-0.000 282 005 912 27 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 912 27(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 27(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 27| = 0.000 282 005 912 27


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 27.

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 27 × 2 = 0 + 0.000 564 011 824 54;
  • 2) 0.000 564 011 824 54 × 2 = 0 + 0.001 128 023 649 08;
  • 3) 0.001 128 023 649 08 × 2 = 0 + 0.002 256 047 298 16;
  • 4) 0.002 256 047 298 16 × 2 = 0 + 0.004 512 094 596 32;
  • 5) 0.004 512 094 596 32 × 2 = 0 + 0.009 024 189 192 64;
  • 6) 0.009 024 189 192 64 × 2 = 0 + 0.018 048 378 385 28;
  • 7) 0.018 048 378 385 28 × 2 = 0 + 0.036 096 756 770 56;
  • 8) 0.036 096 756 770 56 × 2 = 0 + 0.072 193 513 541 12;
  • 9) 0.072 193 513 541 12 × 2 = 0 + 0.144 387 027 082 24;
  • 10) 0.144 387 027 082 24 × 2 = 0 + 0.288 774 054 164 48;
  • 11) 0.288 774 054 164 48 × 2 = 0 + 0.577 548 108 328 96;
  • 12) 0.577 548 108 328 96 × 2 = 1 + 0.155 096 216 657 92;
  • 13) 0.155 096 216 657 92 × 2 = 0 + 0.310 192 433 315 84;
  • 14) 0.310 192 433 315 84 × 2 = 0 + 0.620 384 866 631 68;
  • 15) 0.620 384 866 631 68 × 2 = 1 + 0.240 769 733 263 36;
  • 16) 0.240 769 733 263 36 × 2 = 0 + 0.481 539 466 526 72;
  • 17) 0.481 539 466 526 72 × 2 = 0 + 0.963 078 933 053 44;
  • 18) 0.963 078 933 053 44 × 2 = 1 + 0.926 157 866 106 88;
  • 19) 0.926 157 866 106 88 × 2 = 1 + 0.852 315 732 213 76;
  • 20) 0.852 315 732 213 76 × 2 = 1 + 0.704 631 464 427 52;
  • 21) 0.704 631 464 427 52 × 2 = 1 + 0.409 262 928 855 04;
  • 22) 0.409 262 928 855 04 × 2 = 0 + 0.818 525 857 710 08;
  • 23) 0.818 525 857 710 08 × 2 = 1 + 0.637 051 715 420 16;
  • 24) 0.637 051 715 420 16 × 2 = 1 + 0.274 103 430 840 32;
  • 25) 0.274 103 430 840 32 × 2 = 0 + 0.548 206 861 680 64;
  • 26) 0.548 206 861 680 64 × 2 = 1 + 0.096 413 723 361 28;
  • 27) 0.096 413 723 361 28 × 2 = 0 + 0.192 827 446 722 56;
  • 28) 0.192 827 446 722 56 × 2 = 0 + 0.385 654 893 445 12;
  • 29) 0.385 654 893 445 12 × 2 = 0 + 0.771 309 786 890 24;
  • 30) 0.771 309 786 890 24 × 2 = 1 + 0.542 619 573 780 48;
  • 31) 0.542 619 573 780 48 × 2 = 1 + 0.085 239 147 560 96;
  • 32) 0.085 239 147 560 96 × 2 = 0 + 0.170 478 295 121 92;
  • 33) 0.170 478 295 121 92 × 2 = 0 + 0.340 956 590 243 84;
  • 34) 0.340 956 590 243 84 × 2 = 0 + 0.681 913 180 487 68;
  • 35) 0.681 913 180 487 68 × 2 = 1 + 0.363 826 360 975 36;
  • 36) 0.363 826 360 975 36 × 2 = 0 + 0.727 652 721 950 72;
  • 37) 0.727 652 721 950 72 × 2 = 1 + 0.455 305 443 901 44;
  • 38) 0.455 305 443 901 44 × 2 = 0 + 0.910 610 887 802 88;
  • 39) 0.910 610 887 802 88 × 2 = 1 + 0.821 221 775 605 76;
  • 40) 0.821 221 775 605 76 × 2 = 1 + 0.642 443 551 211 52;
  • 41) 0.642 443 551 211 52 × 2 = 1 + 0.284 887 102 423 04;
  • 42) 0.284 887 102 423 04 × 2 = 0 + 0.569 774 204 846 08;
  • 43) 0.569 774 204 846 08 × 2 = 1 + 0.139 548 409 692 16;
  • 44) 0.139 548 409 692 16 × 2 = 0 + 0.279 096 819 384 32;
  • 45) 0.279 096 819 384 32 × 2 = 0 + 0.558 193 638 768 64;
  • 46) 0.558 193 638 768 64 × 2 = 1 + 0.116 387 277 537 28;
  • 47) 0.116 387 277 537 28 × 2 = 0 + 0.232 774 555 074 56;
  • 48) 0.232 774 555 074 56 × 2 = 0 + 0.465 549 110 149 12;
  • 49) 0.465 549 110 149 12 × 2 = 0 + 0.931 098 220 298 24;
  • 50) 0.931 098 220 298 24 × 2 = 1 + 0.862 196 440 596 48;
  • 51) 0.862 196 440 596 48 × 2 = 1 + 0.724 392 881 192 96;
  • 52) 0.724 392 881 192 96 × 2 = 1 + 0.448 785 762 385 92;
  • 53) 0.448 785 762 385 92 × 2 = 0 + 0.897 571 524 771 84;
  • 54) 0.897 571 524 771 84 × 2 = 1 + 0.795 143 049 543 68;
  • 55) 0.795 143 049 543 68 × 2 = 1 + 0.590 286 099 087 36;
  • 56) 0.590 286 099 087 36 × 2 = 1 + 0.180 572 198 174 72;
  • 57) 0.180 572 198 174 72 × 2 = 0 + 0.361 144 396 349 44;
  • 58) 0.361 144 396 349 44 × 2 = 0 + 0.722 288 792 698 88;
  • 59) 0.722 288 792 698 88 × 2 = 1 + 0.444 577 585 397 76;
  • 60) 0.444 577 585 397 76 × 2 = 0 + 0.889 155 170 795 52;
  • 61) 0.889 155 170 795 52 × 2 = 1 + 0.778 310 341 591 04;
  • 62) 0.778 310 341 591 04 × 2 = 1 + 0.556 620 683 182 08;
  • 63) 0.556 620 683 182 08 × 2 = 1 + 0.113 241 366 364 16;
  • 64) 0.113 241 366 364 16 × 2 = 0 + 0.226 482 732 728 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).


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 27(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1011 1010 0100 0111 0111 0010 1110(2)

6. Positive number before normalization:

0.000 282 005 912 27(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1011 1010 0100 0111 0111 0010 1110(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 27(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1011 1010 0100 0111 0111 0010 1110(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1011 1010 0100 0111 0111 0010 1110(2) × 20 =


1.0010 0111 1011 0100 0110 0010 1011 1010 0100 0111 0111 0010 1110(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 1010 0100 0111 0111 0010 1110


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 1010 0100 0111 0111 0010 1110 =


0010 0111 1011 0100 0110 0010 1011 1010 0100 0111 0111 0010 1110


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 1010 0100 0111 0111 0010 1110


Decimal number -0.000 282 005 912 27 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0010 1011 1010 0100 0111 0111 0010 1110


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