-0.000 282 006 313 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 313(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
-0.000 282 006 313(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:

|-0.000 282 006 313| = 0.000 282 006 313


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: 0.000 282 006 313.

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) 0.000 282 006 313 × 2 = 0 + 0.000 564 012 626;
  • 2) 0.000 564 012 626 × 2 = 0 + 0.001 128 025 252;
  • 3) 0.001 128 025 252 × 2 = 0 + 0.002 256 050 504;
  • 4) 0.002 256 050 504 × 2 = 0 + 0.004 512 101 008;
  • 5) 0.004 512 101 008 × 2 = 0 + 0.009 024 202 016;
  • 6) 0.009 024 202 016 × 2 = 0 + 0.018 048 404 032;
  • 7) 0.018 048 404 032 × 2 = 0 + 0.036 096 808 064;
  • 8) 0.036 096 808 064 × 2 = 0 + 0.072 193 616 128;
  • 9) 0.072 193 616 128 × 2 = 0 + 0.144 387 232 256;
  • 10) 0.144 387 232 256 × 2 = 0 + 0.288 774 464 512;
  • 11) 0.288 774 464 512 × 2 = 0 + 0.577 548 929 024;
  • 12) 0.577 548 929 024 × 2 = 1 + 0.155 097 858 048;
  • 13) 0.155 097 858 048 × 2 = 0 + 0.310 195 716 096;
  • 14) 0.310 195 716 096 × 2 = 0 + 0.620 391 432 192;
  • 15) 0.620 391 432 192 × 2 = 1 + 0.240 782 864 384;
  • 16) 0.240 782 864 384 × 2 = 0 + 0.481 565 728 768;
  • 17) 0.481 565 728 768 × 2 = 0 + 0.963 131 457 536;
  • 18) 0.963 131 457 536 × 2 = 1 + 0.926 262 915 072;
  • 19) 0.926 262 915 072 × 2 = 1 + 0.852 525 830 144;
  • 20) 0.852 525 830 144 × 2 = 1 + 0.705 051 660 288;
  • 21) 0.705 051 660 288 × 2 = 1 + 0.410 103 320 576;
  • 22) 0.410 103 320 576 × 2 = 0 + 0.820 206 641 152;
  • 23) 0.820 206 641 152 × 2 = 1 + 0.640 413 282 304;
  • 24) 0.640 413 282 304 × 2 = 1 + 0.280 826 564 608;
  • 25) 0.280 826 564 608 × 2 = 0 + 0.561 653 129 216;
  • 26) 0.561 653 129 216 × 2 = 1 + 0.123 306 258 432;
  • 27) 0.123 306 258 432 × 2 = 0 + 0.246 612 516 864;
  • 28) 0.246 612 516 864 × 2 = 0 + 0.493 225 033 728;
  • 29) 0.493 225 033 728 × 2 = 0 + 0.986 450 067 456;
  • 30) 0.986 450 067 456 × 2 = 1 + 0.972 900 134 912;
  • 31) 0.972 900 134 912 × 2 = 1 + 0.945 800 269 824;
  • 32) 0.945 800 269 824 × 2 = 1 + 0.891 600 539 648;
  • 33) 0.891 600 539 648 × 2 = 1 + 0.783 201 079 296;
  • 34) 0.783 201 079 296 × 2 = 1 + 0.566 402 158 592;
  • 35) 0.566 402 158 592 × 2 = 1 + 0.132 804 317 184;
  • 36) 0.132 804 317 184 × 2 = 0 + 0.265 608 634 368;
  • 37) 0.265 608 634 368 × 2 = 0 + 0.531 217 268 736;
  • 38) 0.531 217 268 736 × 2 = 1 + 0.062 434 537 472;
  • 39) 0.062 434 537 472 × 2 = 0 + 0.124 869 074 944;
  • 40) 0.124 869 074 944 × 2 = 0 + 0.249 738 149 888;
  • 41) 0.249 738 149 888 × 2 = 0 + 0.499 476 299 776;
  • 42) 0.499 476 299 776 × 2 = 0 + 0.998 952 599 552;
  • 43) 0.998 952 599 552 × 2 = 1 + 0.997 905 199 104;
  • 44) 0.997 905 199 104 × 2 = 1 + 0.995 810 398 208;
  • 45) 0.995 810 398 208 × 2 = 1 + 0.991 620 796 416;
  • 46) 0.991 620 796 416 × 2 = 1 + 0.983 241 592 832;
  • 47) 0.983 241 592 832 × 2 = 1 + 0.966 483 185 664;
  • 48) 0.966 483 185 664 × 2 = 1 + 0.932 966 371 328;
  • 49) 0.932 966 371 328 × 2 = 1 + 0.865 932 742 656;
  • 50) 0.865 932 742 656 × 2 = 1 + 0.731 865 485 312;
  • 51) 0.731 865 485 312 × 2 = 1 + 0.463 730 970 624;
  • 52) 0.463 730 970 624 × 2 = 0 + 0.927 461 941 248;
  • 53) 0.927 461 941 248 × 2 = 1 + 0.854 923 882 496;
  • 54) 0.854 923 882 496 × 2 = 1 + 0.709 847 764 992;
  • 55) 0.709 847 764 992 × 2 = 1 + 0.419 695 529 984;
  • 56) 0.419 695 529 984 × 2 = 0 + 0.839 391 059 968;
  • 57) 0.839 391 059 968 × 2 = 1 + 0.678 782 119 936;
  • 58) 0.678 782 119 936 × 2 = 1 + 0.357 564 239 872;
  • 59) 0.357 564 239 872 × 2 = 0 + 0.715 128 479 744;
  • 60) 0.715 128 479 744 × 2 = 1 + 0.430 256 959 488;
  • 61) 0.430 256 959 488 × 2 = 0 + 0.860 513 918 976;
  • 62) 0.860 513 918 976 × 2 = 1 + 0.721 027 837 952;
  • 63) 0.721 027 837 952 × 2 = 1 + 0.442 055 675 904;
  • 64) 0.442 055 675 904 × 2 = 0 + 0.884 111 351 808;

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:


0.000 282 006 313(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1110 0100 0011 1111 1110 1110 1101 0110(2)

6. Positive number before normalization:

0.000 282 006 313(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1110 0100 0011 1111 1110 1110 1101 0110(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:


0.000 282 006 313(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1110 0100 0011 1111 1110 1110 1101 0110(2) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1110 0100 0011 1111 1110 1110 1101 0110(2) × 20 =


1.0010 0111 1011 0100 0111 1110 0100 0011 1111 1110 1110 1101 0110(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 1110 0100 0011 1111 1110 1110 1101 0110


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 1110 0100 0011 1111 1110 1110 1101 0110 =


0010 0111 1011 0100 0111 1110 0100 0011 1111 1110 1110 1101 0110


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 1110 0100 0011 1111 1110 1110 1101 0110


Decimal number -0.000 282 006 313 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0111 1110 0100 0011 1111 1110 1110 1101 0110


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