2 = 0 + 0.898 175 903 334 4;
  • 23) 0.898 175 903 334 4 × 2 = 1 + 0.796 351 806 668 8;
  • 24) 0.796 351 806 668 8 × 2 = 1 + 0.592 703 613 337 6;
  • 25) 0.592 703 613 337 6 × 2 = 1 + 0.185 407 226 675 2;
  • 26) 0.185 407 226 675 2 × 2 = 0 + 0.370 814 453 350 4;
  • 27) 0.370 814 453 350 4 × 2 = 0 + 0.741 628 906 700 8;
  • 28) 0.741 628 906 700 8 × 2 = 1 + 0.483 257 813 401 6;
  • 29) 0.483 257 813 401 6 × 2 = 0 + 0.966 515 626 803 2;
  • 30) 0.966 515 626 803 2 × 2 = 1 + 0.933 031 253 606 4;
  • 31) 0.933 031 253 606 4 × 2 = 1 + 0.866 062 507 212 8;
  • 32) 0.866 062 507 212 8 × 2 = 1 + 0.732 125 014 425 6;
  • 33) 0.732 125 014 425 6 × 2 = 1 + 0.464 250 028 851 2;
  • 34) 0.464 250 028 851 2 × 2 = 0 + 0.928 500 057 702 4;
  • 35) 0.928 500 057 702 4 × 2 = 1 + 0.857 000 115 404 8;
  • 36) 0.857 000 115 404 8 × 2 = 1 + 0.714 000 230 809 6;
  • 37) 0.714 000 230 809 6 × 2 = 1 + 0.428 000 461 619 2;
  • 38) 0.428 000 461 619 2 × 2 = 0 + 0.856 000 923 238 4;
  • 39) 0.856 000 923 238 4 × 2 = 1 + 0.712 001 846 476 8;
  • 40) 0.712 001 846 476 8 × 2 = 1 + 0.424 003 692 953 6;
  • 41) 0.424 003 692 953 6 × 2 = 0 + 0.848 007 385 907 2;
  • 42) 0.848 007 385 907 2 × 2 = 1 + 0.696 014 771 814 4;
  • 43) 0.696 014 771 814 4 × 2 = 1 + 0.392 029 543 628 8;
  • 44) 0.392 029 543 628 8 × 2 = 0 + 0.784 059 087 257 6;
  • 45) 0.784 059 087 257 6 × 2 = 1 + 0.568 118 174 515 2;
  • 46) 0.568 118 174 515 2 × 2 = 1 + 0.136 236 349 030 4;
  • 47) 0.136 236 349 030 4 × 2 = 0 + 0.272 472 698 060 8;
  • 48) 0.272 472 698 060 8 × 2 = 0 + 0.544 945 396 121 6;
  • 49) 0.544 945 396 121 6 × 2 = 1 + 0.089 890 792 243 2;
  • 50) 0.089 890 792 243 2 × 2 = 0 + 0.179 781 584 486 4;
  • 51) 0.179 781 584 486 4 × 2 = 0 + 0.359 563 168 972 8;
  • 52) 0.359 563 168 972 8 × 2 = 0 + 0.719 126 337 945 6;
  • 53) 0.719 126 337 945 6 × 2 = 1 + 0.438 252 675 891 2;

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).


5. 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:


0.234 275 078 338 6(10) =


0.0011 1011 1111 1001 0111 0011 1001 0111 1011 1011 0110 1100 1000 1(2)

6. Positive number before normalization:

532.234 275 078 338 6(10) =


10 0001 0100.0011 1011 1111 1001 0111 0011 1001 0111 1011 1011 0110 1100 1000 1(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 9 positions to the left, so that only one non zero digit remains to the left of it:


532.234 275 078 338 6(10) =


10 0001 0100.0011 1011 1111 1001 0111 0011 1001 0111 1011 1011 0110 1100 1000 1(2) =


10 0001 0100.0011 1011 1111 1001 0111 0011 1001 0111 1011 1011 0110 1100 1000 1(2) × 20 =


1.0000 1010 0001 1101 1111 1100 1011 1001 1100 1011 1101 1101 1011 0110 0100 01(2) × 29


8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

Sign 1 (a negative number)


Exponent (unadjusted): 9


Mantissa (not normalized):
1.0000 1010 0001 1101 1111 1100 1011 1001 1100 1011 1101 1101 1011 0110 0100 01


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


9 + 2(11-1) - 1 =


(9 + 1 023)(10) =


1 032(10)


10. Convert the adjusted exponent from the decimal (base 10) to 11 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 1 032 ÷ 2 = 516 + 0;
  • 516 ÷ 2 = 258 + 0;
  • 258 ÷ 2 = 129 + 0;
  • 129 ÷ 2 = 64 + 1;
  • 64 ÷ 2 = 32 + 0;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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

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


Exponent (adjusted) =


1032(10) =


100 0000 1000(2)


12. 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 52 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. 0000 1010 0001 1101 1111 1100 1011 1001 1100 1011 1101 1101 1011 01 1001 0001 =


0000 1010 0001 1101 1111 1100 1011 1001 1100 1011 1101 1101 1011


13. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

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


Exponent (11 bits) =
100 0000 1000


Mantissa (52 bits) =
0000 1010 0001 1101 1111 1100 1011 1001 1100 1011 1101 1101 1011


Decimal number -532.234 275 078 338 6 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 1000 - 0000 1010 0001 1101 1111 1100 1011 1001 1100 1011 1101 1101 1011


