-0.000 282 015 4 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 015 4(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
-0.000 282 015 4(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:

|-0.000 282 015 4| = 0.000 282 015 4


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: 0.000 282 015 4.

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) 0.000 282 015 4 × 2 = 0 + 0.000 564 030 8;
  • 2) 0.000 564 030 8 × 2 = 0 + 0.001 128 061 6;
  • 3) 0.001 128 061 6 × 2 = 0 + 0.002 256 123 2;
  • 4) 0.002 256 123 2 × 2 = 0 + 0.004 512 246 4;
  • 5) 0.004 512 246 4 × 2 = 0 + 0.009 024 492 8;
  • 6) 0.009 024 492 8 × 2 = 0 + 0.018 048 985 6;
  • 7) 0.018 048 985 6 × 2 = 0 + 0.036 097 971 2;
  • 8) 0.036 097 971 2 × 2 = 0 + 0.072 195 942 4;
  • 9) 0.072 195 942 4 × 2 = 0 + 0.144 391 884 8;
  • 10) 0.144 391 884 8 × 2 = 0 + 0.288 783 769 6;
  • 11) 0.288 783 769 6 × 2 = 0 + 0.577 567 539 2;
  • 12) 0.577 567 539 2 × 2 = 1 + 0.155 135 078 4;
  • 13) 0.155 135 078 4 × 2 = 0 + 0.310 270 156 8;
  • 14) 0.310 270 156 8 × 2 = 0 + 0.620 540 313 6;
  • 15) 0.620 540 313 6 × 2 = 1 + 0.241 080 627 2;
  • 16) 0.241 080 627 2 × 2 = 0 + 0.482 161 254 4;
  • 17) 0.482 161 254 4 × 2 = 0 + 0.964 322 508 8;
  • 18) 0.964 322 508 8 × 2 = 1 + 0.928 645 017 6;
  • 19) 0.928 645 017 6 × 2 = 1 + 0.857 290 035 2;
  • 20) 0.857 290 035 2 × 2 = 1 + 0.714 580 070 4;
  • 21) 0.714 580 070 4 × 2 = 1 + 0.429 160 140 8;
  • 22) 0.429 160 140 8 × 2 = 0 + 0.858 320 281 6;
  • 23) 0.858 320 281 6 × 2 = 1 + 0.716 640 563 2;
  • 24) 0.716 640 563 2 × 2 = 1 + 0.433 281 126 4;
  • 25) 0.433 281 126 4 × 2 = 0 + 0.866 562 252 8;
  • 26) 0.866 562 252 8 × 2 = 1 + 0.733 124 505 6;
  • 27) 0.733 124 505 6 × 2 = 1 + 0.466 249 011 2;
  • 28) 0.466 249 011 2 × 2 = 0 + 0.932 498 022 4;
  • 29) 0.932 498 022 4 × 2 = 1 + 0.864 996 044 8;
  • 30) 0.864 996 044 8 × 2 = 1 + 0.729 992 089 6;
  • 31) 0.729 992 089 6 × 2 = 1 + 0.459 984 179 2;
  • 32) 0.459 984 179 2 × 2 = 0 + 0.919 968 358 4;
  • 33) 0.919 968 358 4 × 2 = 1 + 0.839 936 716 8;
  • 34) 0.839 936 716 8 × 2 = 1 + 0.679 873 433 6;
  • 35) 0.679 873 433 6 × 2 = 1 + 0.359 746 867 2;
  • 36) 0.359 746 867 2 × 2 = 0 + 0.719 493 734 4;
  • 37) 0.719 493 734 4 × 2 = 1 + 0.438 987 468 8;
  • 38) 0.438 987 468 8 × 2 = 0 + 0.877 974 937 6;
  • 39) 0.877 974 937 6 × 2 = 1 + 0.755 949 875 2;
  • 40) 0.755 949 875 2 × 2 = 1 + 0.511 899 750 4;
  • 41) 0.511 899 750 4 × 2 = 1 + 0.023 799 500 8;
  • 42) 0.023 799 500 8 × 2 = 0 + 0.047 599 001 6;
  • 43) 0.047 599 001 6 × 2 = 0 + 0.095 198 003 2;
  • 44) 0.095 198 003 2 × 2 = 0 + 0.190 396 006 4;
  • 45) 0.190 396 006 4 × 2 = 0 + 0.380 792 012 8;
  • 46) 0.380 792 012 8 × 2 = 0 + 0.761 584 025 6;
  • 47) 0.761 584 025 6 × 2 = 1 + 0.523 168 051 2;
  • 48) 0.523 168 051 2 × 2 = 1 + 0.046 336 102 4;
  • 49) 0.046 336 102 4 × 2 = 0 + 0.092 672 204 8;
  • 50) 0.092 672 204 8 × 2 = 0 + 0.185 344 409 6;
  • 51) 0.185 344 409 6 × 2 = 0 + 0.370 688 819 2;
  • 52) 0.370 688 819 2 × 2 = 0 + 0.741 377 638 4;
  • 53) 0.741 377 638 4 × 2 = 1 + 0.482 755 276 8;
  • 54) 0.482 755 276 8 × 2 = 0 + 0.965 510 553 6;
  • 55) 0.965 510 553 6 × 2 = 1 + 0.931 021 107 2;
  • 56) 0.931 021 107 2 × 2 = 1 + 0.862 042 214 4;
  • 57) 0.862 042 214 4 × 2 = 1 + 0.724 084 428 8;
  • 58) 0.724 084 428 8 × 2 = 1 + 0.448 168 857 6;
  • 59) 0.448 168 857 6 × 2 = 0 + 0.896 337 715 2;
  • 60) 0.896 337 715 2 × 2 = 1 + 0.792 675 430 4;
  • 61) 0.792 675 430 4 × 2 = 1 + 0.585 350 860 8;
  • 62) 0.585 350 860 8 × 2 = 1 + 0.170 701 721 6;
  • 63) 0.170 701 721 6 × 2 = 0 + 0.341 403 443 2;
  • 64) 0.341 403 443 2 × 2 = 0 + 0.682 806 886 4;

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:


0.000 282 015 4(10) =


0.0000 0000 0001 0010 0111 1011 0110 1110 1110 1011 1000 0011 0000 1011 1101 1100(2)

6. Positive number before normalization:

0.000 282 015 4(10) =


0.0000 0000 0001 0010 0111 1011 0110 1110 1110 1011 1000 0011 0000 1011 1101 1100(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:


0.000 282 015 4(10) =


0.0000 0000 0001 0010 0111 1011 0110 1110 1110 1011 1000 0011 0000 1011 1101 1100(2) =


0.0000 0000 0001 0010 0111 1011 0110 1110 1110 1011 1000 0011 0000 1011 1101 1100(2) × 20 =


1.0010 0111 1011 0110 1110 1110 1011 1000 0011 0000 1011 1101 1100(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 0110 1110 1110 1011 1000 0011 0000 1011 1101 1100


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 0110 1110 1110 1011 1000 0011 0000 1011 1101 1100 =


0010 0111 1011 0110 1110 1110 1011 1000 0011 0000 1011 1101 1100


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 0110 1110 1110 1011 1000 0011 0000 1011 1101 1100


Decimal number -0.000 282 015 4 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0110 1110 1110 1011 1000 0011 0000 1011 1101 1100


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