-0.000 282 005 912 44 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 912 44(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
-0.000 282 005 912 44(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:

|-0.000 282 005 912 44| = 0.000 282 005 912 44


2. First, convert to binary (in base 2) the integer part: 0.
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;
  • 0 ÷ 2 = 0 + 0;

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.

0(10) =


0(2)


4. Convert to binary (base 2) the fractional part: 0.000 282 005 912 44.

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) 0.000 282 005 912 44 × 2 = 0 + 0.000 564 011 824 88;
  • 2) 0.000 564 011 824 88 × 2 = 0 + 0.001 128 023 649 76;
  • 3) 0.001 128 023 649 76 × 2 = 0 + 0.002 256 047 299 52;
  • 4) 0.002 256 047 299 52 × 2 = 0 + 0.004 512 094 599 04;
  • 5) 0.004 512 094 599 04 × 2 = 0 + 0.009 024 189 198 08;
  • 6) 0.009 024 189 198 08 × 2 = 0 + 0.018 048 378 396 16;
  • 7) 0.018 048 378 396 16 × 2 = 0 + 0.036 096 756 792 32;
  • 8) 0.036 096 756 792 32 × 2 = 0 + 0.072 193 513 584 64;
  • 9) 0.072 193 513 584 64 × 2 = 0 + 0.144 387 027 169 28;
  • 10) 0.144 387 027 169 28 × 2 = 0 + 0.288 774 054 338 56;
  • 11) 0.288 774 054 338 56 × 2 = 0 + 0.577 548 108 677 12;
  • 12) 0.577 548 108 677 12 × 2 = 1 + 0.155 096 217 354 24;
  • 13) 0.155 096 217 354 24 × 2 = 0 + 0.310 192 434 708 48;
  • 14) 0.310 192 434 708 48 × 2 = 0 + 0.620 384 869 416 96;
  • 15) 0.620 384 869 416 96 × 2 = 1 + 0.240 769 738 833 92;
  • 16) 0.240 769 738 833 92 × 2 = 0 + 0.481 539 477 667 84;
  • 17) 0.481 539 477 667 84 × 2 = 0 + 0.963 078 955 335 68;
  • 18) 0.963 078 955 335 68 × 2 = 1 + 0.926 157 910 671 36;
  • 19) 0.926 157 910 671 36 × 2 = 1 + 0.852 315 821 342 72;
  • 20) 0.852 315 821 342 72 × 2 = 1 + 0.704 631 642 685 44;
  • 21) 0.704 631 642 685 44 × 2 = 1 + 0.409 263 285 370 88;
  • 22) 0.409 263 285 370 88 × 2 = 0 + 0.818 526 570 741 76;
  • 23) 0.818 526 570 741 76 × 2 = 1 + 0.637 053 141 483 52;
  • 24) 0.637 053 141 483 52 × 2 = 1 + 0.274 106 282 967 04;
  • 25) 0.274 106 282 967 04 × 2 = 0 + 0.548 212 565 934 08;
  • 26) 0.548 212 565 934 08 × 2 = 1 + 0.096 425 131 868 16;
  • 27) 0.096 425 131 868 16 × 2 = 0 + 0.192 850 263 736 32;
  • 28) 0.192 850 263 736 32 × 2 = 0 + 0.385 700 527 472 64;
  • 29) 0.385 700 527 472 64 × 2 = 0 + 0.771 401 054 945 28;
  • 30) 0.771 401 054 945 28 × 2 = 1 + 0.542 802 109 890 56;
  • 31) 0.542 802 109 890 56 × 2 = 1 + 0.085 604 219 781 12;
  • 32) 0.085 604 219 781 12 × 2 = 0 + 0.171 208 439 562 24;
  • 33) 0.171 208 439 562 24 × 2 = 0 + 0.342 416 879 124 48;
  • 34) 0.342 416 879 124 48 × 2 = 0 + 0.684 833 758 248 96;
  • 35) 0.684 833 758 248 96 × 2 = 1 + 0.369 667 516 497 92;
  • 36) 0.369 667 516 497 92 × 2 = 0 + 0.739 335 032 995 84;
  • 37) 0.739 335 032 995 84 × 2 = 1 + 0.478 670 065 991 68;
  • 38) 0.478 670 065 991 68 × 2 = 0 + 0.957 340 131 983 36;
  • 39) 0.957 340 131 983 36 × 2 = 1 + 0.914 680 263 966 72;
  • 40) 0.914 680 263 966 72 × 2 = 1 + 0.829 360 527 933 44;
  • 41) 0.829 360 527 933 44 × 2 = 1 + 0.658 721 055 866 88;
  • 42) 0.658 721 055 866 88 × 2 = 1 + 0.317 442 111 733 76;
  • 43) 0.317 442 111 733 76 × 2 = 0 + 0.634 884 223 467 52;
  • 44) 0.634 884 223 467 52 × 2 = 1 + 0.269 768 446 935 04;
  • 45) 0.269 768 446 935 04 × 2 = 0 + 0.539 536 893 870 08;
  • 46) 0.539 536 893 870 08 × 2 = 1 + 0.079 073 787 740 16;
  • 47) 0.079 073 787 740 16 × 2 = 0 + 0.158 147 575 480 32;
  • 48) 0.158 147 575 480 32 × 2 = 0 + 0.316 295 150 960 64;
  • 49) 0.316 295 150 960 64 × 2 = 0 + 0.632 590 301 921 28;
  • 50) 0.632 590 301 921 28 × 2 = 1 + 0.265 180 603 842 56;
  • 51) 0.265 180 603 842 56 × 2 = 0 + 0.530 361 207 685 12;
  • 52) 0.530 361 207 685 12 × 2 = 1 + 0.060 722 415 370 24;
  • 53) 0.060 722 415 370 24 × 2 = 0 + 0.121 444 830 740 48;
  • 54) 0.121 444 830 740 48 × 2 = 0 + 0.242 889 661 480 96;
  • 55) 0.242 889 661 480 96 × 2 = 0 + 0.485 779 322 961 92;
  • 56) 0.485 779 322 961 92 × 2 = 0 + 0.971 558 645 923 84;
  • 57) 0.971 558 645 923 84 × 2 = 1 + 0.943 117 291 847 68;
  • 58) 0.943 117 291 847 68 × 2 = 1 + 0.886 234 583 695 36;
  • 59) 0.886 234 583 695 36 × 2 = 1 + 0.772 469 167 390 72;
  • 60) 0.772 469 167 390 72 × 2 = 1 + 0.544 938 334 781 44;
  • 61) 0.544 938 334 781 44 × 2 = 1 + 0.089 876 669 562 88;
  • 62) 0.089 876 669 562 88 × 2 = 0 + 0.179 753 339 125 76;
  • 63) 0.179 753 339 125 76 × 2 = 0 + 0.359 506 678 251 52;
  • 64) 0.359 506 678 251 52 × 2 = 0 + 0.719 013 356 503 04;

