-0.000 282 011 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 011 2(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
-0.000 282 011 2(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:

|-0.000 282 011 2| = 0.000 282 011 2


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: 0.000 282 011 2.

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) 0.000 282 011 2 × 2 = 0 + 0.000 564 022 4;
  • 2) 0.000 564 022 4 × 2 = 0 + 0.001 128 044 8;
  • 3) 0.001 128 044 8 × 2 = 0 + 0.002 256 089 6;
  • 4) 0.002 256 089 6 × 2 = 0 + 0.004 512 179 2;
  • 5) 0.004 512 179 2 × 2 = 0 + 0.009 024 358 4;
  • 6) 0.009 024 358 4 × 2 = 0 + 0.018 048 716 8;
  • 7) 0.018 048 716 8 × 2 = 0 + 0.036 097 433 6;
  • 8) 0.036 097 433 6 × 2 = 0 + 0.072 194 867 2;
  • 9) 0.072 194 867 2 × 2 = 0 + 0.144 389 734 4;
  • 10) 0.144 389 734 4 × 2 = 0 + 0.288 779 468 8;
  • 11) 0.288 779 468 8 × 2 = 0 + 0.577 558 937 6;
  • 12) 0.577 558 937 6 × 2 = 1 + 0.155 117 875 2;
  • 13) 0.155 117 875 2 × 2 = 0 + 0.310 235 750 4;
  • 14) 0.310 235 750 4 × 2 = 0 + 0.620 471 500 8;
  • 15) 0.620 471 500 8 × 2 = 1 + 0.240 943 001 6;
  • 16) 0.240 943 001 6 × 2 = 0 + 0.481 886 003 2;
  • 17) 0.481 886 003 2 × 2 = 0 + 0.963 772 006 4;
  • 18) 0.963 772 006 4 × 2 = 1 + 0.927 544 012 8;
  • 19) 0.927 544 012 8 × 2 = 1 + 0.855 088 025 6;
  • 20) 0.855 088 025 6 × 2 = 1 + 0.710 176 051 2;
  • 21) 0.710 176 051 2 × 2 = 1 + 0.420 352 102 4;
  • 22) 0.420 352 102 4 × 2 = 0 + 0.840 704 204 8;
  • 23) 0.840 704 204 8 × 2 = 1 + 0.681 408 409 6;
  • 24) 0.681 408 409 6 × 2 = 1 + 0.362 816 819 2;
  • 25) 0.362 816 819 2 × 2 = 0 + 0.725 633 638 4;
  • 26) 0.725 633 638 4 × 2 = 1 + 0.451 267 276 8;
  • 27) 0.451 267 276 8 × 2 = 0 + 0.902 534 553 6;
  • 28) 0.902 534 553 6 × 2 = 1 + 0.805 069 107 2;
  • 29) 0.805 069 107 2 × 2 = 1 + 0.610 138 214 4;
  • 30) 0.610 138 214 4 × 2 = 1 + 0.220 276 428 8;
  • 31) 0.220 276 428 8 × 2 = 0 + 0.440 552 857 6;
  • 32) 0.440 552 857 6 × 2 = 0 + 0.881 105 715 2;
  • 33) 0.881 105 715 2 × 2 = 1 + 0.762 211 430 4;
  • 34) 0.762 211 430 4 × 2 = 1 + 0.524 422 860 8;
  • 35) 0.524 422 860 8 × 2 = 1 + 0.048 845 721 6;
  • 36) 0.048 845 721 6 × 2 = 0 + 0.097 691 443 2;
  • 37) 0.097 691 443 2 × 2 = 0 + 0.195 382 886 4;
  • 38) 0.195 382 886 4 × 2 = 0 + 0.390 765 772 8;
  • 39) 0.390 765 772 8 × 2 = 0 + 0.781 531 545 6;
  • 40) 0.781 531 545 6 × 2 = 1 + 0.563 063 091 2;
  • 41) 0.563 063 091 2 × 2 = 1 + 0.126 126 182 4;
  • 42) 0.126 126 182 4 × 2 = 0 + 0.252 252 364 8;
  • 43) 0.252 252 364 8 × 2 = 0 + 0.504 504 729 6;
  • 44) 0.504 504 729 6 × 2 = 1 + 0.009 009 459 2;
  • 45) 0.009 009 459 2 × 2 = 0 + 0.018 018 918 4;
  • 46) 0.018 018 918 4 × 2 = 0 + 0.036 037 836 8;
  • 47) 0.036 037 836 8 × 2 = 0 + 0.072 075 673 6;
  • 48) 0.072 075 673 6 × 2 = 0 + 0.144 151 347 2;
  • 49) 0.144 151 347 2 × 2 = 0 + 0.288 302 694 4;
  • 50) 0.288 302 694 4 × 2 = 0 + 0.576 605 388 8;
  • 51) 0.576 605 388 8 × 2 = 1 + 0.153 210 777 6;
  • 52) 0.153 210 777 6 × 2 = 0 + 0.306 421 555 2;
  • 53) 0.306 421 555 2 × 2 = 0 + 0.612 843 110 4;
  • 54) 0.612 843 110 4 × 2 = 1 + 0.225 686 220 8;
  • 55) 0.225 686 220 8 × 2 = 0 + 0.451 372 441 6;
  • 56) 0.451 372 441 6 × 2 = 0 + 0.902 744 883 2;
  • 57) 0.902 744 883 2 × 2 = 1 + 0.805 489 766 4;
  • 58) 0.805 489 766 4 × 2 = 1 + 0.610 979 532 8;
  • 59) 0.610 979 532 8 × 2 = 1 + 0.221 959 065 6;
  • 60) 0.221 959 065 6 × 2 = 0 + 0.443 918 131 2;
  • 61) 0.443 918 131 2 × 2 = 0 + 0.887 836 262 4;
  • 62) 0.887 836 262 4 × 2 = 1 + 0.775 672 524 8;
  • 63) 0.775 672 524 8 × 2 = 1 + 0.551 345 049 6;
  • 64) 0.551 345 049 6 × 2 = 1 + 0.102 690 099 2;

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:


0.000 282 011 2(10) =


0.0000 0000 0001 0010 0111 1011 0101 1100 1110 0001 1001 0000 0010 0100 1110 0111(2)

6. Positive number before normalization:

0.000 282 011 2(10) =


0.0000 0000 0001 0010 0111 1011 0101 1100 1110 0001 1001 0000 0010 0100 1110 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:


0.000 282 011 2(10) =


0.0000 0000 0001 0010 0111 1011 0101 1100 1110 0001 1001 0000 0010 0100 1110 0111(2) =


0.0000 0000 0001 0010 0111 1011 0101 1100 1110 0001 1001 0000 0010 0100 1110 0111(2) × 20 =


1.0010 0111 1011 0101 1100 1110 0001 1001 0000 0010 0100 1110 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 0101 1100 1110 0001 1001 0000 0010 0100 1110 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 0101 1100 1110 0001 1001 0000 0010 0100 1110 0111 =


0010 0111 1011 0101 1100 1110 0001 1001 0000 0010 0100 1110 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 0101 1100 1110 0001 1001 0000 0010 0100 1110 0111


Decimal number -0.000 282 011 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0101 1100 1110 0001 1001 0000 0010 0100 1110 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