How to convert numbers from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 64 bit double 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 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 from the previous 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 multiplying operations, starting from the top of the list constructed 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, shifting the decimal mark (the decimal point) "n" positions either to the left, or to the right, so that only one non zero digit remains to the left of the decimal mark.
  • 7. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal mark, if the case) and adjust its length to 52 bits, either by removing the excess bits from the right (losing precision...) or by adding extra bits set on '0' 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 -31.640 215 from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point:

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

    |-31.640 215| = 31.640 215

  • 2. First convert the integer part, 31. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 31 ÷ 2 = 15 + 1;
    • 15 ÷ 2 = 7 + 1;
    • 7 ÷ 2 = 3 + 1;
    • 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:

    31(10) = 1 1111(2)

  • 4. Then, convert the fractional part, 0.640 215. 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) 0.640 215 × 2 = 1 + 0.280 43;
    • 2) 0.280 43 × 2 = 0 + 0.560 86;
    • 3) 0.560 86 × 2 = 1 + 0.121 72;
    • 4) 0.121 72 × 2 = 0 + 0.243 44;
    • 5) 0.243 44 × 2 = 0 + 0.486 88;
    • 6) 0.486 88 × 2 = 0 + 0.973 76;
    • 7) 0.973 76 × 2 = 1 + 0.947 52;
    • 8) 0.947 52 × 2 = 1 + 0.895 04;
    • 9) 0.895 04 × 2 = 1 + 0.790 08;
    • 10) 0.790 08 × 2 = 1 + 0.580 16;
    • 11) 0.580 16 × 2 = 1 + 0.160 32;
    • 12) 0.160 32 × 2 = 0 + 0.320 64;
    • 13) 0.320 64 × 2 = 0 + 0.641 28;
    • 14) 0.641 28 × 2 = 1 + 0.282 56;
    • 15) 0.282 56 × 2 = 0 + 0.565 12;
    • 16) 0.565 12 × 2 = 1 + 0.130 24;
    • 17) 0.130 24 × 2 = 0 + 0.260 48;
    • 18) 0.260 48 × 2 = 0 + 0.520 96;
    • 19) 0.520 96 × 2 = 1 + 0.041 92;
    • 20) 0.041 92 × 2 = 0 + 0.083 84;
    • 21) 0.083 84 × 2 = 0 + 0.167 68;
    • 22) 0.167 68 × 2 = 0 + 0.335 36;
    • 23) 0.335 36 × 2 = 0 + 0.670 72;
    • 24) 0.670 72 × 2 = 1 + 0.341 44;
    • 25) 0.341 44 × 2 = 0 + 0.682 88;
    • 26) 0.682 88 × 2 = 1 + 0.365 76;
    • 27) 0.365 76 × 2 = 0 + 0.731 52;
    • 28) 0.731 52 × 2 = 1 + 0.463 04;
    • 29) 0.463 04 × 2 = 0 + 0.926 08;
    • 30) 0.926 08 × 2 = 1 + 0.852 16;
    • 31) 0.852 16 × 2 = 1 + 0.704 32;
    • 32) 0.704 32 × 2 = 1 + 0.408 64;
    • 33) 0.408 64 × 2 = 0 + 0.817 28;
    • 34) 0.817 28 × 2 = 1 + 0.634 56;
    • 35) 0.634 56 × 2 = 1 + 0.269 12;
    • 36) 0.269 12 × 2 = 0 + 0.538 24;
    • 37) 0.538 24 × 2 = 1 + 0.076 48;
    • 38) 0.076 48 × 2 = 0 + 0.152 96;
    • 39) 0.152 96 × 2 = 0 + 0.305 92;
    • 40) 0.305 92 × 2 = 0 + 0.611 84;
    • 41) 0.611 84 × 2 = 1 + 0.223 68;
    • 42) 0.223 68 × 2 = 0 + 0.447 36;
    • 43) 0.447 36 × 2 = 0 + 0.894 72;
    • 44) 0.894 72 × 2 = 1 + 0.789 44;
    • 45) 0.789 44 × 2 = 1 + 0.578 88;
    • 46) 0.578 88 × 2 = 1 + 0.157 76;
    • 47) 0.157 76 × 2 = 0 + 0.315 52;
    • 48) 0.315 52 × 2 = 0 + 0.631 04;
    • 49) 0.631 04 × 2 = 1 + 0.262 08;
    • 50) 0.262 08 × 2 = 0 + 0.524 16;
    • 51) 0.524 16 × 2 = 1 + 0.048 32;
    • 52) 0.048 32 × 2 = 0 + 0.096 64;
    • 53) 0.096 64 × 2 = 0 + 0.193 28;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 52) 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:

    0.640 215(10) = 0.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 6. Summarizing - the positive number before normalization:

    31.640 215(10) = 1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

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

    31.640 215(10) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 20 =
    1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

  • 9. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as shown above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1 = (4 + 1023)(10) = 1027(10) =
    100 0000 0011(2)

  • 10. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign) and adjust its length to 52 bits, by removing the excess bits, from the right (losing precision...):

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

    Mantissa (normalized): 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Conclusion:

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

    Exponent (8 bits) = 100 0000 0011

    Mantissa (52 bits) = 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Number -31.640 215, converted from decimal system (base 10) to 64 bit double precision IEEE 754 binary floating point =
    1 - 100 0000 0011 - 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100