-0.000 282 006 208 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 208(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
-0.000 282 006 208(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:

|-0.000 282 006 208| = 0.000 282 006 208


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: 0.000 282 006 208.

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) 0.000 282 006 208 × 2 = 0 + 0.000 564 012 416;
  • 2) 0.000 564 012 416 × 2 = 0 + 0.001 128 024 832;
  • 3) 0.001 128 024 832 × 2 = 0 + 0.002 256 049 664;
  • 4) 0.002 256 049 664 × 2 = 0 + 0.004 512 099 328;
  • 5) 0.004 512 099 328 × 2 = 0 + 0.009 024 198 656;
  • 6) 0.009 024 198 656 × 2 = 0 + 0.018 048 397 312;
  • 7) 0.018 048 397 312 × 2 = 0 + 0.036 096 794 624;
  • 8) 0.036 096 794 624 × 2 = 0 + 0.072 193 589 248;
  • 9) 0.072 193 589 248 × 2 = 0 + 0.144 387 178 496;
  • 10) 0.144 387 178 496 × 2 = 0 + 0.288 774 356 992;
  • 11) 0.288 774 356 992 × 2 = 0 + 0.577 548 713 984;
  • 12) 0.577 548 713 984 × 2 = 1 + 0.155 097 427 968;
  • 13) 0.155 097 427 968 × 2 = 0 + 0.310 194 855 936;
  • 14) 0.310 194 855 936 × 2 = 0 + 0.620 389 711 872;
  • 15) 0.620 389 711 872 × 2 = 1 + 0.240 779 423 744;
  • 16) 0.240 779 423 744 × 2 = 0 + 0.481 558 847 488;
  • 17) 0.481 558 847 488 × 2 = 0 + 0.963 117 694 976;
  • 18) 0.963 117 694 976 × 2 = 1 + 0.926 235 389 952;
  • 19) 0.926 235 389 952 × 2 = 1 + 0.852 470 779 904;
  • 20) 0.852 470 779 904 × 2 = 1 + 0.704 941 559 808;
  • 21) 0.704 941 559 808 × 2 = 1 + 0.409 883 119 616;
  • 22) 0.409 883 119 616 × 2 = 0 + 0.819 766 239 232;
  • 23) 0.819 766 239 232 × 2 = 1 + 0.639 532 478 464;
  • 24) 0.639 532 478 464 × 2 = 1 + 0.279 064 956 928;
  • 25) 0.279 064 956 928 × 2 = 0 + 0.558 129 913 856;
  • 26) 0.558 129 913 856 × 2 = 1 + 0.116 259 827 712;
  • 27) 0.116 259 827 712 × 2 = 0 + 0.232 519 655 424;
  • 28) 0.232 519 655 424 × 2 = 0 + 0.465 039 310 848;
  • 29) 0.465 039 310 848 × 2 = 0 + 0.930 078 621 696;
  • 30) 0.930 078 621 696 × 2 = 1 + 0.860 157 243 392;
  • 31) 0.860 157 243 392 × 2 = 1 + 0.720 314 486 784;
  • 32) 0.720 314 486 784 × 2 = 1 + 0.440 628 973 568;
  • 33) 0.440 628 973 568 × 2 = 0 + 0.881 257 947 136;
  • 34) 0.881 257 947 136 × 2 = 1 + 0.762 515 894 272;
  • 35) 0.762 515 894 272 × 2 = 1 + 0.525 031 788 544;
  • 36) 0.525 031 788 544 × 2 = 1 + 0.050 063 577 088;
  • 37) 0.050 063 577 088 × 2 = 0 + 0.100 127 154 176;
  • 38) 0.100 127 154 176 × 2 = 0 + 0.200 254 308 352;
  • 39) 0.200 254 308 352 × 2 = 0 + 0.400 508 616 704;
  • 40) 0.400 508 616 704 × 2 = 0 + 0.801 017 233 408;
  • 41) 0.801 017 233 408 × 2 = 1 + 0.602 034 466 816;
  • 42) 0.602 034 466 816 × 2 = 1 + 0.204 068 933 632;
  • 43) 0.204 068 933 632 × 2 = 0 + 0.408 137 867 264;
  • 44) 0.408 137 867 264 × 2 = 0 + 0.816 275 734 528;
  • 45) 0.816 275 734 528 × 2 = 1 + 0.632 551 469 056;
  • 46) 0.632 551 469 056 × 2 = 1 + 0.265 102 938 112;
  • 47) 0.265 102 938 112 × 2 = 0 + 0.530 205 876 224;
  • 48) 0.530 205 876 224 × 2 = 1 + 0.060 411 752 448;
  • 49) 0.060 411 752 448 × 2 = 0 + 0.120 823 504 896;
  • 50) 0.120 823 504 896 × 2 = 0 + 0.241 647 009 792;
  • 51) 0.241 647 009 792 × 2 = 0 + 0.483 294 019 584;
  • 52) 0.483 294 019 584 × 2 = 0 + 0.966 588 039 168;
  • 53) 0.966 588 039 168 × 2 = 1 + 0.933 176 078 336;
  • 54) 0.933 176 078 336 × 2 = 1 + 0.866 352 156 672;
  • 55) 0.866 352 156 672 × 2 = 1 + 0.732 704 313 344;
  • 56) 0.732 704 313 344 × 2 = 1 + 0.465 408 626 688;
  • 57) 0.465 408 626 688 × 2 = 0 + 0.930 817 253 376;
  • 58) 0.930 817 253 376 × 2 = 1 + 0.861 634 506 752;
  • 59) 0.861 634 506 752 × 2 = 1 + 0.723 269 013 504;
  • 60) 0.723 269 013 504 × 2 = 1 + 0.446 538 027 008;
  • 61) 0.446 538 027 008 × 2 = 0 + 0.893 076 054 016;
  • 62) 0.893 076 054 016 × 2 = 1 + 0.786 152 108 032;
  • 63) 0.786 152 108 032 × 2 = 1 + 0.572 304 216 064;
  • 64) 0.572 304 216 064 × 2 = 1 + 0.144 608 432 128;

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:


0.000 282 006 208(10) =


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

6. Positive number before normalization:

0.000 282 006 208(10) =


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


0.000 282 006 208(10) =


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


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


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


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


Decimal number -0.000 282 006 208 converted to 64 bit double precision IEEE 754 binary floating point representation:

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