-0.000 282 027 1 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 027 1(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
-0.000 282 027 1(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:

|-0.000 282 027 1| = 0.000 282 027 1


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: 0.000 282 027 1.

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) 0.000 282 027 1 × 2 = 0 + 0.000 564 054 2;
  • 2) 0.000 564 054 2 × 2 = 0 + 0.001 128 108 4;
  • 3) 0.001 128 108 4 × 2 = 0 + 0.002 256 216 8;
  • 4) 0.002 256 216 8 × 2 = 0 + 0.004 512 433 6;
  • 5) 0.004 512 433 6 × 2 = 0 + 0.009 024 867 2;
  • 6) 0.009 024 867 2 × 2 = 0 + 0.018 049 734 4;
  • 7) 0.018 049 734 4 × 2 = 0 + 0.036 099 468 8;
  • 8) 0.036 099 468 8 × 2 = 0 + 0.072 198 937 6;
  • 9) 0.072 198 937 6 × 2 = 0 + 0.144 397 875 2;
  • 10) 0.144 397 875 2 × 2 = 0 + 0.288 795 750 4;
  • 11) 0.288 795 750 4 × 2 = 0 + 0.577 591 500 8;
  • 12) 0.577 591 500 8 × 2 = 1 + 0.155 183 001 6;
  • 13) 0.155 183 001 6 × 2 = 0 + 0.310 366 003 2;
  • 14) 0.310 366 003 2 × 2 = 0 + 0.620 732 006 4;
  • 15) 0.620 732 006 4 × 2 = 1 + 0.241 464 012 8;
  • 16) 0.241 464 012 8 × 2 = 0 + 0.482 928 025 6;
  • 17) 0.482 928 025 6 × 2 = 0 + 0.965 856 051 2;
  • 18) 0.965 856 051 2 × 2 = 1 + 0.931 712 102 4;
  • 19) 0.931 712 102 4 × 2 = 1 + 0.863 424 204 8;
  • 20) 0.863 424 204 8 × 2 = 1 + 0.726 848 409 6;
  • 21) 0.726 848 409 6 × 2 = 1 + 0.453 696 819 2;
  • 22) 0.453 696 819 2 × 2 = 0 + 0.907 393 638 4;
  • 23) 0.907 393 638 4 × 2 = 1 + 0.814 787 276 8;
  • 24) 0.814 787 276 8 × 2 = 1 + 0.629 574 553 6;
  • 25) 0.629 574 553 6 × 2 = 1 + 0.259 149 107 2;
  • 26) 0.259 149 107 2 × 2 = 0 + 0.518 298 214 4;
  • 27) 0.518 298 214 4 × 2 = 1 + 0.036 596 428 8;
  • 28) 0.036 596 428 8 × 2 = 0 + 0.073 192 857 6;
  • 29) 0.073 192 857 6 × 2 = 0 + 0.146 385 715 2;
  • 30) 0.146 385 715 2 × 2 = 0 + 0.292 771 430 4;
  • 31) 0.292 771 430 4 × 2 = 0 + 0.585 542 860 8;
  • 32) 0.585 542 860 8 × 2 = 1 + 0.171 085 721 6;
  • 33) 0.171 085 721 6 × 2 = 0 + 0.342 171 443 2;
  • 34) 0.342 171 443 2 × 2 = 0 + 0.684 342 886 4;
  • 35) 0.684 342 886 4 × 2 = 1 + 0.368 685 772 8;
  • 36) 0.368 685 772 8 × 2 = 0 + 0.737 371 545 6;
  • 37) 0.737 371 545 6 × 2 = 1 + 0.474 743 091 2;
  • 38) 0.474 743 091 2 × 2 = 0 + 0.949 486 182 4;
  • 39) 0.949 486 182 4 × 2 = 1 + 0.898 972 364 8;
  • 40) 0.898 972 364 8 × 2 = 1 + 0.797 944 729 6;
  • 41) 0.797 944 729 6 × 2 = 1 + 0.595 889 459 2;
  • 42) 0.595 889 459 2 × 2 = 1 + 0.191 778 918 4;
  • 43) 0.191 778 918 4 × 2 = 0 + 0.383 557 836 8;
  • 44) 0.383 557 836 8 × 2 = 0 + 0.767 115 673 6;
  • 45) 0.767 115 673 6 × 2 = 1 + 0.534 231 347 2;
  • 46) 0.534 231 347 2 × 2 = 1 + 0.068 462 694 4;
  • 47) 0.068 462 694 4 × 2 = 0 + 0.136 925 388 8;
  • 48) 0.136 925 388 8 × 2 = 0 + 0.273 850 777 6;
  • 49) 0.273 850 777 6 × 2 = 0 + 0.547 701 555 2;
  • 50) 0.547 701 555 2 × 2 = 1 + 0.095 403 110 4;
  • 51) 0.095 403 110 4 × 2 = 0 + 0.190 806 220 8;
  • 52) 0.190 806 220 8 × 2 = 0 + 0.381 612 441 6;
  • 53) 0.381 612 441 6 × 2 = 0 + 0.763 224 883 2;
  • 54) 0.763 224 883 2 × 2 = 1 + 0.526 449 766 4;
  • 55) 0.526 449 766 4 × 2 = 1 + 0.052 899 532 8;
  • 56) 0.052 899 532 8 × 2 = 0 + 0.105 799 065 6;
  • 57) 0.105 799 065 6 × 2 = 0 + 0.211 598 131 2;
  • 58) 0.211 598 131 2 × 2 = 0 + 0.423 196 262 4;
  • 59) 0.423 196 262 4 × 2 = 0 + 0.846 392 524 8;
  • 60) 0.846 392 524 8 × 2 = 1 + 0.692 785 049 6;
  • 61) 0.692 785 049 6 × 2 = 1 + 0.385 570 099 2;
  • 62) 0.385 570 099 2 × 2 = 0 + 0.771 140 198 4;
  • 63) 0.771 140 198 4 × 2 = 1 + 0.542 280 396 8;
  • 64) 0.542 280 396 8 × 2 = 1 + 0.084 560 793 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:


0.000 282 027 1(10) =


0.0000 0000 0001 0010 0111 1011 1010 0001 0010 1011 1100 1100 0100 0110 0001 1011(2)

6. Positive number before normalization:

0.000 282 027 1(10) =


0.0000 0000 0001 0010 0111 1011 1010 0001 0010 1011 1100 1100 0100 0110 0001 1011(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:


0.000 282 027 1(10) =


0.0000 0000 0001 0010 0111 1011 1010 0001 0010 1011 1100 1100 0100 0110 0001 1011(2) =


0.0000 0000 0001 0010 0111 1011 1010 0001 0010 1011 1100 1100 0100 0110 0001 1011(2) × 20 =


1.0010 0111 1011 1010 0001 0010 1011 1100 1100 0100 0110 0001 1011(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 1010 0001 0010 1011 1100 1100 0100 0110 0001 1011


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 1010 0001 0010 1011 1100 1100 0100 0110 0001 1011 =


0010 0111 1011 1010 0001 0010 1011 1100 1100 0100 0110 0001 1011


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 1010 0001 0010 1011 1100 1100 0100 0110 0001 1011


Decimal number -0.000 282 027 1 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 1010 0001 0010 1011 1100 1100 0100 0110 0001 1011


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