-0.000 282 026 9 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 026 9(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
-0.000 282 026 9(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:

|-0.000 282 026 9| = 0.000 282 026 9


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: 0.000 282 026 9.

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) 0.000 282 026 9 × 2 = 0 + 0.000 564 053 8;
  • 2) 0.000 564 053 8 × 2 = 0 + 0.001 128 107 6;
  • 3) 0.001 128 107 6 × 2 = 0 + 0.002 256 215 2;
  • 4) 0.002 256 215 2 × 2 = 0 + 0.004 512 430 4;
  • 5) 0.004 512 430 4 × 2 = 0 + 0.009 024 860 8;
  • 6) 0.009 024 860 8 × 2 = 0 + 0.018 049 721 6;
  • 7) 0.018 049 721 6 × 2 = 0 + 0.036 099 443 2;
  • 8) 0.036 099 443 2 × 2 = 0 + 0.072 198 886 4;
  • 9) 0.072 198 886 4 × 2 = 0 + 0.144 397 772 8;
  • 10) 0.144 397 772 8 × 2 = 0 + 0.288 795 545 6;
  • 11) 0.288 795 545 6 × 2 = 0 + 0.577 591 091 2;
  • 12) 0.577 591 091 2 × 2 = 1 + 0.155 182 182 4;
  • 13) 0.155 182 182 4 × 2 = 0 + 0.310 364 364 8;
  • 14) 0.310 364 364 8 × 2 = 0 + 0.620 728 729 6;
  • 15) 0.620 728 729 6 × 2 = 1 + 0.241 457 459 2;
  • 16) 0.241 457 459 2 × 2 = 0 + 0.482 914 918 4;
  • 17) 0.482 914 918 4 × 2 = 0 + 0.965 829 836 8;
  • 18) 0.965 829 836 8 × 2 = 1 + 0.931 659 673 6;
  • 19) 0.931 659 673 6 × 2 = 1 + 0.863 319 347 2;
  • 20) 0.863 319 347 2 × 2 = 1 + 0.726 638 694 4;
  • 21) 0.726 638 694 4 × 2 = 1 + 0.453 277 388 8;
  • 22) 0.453 277 388 8 × 2 = 0 + 0.906 554 777 6;
  • 23) 0.906 554 777 6 × 2 = 1 + 0.813 109 555 2;
  • 24) 0.813 109 555 2 × 2 = 1 + 0.626 219 110 4;
  • 25) 0.626 219 110 4 × 2 = 1 + 0.252 438 220 8;
  • 26) 0.252 438 220 8 × 2 = 0 + 0.504 876 441 6;
  • 27) 0.504 876 441 6 × 2 = 1 + 0.009 752 883 2;
  • 28) 0.009 752 883 2 × 2 = 0 + 0.019 505 766 4;
  • 29) 0.019 505 766 4 × 2 = 0 + 0.039 011 532 8;
  • 30) 0.039 011 532 8 × 2 = 0 + 0.078 023 065 6;
  • 31) 0.078 023 065 6 × 2 = 0 + 0.156 046 131 2;
  • 32) 0.156 046 131 2 × 2 = 0 + 0.312 092 262 4;
  • 33) 0.312 092 262 4 × 2 = 0 + 0.624 184 524 8;
  • 34) 0.624 184 524 8 × 2 = 1 + 0.248 369 049 6;
  • 35) 0.248 369 049 6 × 2 = 0 + 0.496 738 099 2;
  • 36) 0.496 738 099 2 × 2 = 0 + 0.993 476 198 4;
  • 37) 0.993 476 198 4 × 2 = 1 + 0.986 952 396 8;
  • 38) 0.986 952 396 8 × 2 = 1 + 0.973 904 793 6;
  • 39) 0.973 904 793 6 × 2 = 1 + 0.947 809 587 2;
  • 40) 0.947 809 587 2 × 2 = 1 + 0.895 619 174 4;
  • 41) 0.895 619 174 4 × 2 = 1 + 0.791 238 348 8;
  • 42) 0.791 238 348 8 × 2 = 1 + 0.582 476 697 6;
  • 43) 0.582 476 697 6 × 2 = 1 + 0.164 953 395 2;
  • 44) 0.164 953 395 2 × 2 = 0 + 0.329 906 790 4;
  • 45) 0.329 906 790 4 × 2 = 0 + 0.659 813 580 8;
  • 46) 0.659 813 580 8 × 2 = 1 + 0.319 627 161 6;
  • 47) 0.319 627 161 6 × 2 = 0 + 0.639 254 323 2;
  • 48) 0.639 254 323 2 × 2 = 1 + 0.278 508 646 4;
  • 49) 0.278 508 646 4 × 2 = 0 + 0.557 017 292 8;
  • 50) 0.557 017 292 8 × 2 = 1 + 0.114 034 585 6;
  • 51) 0.114 034 585 6 × 2 = 0 + 0.228 069 171 2;
  • 52) 0.228 069 171 2 × 2 = 0 + 0.456 138 342 4;
  • 53) 0.456 138 342 4 × 2 = 0 + 0.912 276 684 8;
  • 54) 0.912 276 684 8 × 2 = 1 + 0.824 553 369 6;
  • 55) 0.824 553 369 6 × 2 = 1 + 0.649 106 739 2;
  • 56) 0.649 106 739 2 × 2 = 1 + 0.298 213 478 4;
  • 57) 0.298 213 478 4 × 2 = 0 + 0.596 426 956 8;
  • 58) 0.596 426 956 8 × 2 = 1 + 0.192 853 913 6;
  • 59) 0.192 853 913 6 × 2 = 0 + 0.385 707 827 2;
  • 60) 0.385 707 827 2 × 2 = 0 + 0.771 415 654 4;
  • 61) 0.771 415 654 4 × 2 = 1 + 0.542 831 308 8;
  • 62) 0.542 831 308 8 × 2 = 1 + 0.085 662 617 6;
  • 63) 0.085 662 617 6 × 2 = 0 + 0.171 325 235 2;
  • 64) 0.171 325 235 2 × 2 = 0 + 0.342 650 470 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:


0.000 282 026 9(10) =


0.0000 0000 0001 0010 0111 1011 1010 0000 0100 1111 1110 0101 0100 0111 0100 1100(2)

6. Positive number before normalization:

0.000 282 026 9(10) =


0.0000 0000 0001 0010 0111 1011 1010 0000 0100 1111 1110 0101 0100 0111 0100 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:


0.000 282 026 9(10) =


0.0000 0000 0001 0010 0111 1011 1010 0000 0100 1111 1110 0101 0100 0111 0100 1100(2) =


0.0000 0000 0001 0010 0111 1011 1010 0000 0100 1111 1110 0101 0100 0111 0100 1100(2) × 20 =


1.0010 0111 1011 1010 0000 0100 1111 1110 0101 0100 0111 0100 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 1010 0000 0100 1111 1110 0101 0100 0111 0100 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 1010 0000 0100 1111 1110 0101 0100 0111 0100 1100 =


0010 0111 1011 1010 0000 0100 1111 1110 0101 0100 0111 0100 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 1010 0000 0100 1111 1110 0101 0100 0111 0100 1100


Decimal number -0.000 282 026 9 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 1010 0000 0100 1111 1110 0101 0100 0111 0100 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