-0.000 282 005 887 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 887(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
-0.000 282 005 887(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:

|-0.000 282 005 887| = 0.000 282 005 887


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: 0.000 282 005 887.

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) 0.000 282 005 887 × 2 = 0 + 0.000 564 011 774;
  • 2) 0.000 564 011 774 × 2 = 0 + 0.001 128 023 548;
  • 3) 0.001 128 023 548 × 2 = 0 + 0.002 256 047 096;
  • 4) 0.002 256 047 096 × 2 = 0 + 0.004 512 094 192;
  • 5) 0.004 512 094 192 × 2 = 0 + 0.009 024 188 384;
  • 6) 0.009 024 188 384 × 2 = 0 + 0.018 048 376 768;
  • 7) 0.018 048 376 768 × 2 = 0 + 0.036 096 753 536;
  • 8) 0.036 096 753 536 × 2 = 0 + 0.072 193 507 072;
  • 9) 0.072 193 507 072 × 2 = 0 + 0.144 387 014 144;
  • 10) 0.144 387 014 144 × 2 = 0 + 0.288 774 028 288;
  • 11) 0.288 774 028 288 × 2 = 0 + 0.577 548 056 576;
  • 12) 0.577 548 056 576 × 2 = 1 + 0.155 096 113 152;
  • 13) 0.155 096 113 152 × 2 = 0 + 0.310 192 226 304;
  • 14) 0.310 192 226 304 × 2 = 0 + 0.620 384 452 608;
  • 15) 0.620 384 452 608 × 2 = 1 + 0.240 768 905 216;
  • 16) 0.240 768 905 216 × 2 = 0 + 0.481 537 810 432;
  • 17) 0.481 537 810 432 × 2 = 0 + 0.963 075 620 864;
  • 18) 0.963 075 620 864 × 2 = 1 + 0.926 151 241 728;
  • 19) 0.926 151 241 728 × 2 = 1 + 0.852 302 483 456;
  • 20) 0.852 302 483 456 × 2 = 1 + 0.704 604 966 912;
  • 21) 0.704 604 966 912 × 2 = 1 + 0.409 209 933 824;
  • 22) 0.409 209 933 824 × 2 = 0 + 0.818 419 867 648;
  • 23) 0.818 419 867 648 × 2 = 1 + 0.636 839 735 296;
  • 24) 0.636 839 735 296 × 2 = 1 + 0.273 679 470 592;
  • 25) 0.273 679 470 592 × 2 = 0 + 0.547 358 941 184;
  • 26) 0.547 358 941 184 × 2 = 1 + 0.094 717 882 368;
  • 27) 0.094 717 882 368 × 2 = 0 + 0.189 435 764 736;
  • 28) 0.189 435 764 736 × 2 = 0 + 0.378 871 529 472;
  • 29) 0.378 871 529 472 × 2 = 0 + 0.757 743 058 944;
  • 30) 0.757 743 058 944 × 2 = 1 + 0.515 486 117 888;
  • 31) 0.515 486 117 888 × 2 = 1 + 0.030 972 235 776;
  • 32) 0.030 972 235 776 × 2 = 0 + 0.061 944 471 552;
  • 33) 0.061 944 471 552 × 2 = 0 + 0.123 888 943 104;
  • 34) 0.123 888 943 104 × 2 = 0 + 0.247 777 886 208;
  • 35) 0.247 777 886 208 × 2 = 0 + 0.495 555 772 416;
  • 36) 0.495 555 772 416 × 2 = 0 + 0.991 111 544 832;
  • 37) 0.991 111 544 832 × 2 = 1 + 0.982 223 089 664;
  • 38) 0.982 223 089 664 × 2 = 1 + 0.964 446 179 328;
  • 39) 0.964 446 179 328 × 2 = 1 + 0.928 892 358 656;
  • 40) 0.928 892 358 656 × 2 = 1 + 0.857 784 717 312;
  • 41) 0.857 784 717 312 × 2 = 1 + 0.715 569 434 624;
  • 42) 0.715 569 434 624 × 2 = 1 + 0.431 138 869 248;
  • 43) 0.431 138 869 248 × 2 = 0 + 0.862 277 738 496;
  • 44) 0.862 277 738 496 × 2 = 1 + 0.724 555 476 992;
  • 45) 0.724 555 476 992 × 2 = 1 + 0.449 110 953 984;
  • 46) 0.449 110 953 984 × 2 = 0 + 0.898 221 907 968;
  • 47) 0.898 221 907 968 × 2 = 1 + 0.796 443 815 936;
  • 48) 0.796 443 815 936 × 2 = 1 + 0.592 887 631 872;
  • 49) 0.592 887 631 872 × 2 = 1 + 0.185 775 263 744;
  • 50) 0.185 775 263 744 × 2 = 0 + 0.371 550 527 488;
  • 51) 0.371 550 527 488 × 2 = 0 + 0.743 101 054 976;
  • 52) 0.743 101 054 976 × 2 = 1 + 0.486 202 109 952;
  • 53) 0.486 202 109 952 × 2 = 0 + 0.972 404 219 904;
  • 54) 0.972 404 219 904 × 2 = 1 + 0.944 808 439 808;
  • 55) 0.944 808 439 808 × 2 = 1 + 0.889 616 879 616;
  • 56) 0.889 616 879 616 × 2 = 1 + 0.779 233 759 232;
  • 57) 0.779 233 759 232 × 2 = 1 + 0.558 467 518 464;
  • 58) 0.558 467 518 464 × 2 = 1 + 0.116 935 036 928;
  • 59) 0.116 935 036 928 × 2 = 0 + 0.233 870 073 856;
  • 60) 0.233 870 073 856 × 2 = 0 + 0.467 740 147 712;
  • 61) 0.467 740 147 712 × 2 = 0 + 0.935 480 295 424;
  • 62) 0.935 480 295 424 × 2 = 1 + 0.870 960 590 848;
  • 63) 0.870 960 590 848 × 2 = 1 + 0.741 921 181 696;
  • 64) 0.741 921 181 696 × 2 = 1 + 0.483 842 363 392;

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:


0.000 282 005 887(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 1111 1101 1011 1001 0111 1100 0111(2)

6. Positive number before normalization:

0.000 282 005 887(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 1111 1101 1011 1001 0111 1100 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:


0.000 282 005 887(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 1111 1101 1011 1001 0111 1100 0111(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 1111 1101 1011 1001 0111 1100 0111(2) × 20 =


1.0010 0111 1011 0100 0110 0000 1111 1101 1011 1001 0111 1100 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 0110 0000 1111 1101 1011 1001 0111 1100 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 0110 0000 1111 1101 1011 1001 0111 1100 0111 =


0010 0111 1011 0100 0110 0000 1111 1101 1011 1001 0111 1100 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 0110 0000 1111 1101 1011 1001 0111 1100 0111


Decimal number -0.000 282 005 887 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0000 1111 1101 1011 1001 0111 1100 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