-0.000 282 014 6 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 014 6(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
-0.000 282 014 6(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:

|-0.000 282 014 6| = 0.000 282 014 6


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: 0.000 282 014 6.

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) 0.000 282 014 6 × 2 = 0 + 0.000 564 029 2;
  • 2) 0.000 564 029 2 × 2 = 0 + 0.001 128 058 4;
  • 3) 0.001 128 058 4 × 2 = 0 + 0.002 256 116 8;
  • 4) 0.002 256 116 8 × 2 = 0 + 0.004 512 233 6;
  • 5) 0.004 512 233 6 × 2 = 0 + 0.009 024 467 2;
  • 6) 0.009 024 467 2 × 2 = 0 + 0.018 048 934 4;
  • 7) 0.018 048 934 4 × 2 = 0 + 0.036 097 868 8;
  • 8) 0.036 097 868 8 × 2 = 0 + 0.072 195 737 6;
  • 9) 0.072 195 737 6 × 2 = 0 + 0.144 391 475 2;
  • 10) 0.144 391 475 2 × 2 = 0 + 0.288 782 950 4;
  • 11) 0.288 782 950 4 × 2 = 0 + 0.577 565 900 8;
  • 12) 0.577 565 900 8 × 2 = 1 + 0.155 131 801 6;
  • 13) 0.155 131 801 6 × 2 = 0 + 0.310 263 603 2;
  • 14) 0.310 263 603 2 × 2 = 0 + 0.620 527 206 4;
  • 15) 0.620 527 206 4 × 2 = 1 + 0.241 054 412 8;
  • 16) 0.241 054 412 8 × 2 = 0 + 0.482 108 825 6;
  • 17) 0.482 108 825 6 × 2 = 0 + 0.964 217 651 2;
  • 18) 0.964 217 651 2 × 2 = 1 + 0.928 435 302 4;
  • 19) 0.928 435 302 4 × 2 = 1 + 0.856 870 604 8;
  • 20) 0.856 870 604 8 × 2 = 1 + 0.713 741 209 6;
  • 21) 0.713 741 209 6 × 2 = 1 + 0.427 482 419 2;
  • 22) 0.427 482 419 2 × 2 = 0 + 0.854 964 838 4;
  • 23) 0.854 964 838 4 × 2 = 1 + 0.709 929 676 8;
  • 24) 0.709 929 676 8 × 2 = 1 + 0.419 859 353 6;
  • 25) 0.419 859 353 6 × 2 = 0 + 0.839 718 707 2;
  • 26) 0.839 718 707 2 × 2 = 1 + 0.679 437 414 4;
  • 27) 0.679 437 414 4 × 2 = 1 + 0.358 874 828 8;
  • 28) 0.358 874 828 8 × 2 = 0 + 0.717 749 657 6;
  • 29) 0.717 749 657 6 × 2 = 1 + 0.435 499 315 2;
  • 30) 0.435 499 315 2 × 2 = 0 + 0.870 998 630 4;
  • 31) 0.870 998 630 4 × 2 = 1 + 0.741 997 260 8;
  • 32) 0.741 997 260 8 × 2 = 1 + 0.483 994 521 6;
  • 33) 0.483 994 521 6 × 2 = 0 + 0.967 989 043 2;
  • 34) 0.967 989 043 2 × 2 = 1 + 0.935 978 086 4;
  • 35) 0.935 978 086 4 × 2 = 1 + 0.871 956 172 8;
  • 36) 0.871 956 172 8 × 2 = 1 + 0.743 912 345 6;
  • 37) 0.743 912 345 6 × 2 = 1 + 0.487 824 691 2;
  • 38) 0.487 824 691 2 × 2 = 0 + 0.975 649 382 4;
  • 39) 0.975 649 382 4 × 2 = 1 + 0.951 298 764 8;
  • 40) 0.951 298 764 8 × 2 = 1 + 0.902 597 529 6;
  • 41) 0.902 597 529 6 × 2 = 1 + 0.805 195 059 2;
  • 42) 0.805 195 059 2 × 2 = 1 + 0.610 390 118 4;
  • 43) 0.610 390 118 4 × 2 = 1 + 0.220 780 236 8;
  • 44) 0.220 780 236 8 × 2 = 0 + 0.441 560 473 6;
  • 45) 0.441 560 473 6 × 2 = 0 + 0.883 120 947 2;
  • 46) 0.883 120 947 2 × 2 = 1 + 0.766 241 894 4;
  • 47) 0.766 241 894 4 × 2 = 1 + 0.532 483 788 8;
  • 48) 0.532 483 788 8 × 2 = 1 + 0.064 967 577 6;
  • 49) 0.064 967 577 6 × 2 = 0 + 0.129 935 155 2;
  • 50) 0.129 935 155 2 × 2 = 0 + 0.259 870 310 4;
  • 51) 0.259 870 310 4 × 2 = 0 + 0.519 740 620 8;
  • 52) 0.519 740 620 8 × 2 = 1 + 0.039 481 241 6;
  • 53) 0.039 481 241 6 × 2 = 0 + 0.078 962 483 2;
  • 54) 0.078 962 483 2 × 2 = 0 + 0.157 924 966 4;
  • 55) 0.157 924 966 4 × 2 = 0 + 0.315 849 932 8;
  • 56) 0.315 849 932 8 × 2 = 0 + 0.631 699 865 6;
  • 57) 0.631 699 865 6 × 2 = 1 + 0.263 399 731 2;
  • 58) 0.263 399 731 2 × 2 = 0 + 0.526 799 462 4;
  • 59) 0.526 799 462 4 × 2 = 1 + 0.053 598 924 8;
  • 60) 0.053 598 924 8 × 2 = 0 + 0.107 197 849 6;
  • 61) 0.107 197 849 6 × 2 = 0 + 0.214 395 699 2;
  • 62) 0.214 395 699 2 × 2 = 0 + 0.428 791 398 4;
  • 63) 0.428 791 398 4 × 2 = 0 + 0.857 582 796 8;
  • 64) 0.857 582 796 8 × 2 = 1 + 0.715 165 593 6;

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:


0.000 282 014 6(10) =


0.0000 0000 0001 0010 0111 1011 0110 1011 0111 1011 1110 0111 0001 0000 1010 0001(2)

6. Positive number before normalization:

0.000 282 014 6(10) =


0.0000 0000 0001 0010 0111 1011 0110 1011 0111 1011 1110 0111 0001 0000 1010 0001(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:


0.000 282 014 6(10) =


0.0000 0000 0001 0010 0111 1011 0110 1011 0111 1011 1110 0111 0001 0000 1010 0001(2) =


0.0000 0000 0001 0010 0111 1011 0110 1011 0111 1011 1110 0111 0001 0000 1010 0001(2) × 20 =


1.0010 0111 1011 0110 1011 0111 1011 1110 0111 0001 0000 1010 0001(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 1011 0111 1011 1110 0111 0001 0000 1010 0001


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 1011 0111 1011 1110 0111 0001 0000 1010 0001 =


0010 0111 1011 0110 1011 0111 1011 1110 0111 0001 0000 1010 0001


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 1011 0111 1011 1110 0111 0001 0000 1010 0001


Decimal number -0.000 282 014 6 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0110 1011 0111 1011 1110 0111 0001 0000 1010 0001


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