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:


0.000 282 005 912 44(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1011 1101 0100 0101 0000 1111 1000(2)

6. Positive number before normalization:

0.000 282 005 912 44(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1011 1101 0100 0101 0000 1111 1000(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 12 positions to the right, so that only one non zero digit remains to the left of it:


0.000 282 005 912 44(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1011 1101 0100 0101 0000 1111 1000(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1011 1101 0100 0101 0000 1111 1000(2) × 20 =


1.0010 0111 1011 0100 0110 0010 1011 1101 0100 0101 0000 1111 1000(2) × 2-12


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): -12


Mantissa (not normalized):
1.0010 0111 1011 0100 0110 0010 1011 1101 0100 0101 0000 1111 1000


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-12 + 2(11-1) - 1 =


(-12 + 1 023)(10) =


1 011(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;
  • 1 011 ÷ 2 = 505 + 1;
  • 505 ÷ 2 = 252 + 1;
  • 252 ÷ 2 = 126 + 0;
  • 126 ÷ 2 = 63 + 0;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


1011(10) =


011 1111 0011(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, only if necessary (not the case here).


Mantissa (normalized) =


1. 0010 0111 1011 0100 0110 0010 1011 1101 0100 0101 0000 1111 1000 =


0010 0111 1011 0100 0110 0010 1011 1101 0100 0101 0000 1111 1000


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) =
011 1111 0011


Mantissa (52 bits) =
0010 0111 1011 0100 0110 0010 1011 1101 0100 0101 0000 1111 1000


Decimal number -0.000 282 005 912 44 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0010 1011 1101 0100 0101 0000 1111 1000


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