-0.000 282 031 8 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 031 8(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
-0.000 282 031 8(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:

|-0.000 282 031 8| = 0.000 282 031 8


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: 0.000 282 031 8.

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) 0.000 282 031 8 × 2 = 0 + 0.000 564 063 6;
  • 2) 0.000 564 063 6 × 2 = 0 + 0.001 128 127 2;
  • 3) 0.001 128 127 2 × 2 = 0 + 0.002 256 254 4;
  • 4) 0.002 256 254 4 × 2 = 0 + 0.004 512 508 8;
  • 5) 0.004 512 508 8 × 2 = 0 + 0.009 025 017 6;
  • 6) 0.009 025 017 6 × 2 = 0 + 0.018 050 035 2;
  • 7) 0.018 050 035 2 × 2 = 0 + 0.036 100 070 4;
  • 8) 0.036 100 070 4 × 2 = 0 + 0.072 200 140 8;
  • 9) 0.072 200 140 8 × 2 = 0 + 0.144 400 281 6;
  • 10) 0.144 400 281 6 × 2 = 0 + 0.288 800 563 2;
  • 11) 0.288 800 563 2 × 2 = 0 + 0.577 601 126 4;
  • 12) 0.577 601 126 4 × 2 = 1 + 0.155 202 252 8;
  • 13) 0.155 202 252 8 × 2 = 0 + 0.310 404 505 6;
  • 14) 0.310 404 505 6 × 2 = 0 + 0.620 809 011 2;
  • 15) 0.620 809 011 2 × 2 = 1 + 0.241 618 022 4;
  • 16) 0.241 618 022 4 × 2 = 0 + 0.483 236 044 8;
  • 17) 0.483 236 044 8 × 2 = 0 + 0.966 472 089 6;
  • 18) 0.966 472 089 6 × 2 = 1 + 0.932 944 179 2;
  • 19) 0.932 944 179 2 × 2 = 1 + 0.865 888 358 4;
  • 20) 0.865 888 358 4 × 2 = 1 + 0.731 776 716 8;
  • 21) 0.731 776 716 8 × 2 = 1 + 0.463 553 433 6;
  • 22) 0.463 553 433 6 × 2 = 0 + 0.927 106 867 2;
  • 23) 0.927 106 867 2 × 2 = 1 + 0.854 213 734 4;
  • 24) 0.854 213 734 4 × 2 = 1 + 0.708 427 468 8;
  • 25) 0.708 427 468 8 × 2 = 1 + 0.416 854 937 6;
  • 26) 0.416 854 937 6 × 2 = 0 + 0.833 709 875 2;
  • 27) 0.833 709 875 2 × 2 = 1 + 0.667 419 750 4;
  • 28) 0.667 419 750 4 × 2 = 1 + 0.334 839 500 8;
  • 29) 0.334 839 500 8 × 2 = 0 + 0.669 679 001 6;
  • 30) 0.669 679 001 6 × 2 = 1 + 0.339 358 003 2;
  • 31) 0.339 358 003 2 × 2 = 0 + 0.678 716 006 4;
  • 32) 0.678 716 006 4 × 2 = 1 + 0.357 432 012 8;
  • 33) 0.357 432 012 8 × 2 = 0 + 0.714 864 025 6;
  • 34) 0.714 864 025 6 × 2 = 1 + 0.429 728 051 2;
  • 35) 0.429 728 051 2 × 2 = 0 + 0.859 456 102 4;
  • 36) 0.859 456 102 4 × 2 = 1 + 0.718 912 204 8;
  • 37) 0.718 912 204 8 × 2 = 1 + 0.437 824 409 6;
  • 38) 0.437 824 409 6 × 2 = 0 + 0.875 648 819 2;
  • 39) 0.875 648 819 2 × 2 = 1 + 0.751 297 638 4;
  • 40) 0.751 297 638 4 × 2 = 1 + 0.502 595 276 8;
  • 41) 0.502 595 276 8 × 2 = 1 + 0.005 190 553 6;
  • 42) 0.005 190 553 6 × 2 = 0 + 0.010 381 107 2;
  • 43) 0.010 381 107 2 × 2 = 0 + 0.020 762 214 4;
  • 44) 0.020 762 214 4 × 2 = 0 + 0.041 524 428 8;
  • 45) 0.041 524 428 8 × 2 = 0 + 0.083 048 857 6;
  • 46) 0.083 048 857 6 × 2 = 0 + 0.166 097 715 2;
  • 47) 0.166 097 715 2 × 2 = 0 + 0.332 195 430 4;
  • 48) 0.332 195 430 4 × 2 = 0 + 0.664 390 860 8;
  • 49) 0.664 390 860 8 × 2 = 1 + 0.328 781 721 6;
  • 50) 0.328 781 721 6 × 2 = 0 + 0.657 563 443 2;
  • 51) 0.657 563 443 2 × 2 = 1 + 0.315 126 886 4;
  • 52) 0.315 126 886 4 × 2 = 0 + 0.630 253 772 8;
  • 53) 0.630 253 772 8 × 2 = 1 + 0.260 507 545 6;
  • 54) 0.260 507 545 6 × 2 = 0 + 0.521 015 091 2;
  • 55) 0.521 015 091 2 × 2 = 1 + 0.042 030 182 4;
  • 56) 0.042 030 182 4 × 2 = 0 + 0.084 060 364 8;
  • 57) 0.084 060 364 8 × 2 = 0 + 0.168 120 729 6;
  • 58) 0.168 120 729 6 × 2 = 0 + 0.336 241 459 2;
  • 59) 0.336 241 459 2 × 2 = 0 + 0.672 482 918 4;
  • 60) 0.672 482 918 4 × 2 = 1 + 0.344 965 836 8;
  • 61) 0.344 965 836 8 × 2 = 0 + 0.689 931 673 6;
  • 62) 0.689 931 673 6 × 2 = 1 + 0.379 863 347 2;
  • 63) 0.379 863 347 2 × 2 = 0 + 0.759 726 694 4;
  • 64) 0.759 726 694 4 × 2 = 1 + 0.519 453 388 8;

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:


0.000 282 031 8(10) =


0.0000 0000 0001 0010 0111 1011 1011 0101 0101 1011 1000 0000 1010 1010 0001 0101(2)

6. Positive number before normalization:

0.000 282 031 8(10) =


0.0000 0000 0001 0010 0111 1011 1011 0101 0101 1011 1000 0000 1010 1010 0001 0101(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:


0.000 282 031 8(10) =


0.0000 0000 0001 0010 0111 1011 1011 0101 0101 1011 1000 0000 1010 1010 0001 0101(2) =


0.0000 0000 0001 0010 0111 1011 1011 0101 0101 1011 1000 0000 1010 1010 0001 0101(2) × 20 =


1.0010 0111 1011 1011 0101 0101 1011 1000 0000 1010 1010 0001 0101(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 1011 0101 0101 1011 1000 0000 1010 1010 0001 0101


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 1011 0101 0101 1011 1000 0000 1010 1010 0001 0101 =


0010 0111 1011 1011 0101 0101 1011 1000 0000 1010 1010 0001 0101


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 1011 0101 0101 1011 1000 0000 1010 1010 0001 0101


Decimal number -0.000 282 031 8 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 1011 0101 0101 1011 1000 0000 1010 1010 0001 0101


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