-0.000 282 005 712 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 712(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
-0.000 282 005 712(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:

|-0.000 282 005 712| = 0.000 282 005 712


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: 0.000 282 005 712.

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) 0.000 282 005 712 × 2 = 0 + 0.000 564 011 424;
  • 2) 0.000 564 011 424 × 2 = 0 + 0.001 128 022 848;
  • 3) 0.001 128 022 848 × 2 = 0 + 0.002 256 045 696;
  • 4) 0.002 256 045 696 × 2 = 0 + 0.004 512 091 392;
  • 5) 0.004 512 091 392 × 2 = 0 + 0.009 024 182 784;
  • 6) 0.009 024 182 784 × 2 = 0 + 0.018 048 365 568;
  • 7) 0.018 048 365 568 × 2 = 0 + 0.036 096 731 136;
  • 8) 0.036 096 731 136 × 2 = 0 + 0.072 193 462 272;
  • 9) 0.072 193 462 272 × 2 = 0 + 0.144 386 924 544;
  • 10) 0.144 386 924 544 × 2 = 0 + 0.288 773 849 088;
  • 11) 0.288 773 849 088 × 2 = 0 + 0.577 547 698 176;
  • 12) 0.577 547 698 176 × 2 = 1 + 0.155 095 396 352;
  • 13) 0.155 095 396 352 × 2 = 0 + 0.310 190 792 704;
  • 14) 0.310 190 792 704 × 2 = 0 + 0.620 381 585 408;
  • 15) 0.620 381 585 408 × 2 = 1 + 0.240 763 170 816;
  • 16) 0.240 763 170 816 × 2 = 0 + 0.481 526 341 632;
  • 17) 0.481 526 341 632 × 2 = 0 + 0.963 052 683 264;
  • 18) 0.963 052 683 264 × 2 = 1 + 0.926 105 366 528;
  • 19) 0.926 105 366 528 × 2 = 1 + 0.852 210 733 056;
  • 20) 0.852 210 733 056 × 2 = 1 + 0.704 421 466 112;
  • 21) 0.704 421 466 112 × 2 = 1 + 0.408 842 932 224;
  • 22) 0.408 842 932 224 × 2 = 0 + 0.817 685 864 448;
  • 23) 0.817 685 864 448 × 2 = 1 + 0.635 371 728 896;
  • 24) 0.635 371 728 896 × 2 = 1 + 0.270 743 457 792;
  • 25) 0.270 743 457 792 × 2 = 0 + 0.541 486 915 584;
  • 26) 0.541 486 915 584 × 2 = 1 + 0.082 973 831 168;
  • 27) 0.082 973 831 168 × 2 = 0 + 0.165 947 662 336;
  • 28) 0.165 947 662 336 × 2 = 0 + 0.331 895 324 672;
  • 29) 0.331 895 324 672 × 2 = 0 + 0.663 790 649 344;
  • 30) 0.663 790 649 344 × 2 = 1 + 0.327 581 298 688;
  • 31) 0.327 581 298 688 × 2 = 0 + 0.655 162 597 376;
  • 32) 0.655 162 597 376 × 2 = 1 + 0.310 325 194 752;
  • 33) 0.310 325 194 752 × 2 = 0 + 0.620 650 389 504;
  • 34) 0.620 650 389 504 × 2 = 1 + 0.241 300 779 008;
  • 35) 0.241 300 779 008 × 2 = 0 + 0.482 601 558 016;
  • 36) 0.482 601 558 016 × 2 = 0 + 0.965 203 116 032;
  • 37) 0.965 203 116 032 × 2 = 1 + 0.930 406 232 064;
  • 38) 0.930 406 232 064 × 2 = 1 + 0.860 812 464 128;
  • 39) 0.860 812 464 128 × 2 = 1 + 0.721 624 928 256;
  • 40) 0.721 624 928 256 × 2 = 1 + 0.443 249 856 512;
  • 41) 0.443 249 856 512 × 2 = 0 + 0.886 499 713 024;
  • 42) 0.886 499 713 024 × 2 = 1 + 0.772 999 426 048;
  • 43) 0.772 999 426 048 × 2 = 1 + 0.545 998 852 096;
  • 44) 0.545 998 852 096 × 2 = 1 + 0.091 997 704 192;
  • 45) 0.091 997 704 192 × 2 = 0 + 0.183 995 408 384;
  • 46) 0.183 995 408 384 × 2 = 0 + 0.367 990 816 768;
  • 47) 0.367 990 816 768 × 2 = 0 + 0.735 981 633 536;
  • 48) 0.735 981 633 536 × 2 = 1 + 0.471 963 267 072;
  • 49) 0.471 963 267 072 × 2 = 0 + 0.943 926 534 144;
  • 50) 0.943 926 534 144 × 2 = 1 + 0.887 853 068 288;
  • 51) 0.887 853 068 288 × 2 = 1 + 0.775 706 136 576;
  • 52) 0.775 706 136 576 × 2 = 1 + 0.551 412 273 152;
  • 53) 0.551 412 273 152 × 2 = 1 + 0.102 824 546 304;
  • 54) 0.102 824 546 304 × 2 = 0 + 0.205 649 092 608;
  • 55) 0.205 649 092 608 × 2 = 0 + 0.411 298 185 216;
  • 56) 0.411 298 185 216 × 2 = 0 + 0.822 596 370 432;
  • 57) 0.822 596 370 432 × 2 = 1 + 0.645 192 740 864;
  • 58) 0.645 192 740 864 × 2 = 1 + 0.290 385 481 728;
  • 59) 0.290 385 481 728 × 2 = 0 + 0.580 770 963 456;
  • 60) 0.580 770 963 456 × 2 = 1 + 0.161 541 926 912;
  • 61) 0.161 541 926 912 × 2 = 0 + 0.323 083 853 824;
  • 62) 0.323 083 853 824 × 2 = 0 + 0.646 167 707 648;
  • 63) 0.646 167 707 648 × 2 = 1 + 0.292 335 415 296;
  • 64) 0.292 335 415 296 × 2 = 0 + 0.584 670 830 592;

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:


0.000 282 005 712(10) =


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

6. Positive number before normalization:

0.000 282 005 712(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 0100 1111 0111 0001 0111 1000 1101 0010(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:


0.000 282 005 712(10) =


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


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


1.0010 0111 1011 0100 0101 0100 1111 0111 0001 0111 1000 1101 0010(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 0100 1111 0111 0001 0111 1000 1101 0010


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 0100 1111 0111 0001 0111 1000 1101 0010 =


0010 0111 1011 0100 0101 0100 1111 0111 0001 0111 1000 1101 0010


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 0100 1111 0111 0001 0111 1000 1101 0010


Decimal number -0.000 282 005 712 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0101 0100 1111 0111 0001 0111 1000 1101 0010


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