-0.000 282 005 784 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 784(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
-0.000 282 005 784(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:

|-0.000 282 005 784| = 0.000 282 005 784


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: 0.000 282 005 784.

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) 0.000 282 005 784 × 2 = 0 + 0.000 564 011 568;
  • 2) 0.000 564 011 568 × 2 = 0 + 0.001 128 023 136;
  • 3) 0.001 128 023 136 × 2 = 0 + 0.002 256 046 272;
  • 4) 0.002 256 046 272 × 2 = 0 + 0.004 512 092 544;
  • 5) 0.004 512 092 544 × 2 = 0 + 0.009 024 185 088;
  • 6) 0.009 024 185 088 × 2 = 0 + 0.018 048 370 176;
  • 7) 0.018 048 370 176 × 2 = 0 + 0.036 096 740 352;
  • 8) 0.036 096 740 352 × 2 = 0 + 0.072 193 480 704;
  • 9) 0.072 193 480 704 × 2 = 0 + 0.144 386 961 408;
  • 10) 0.144 386 961 408 × 2 = 0 + 0.288 773 922 816;
  • 11) 0.288 773 922 816 × 2 = 0 + 0.577 547 845 632;
  • 12) 0.577 547 845 632 × 2 = 1 + 0.155 095 691 264;
  • 13) 0.155 095 691 264 × 2 = 0 + 0.310 191 382 528;
  • 14) 0.310 191 382 528 × 2 = 0 + 0.620 382 765 056;
  • 15) 0.620 382 765 056 × 2 = 1 + 0.240 765 530 112;
  • 16) 0.240 765 530 112 × 2 = 0 + 0.481 531 060 224;
  • 17) 0.481 531 060 224 × 2 = 0 + 0.963 062 120 448;
  • 18) 0.963 062 120 448 × 2 = 1 + 0.926 124 240 896;
  • 19) 0.926 124 240 896 × 2 = 1 + 0.852 248 481 792;
  • 20) 0.852 248 481 792 × 2 = 1 + 0.704 496 963 584;
  • 21) 0.704 496 963 584 × 2 = 1 + 0.408 993 927 168;
  • 22) 0.408 993 927 168 × 2 = 0 + 0.817 987 854 336;
  • 23) 0.817 987 854 336 × 2 = 1 + 0.635 975 708 672;
  • 24) 0.635 975 708 672 × 2 = 1 + 0.271 951 417 344;
  • 25) 0.271 951 417 344 × 2 = 0 + 0.543 902 834 688;
  • 26) 0.543 902 834 688 × 2 = 1 + 0.087 805 669 376;
  • 27) 0.087 805 669 376 × 2 = 0 + 0.175 611 338 752;
  • 28) 0.175 611 338 752 × 2 = 0 + 0.351 222 677 504;
  • 29) 0.351 222 677 504 × 2 = 0 + 0.702 445 355 008;
  • 30) 0.702 445 355 008 × 2 = 1 + 0.404 890 710 016;
  • 31) 0.404 890 710 016 × 2 = 0 + 0.809 781 420 032;
  • 32) 0.809 781 420 032 × 2 = 1 + 0.619 562 840 064;
  • 33) 0.619 562 840 064 × 2 = 1 + 0.239 125 680 128;
  • 34) 0.239 125 680 128 × 2 = 0 + 0.478 251 360 256;
  • 35) 0.478 251 360 256 × 2 = 0 + 0.956 502 720 512;
  • 36) 0.956 502 720 512 × 2 = 1 + 0.913 005 441 024;
  • 37) 0.913 005 441 024 × 2 = 1 + 0.826 010 882 048;
  • 38) 0.826 010 882 048 × 2 = 1 + 0.652 021 764 096;
  • 39) 0.652 021 764 096 × 2 = 1 + 0.304 043 528 192;
  • 40) 0.304 043 528 192 × 2 = 0 + 0.608 087 056 384;
  • 41) 0.608 087 056 384 × 2 = 1 + 0.216 174 112 768;
  • 42) 0.216 174 112 768 × 2 = 0 + 0.432 348 225 536;
  • 43) 0.432 348 225 536 × 2 = 0 + 0.864 696 451 072;
  • 44) 0.864 696 451 072 × 2 = 1 + 0.729 392 902 144;
  • 45) 0.729 392 902 144 × 2 = 1 + 0.458 785 804 288;
  • 46) 0.458 785 804 288 × 2 = 0 + 0.917 571 608 576;
  • 47) 0.917 571 608 576 × 2 = 1 + 0.835 143 217 152;
  • 48) 0.835 143 217 152 × 2 = 1 + 0.670 286 434 304;
  • 49) 0.670 286 434 304 × 2 = 1 + 0.340 572 868 608;
  • 50) 0.340 572 868 608 × 2 = 0 + 0.681 145 737 216;
  • 51) 0.681 145 737 216 × 2 = 1 + 0.362 291 474 432;
  • 52) 0.362 291 474 432 × 2 = 0 + 0.724 582 948 864;
  • 53) 0.724 582 948 864 × 2 = 1 + 0.449 165 897 728;
  • 54) 0.449 165 897 728 × 2 = 0 + 0.898 331 795 456;
  • 55) 0.898 331 795 456 × 2 = 1 + 0.796 663 590 912;
  • 56) 0.796 663 590 912 × 2 = 1 + 0.593 327 181 824;
  • 57) 0.593 327 181 824 × 2 = 1 + 0.186 654 363 648;
  • 58) 0.186 654 363 648 × 2 = 0 + 0.373 308 727 296;
  • 59) 0.373 308 727 296 × 2 = 0 + 0.746 617 454 592;
  • 60) 0.746 617 454 592 × 2 = 1 + 0.493 234 909 184;
  • 61) 0.493 234 909 184 × 2 = 0 + 0.986 469 818 368;
  • 62) 0.986 469 818 368 × 2 = 1 + 0.972 939 636 736;
  • 63) 0.972 939 636 736 × 2 = 1 + 0.945 879 273 472;
  • 64) 0.945 879 273 472 × 2 = 1 + 0.891 758 546 944;

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:


0.000 282 005 784(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1001 1110 1001 1011 1010 1011 1001 0111(2)

6. Positive number before normalization:

0.000 282 005 784(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1001 1110 1001 1011 1010 1011 1001 0111(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:


0.000 282 005 784(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1001 1110 1001 1011 1010 1011 1001 0111(2) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1001 1110 1001 1011 1010 1011 1001 0111(2) × 20 =


1.0010 0111 1011 0100 0101 1001 1110 1001 1011 1010 1011 1001 0111(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 0101 1001 1110 1001 1011 1010 1011 1001 0111


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 0101 1001 1110 1001 1011 1010 1011 1001 0111 =


0010 0111 1011 0100 0101 1001 1110 1001 1011 1010 1011 1001 0111


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 0101 1001 1110 1001 1011 1010 1011 1001 0111


Decimal number -0.000 282 005 784 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0101 1001 1110 1001 1011 1010 1011 1001 0111


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