-0.000 282 005 568 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 568(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
-0.000 282 005 568(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:

|-0.000 282 005 568| = 0.000 282 005 568


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: 0.000 282 005 568.

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) 0.000 282 005 568 × 2 = 0 + 0.000 564 011 136;
  • 2) 0.000 564 011 136 × 2 = 0 + 0.001 128 022 272;
  • 3) 0.001 128 022 272 × 2 = 0 + 0.002 256 044 544;
  • 4) 0.002 256 044 544 × 2 = 0 + 0.004 512 089 088;
  • 5) 0.004 512 089 088 × 2 = 0 + 0.009 024 178 176;
  • 6) 0.009 024 178 176 × 2 = 0 + 0.018 048 356 352;
  • 7) 0.018 048 356 352 × 2 = 0 + 0.036 096 712 704;
  • 8) 0.036 096 712 704 × 2 = 0 + 0.072 193 425 408;
  • 9) 0.072 193 425 408 × 2 = 0 + 0.144 386 850 816;
  • 10) 0.144 386 850 816 × 2 = 0 + 0.288 773 701 632;
  • 11) 0.288 773 701 632 × 2 = 0 + 0.577 547 403 264;
  • 12) 0.577 547 403 264 × 2 = 1 + 0.155 094 806 528;
  • 13) 0.155 094 806 528 × 2 = 0 + 0.310 189 613 056;
  • 14) 0.310 189 613 056 × 2 = 0 + 0.620 379 226 112;
  • 15) 0.620 379 226 112 × 2 = 1 + 0.240 758 452 224;
  • 16) 0.240 758 452 224 × 2 = 0 + 0.481 516 904 448;
  • 17) 0.481 516 904 448 × 2 = 0 + 0.963 033 808 896;
  • 18) 0.963 033 808 896 × 2 = 1 + 0.926 067 617 792;
  • 19) 0.926 067 617 792 × 2 = 1 + 0.852 135 235 584;
  • 20) 0.852 135 235 584 × 2 = 1 + 0.704 270 471 168;
  • 21) 0.704 270 471 168 × 2 = 1 + 0.408 540 942 336;
  • 22) 0.408 540 942 336 × 2 = 0 + 0.817 081 884 672;
  • 23) 0.817 081 884 672 × 2 = 1 + 0.634 163 769 344;
  • 24) 0.634 163 769 344 × 2 = 1 + 0.268 327 538 688;
  • 25) 0.268 327 538 688 × 2 = 0 + 0.536 655 077 376;
  • 26) 0.536 655 077 376 × 2 = 1 + 0.073 310 154 752;
  • 27) 0.073 310 154 752 × 2 = 0 + 0.146 620 309 504;
  • 28) 0.146 620 309 504 × 2 = 0 + 0.293 240 619 008;
  • 29) 0.293 240 619 008 × 2 = 0 + 0.586 481 238 016;
  • 30) 0.586 481 238 016 × 2 = 1 + 0.172 962 476 032;
  • 31) 0.172 962 476 032 × 2 = 0 + 0.345 924 952 064;
  • 32) 0.345 924 952 064 × 2 = 0 + 0.691 849 904 128;
  • 33) 0.691 849 904 128 × 2 = 1 + 0.383 699 808 256;
  • 34) 0.383 699 808 256 × 2 = 0 + 0.767 399 616 512;
  • 35) 0.767 399 616 512 × 2 = 1 + 0.534 799 233 024;
  • 36) 0.534 799 233 024 × 2 = 1 + 0.069 598 466 048;
  • 37) 0.069 598 466 048 × 2 = 0 + 0.139 196 932 096;
  • 38) 0.139 196 932 096 × 2 = 0 + 0.278 393 864 192;
  • 39) 0.278 393 864 192 × 2 = 0 + 0.556 787 728 384;
  • 40) 0.556 787 728 384 × 2 = 1 + 0.113 575 456 768;
  • 41) 0.113 575 456 768 × 2 = 0 + 0.227 150 913 536;
  • 42) 0.227 150 913 536 × 2 = 0 + 0.454 301 827 072;
  • 43) 0.454 301 827 072 × 2 = 0 + 0.908 603 654 144;
  • 44) 0.908 603 654 144 × 2 = 1 + 0.817 207 308 288;
  • 45) 0.817 207 308 288 × 2 = 1 + 0.634 414 616 576;
  • 46) 0.634 414 616 576 × 2 = 1 + 0.268 829 233 152;
  • 47) 0.268 829 233 152 × 2 = 0 + 0.537 658 466 304;
  • 48) 0.537 658 466 304 × 2 = 1 + 0.075 316 932 608;
  • 49) 0.075 316 932 608 × 2 = 0 + 0.150 633 865 216;
  • 50) 0.150 633 865 216 × 2 = 0 + 0.301 267 730 432;
  • 51) 0.301 267 730 432 × 2 = 0 + 0.602 535 460 864;
  • 52) 0.602 535 460 864 × 2 = 1 + 0.205 070 921 728;
  • 53) 0.205 070 921 728 × 2 = 0 + 0.410 141 843 456;
  • 54) 0.410 141 843 456 × 2 = 0 + 0.820 283 686 912;
  • 55) 0.820 283 686 912 × 2 = 1 + 0.640 567 373 824;
  • 56) 0.640 567 373 824 × 2 = 1 + 0.281 134 747 648;
  • 57) 0.281 134 747 648 × 2 = 0 + 0.562 269 495 296;
  • 58) 0.562 269 495 296 × 2 = 1 + 0.124 538 990 592;
  • 59) 0.124 538 990 592 × 2 = 0 + 0.249 077 981 184;
  • 60) 0.249 077 981 184 × 2 = 0 + 0.498 155 962 368;
  • 61) 0.498 155 962 368 × 2 = 0 + 0.996 311 924 736;
  • 62) 0.996 311 924 736 × 2 = 1 + 0.992 623 849 472;
  • 63) 0.992 623 849 472 × 2 = 1 + 0.985 247 698 944;
  • 64) 0.985 247 698 944 × 2 = 1 + 0.970 495 397 888;

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:


0.000 282 005 568(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1011 0001 0001 1101 0001 0011 0100 0111(2)

6. Positive number before normalization:

0.000 282 005 568(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1011 0001 0001 1101 0001 0011 0100 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:


0.000 282 005 568(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1011 0001 0001 1101 0001 0011 0100 0111(2) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1011 0001 0001 1101 0001 0011 0100 0111(2) × 20 =


1.0010 0111 1011 0100 0100 1011 0001 0001 1101 0001 0011 0100 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 0100 1011 0001 0001 1101 0001 0011 0100 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 0100 1011 0001 0001 1101 0001 0011 0100 0111 =


0010 0111 1011 0100 0100 1011 0001 0001 1101 0001 0011 0100 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 0100 1011 0001 0001 1101 0001 0011 0100 0111


Decimal number -0.000 282 005 568 converted to 64 bit double precision IEEE 754 binary floating point representation:

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