-0.000 282 008 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 008 2(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
-0.000 282 008 2(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:

|-0.000 282 008 2| = 0.000 282 008 2


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: 0.000 282 008 2.

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) 0.000 282 008 2 × 2 = 0 + 0.000 564 016 4;
  • 2) 0.000 564 016 4 × 2 = 0 + 0.001 128 032 8;
  • 3) 0.001 128 032 8 × 2 = 0 + 0.002 256 065 6;
  • 4) 0.002 256 065 6 × 2 = 0 + 0.004 512 131 2;
  • 5) 0.004 512 131 2 × 2 = 0 + 0.009 024 262 4;
  • 6) 0.009 024 262 4 × 2 = 0 + 0.018 048 524 8;
  • 7) 0.018 048 524 8 × 2 = 0 + 0.036 097 049 6;
  • 8) 0.036 097 049 6 × 2 = 0 + 0.072 194 099 2;
  • 9) 0.072 194 099 2 × 2 = 0 + 0.144 388 198 4;
  • 10) 0.144 388 198 4 × 2 = 0 + 0.288 776 396 8;
  • 11) 0.288 776 396 8 × 2 = 0 + 0.577 552 793 6;
  • 12) 0.577 552 793 6 × 2 = 1 + 0.155 105 587 2;
  • 13) 0.155 105 587 2 × 2 = 0 + 0.310 211 174 4;
  • 14) 0.310 211 174 4 × 2 = 0 + 0.620 422 348 8;
  • 15) 0.620 422 348 8 × 2 = 1 + 0.240 844 697 6;
  • 16) 0.240 844 697 6 × 2 = 0 + 0.481 689 395 2;
  • 17) 0.481 689 395 2 × 2 = 0 + 0.963 378 790 4;
  • 18) 0.963 378 790 4 × 2 = 1 + 0.926 757 580 8;
  • 19) 0.926 757 580 8 × 2 = 1 + 0.853 515 161 6;
  • 20) 0.853 515 161 6 × 2 = 1 + 0.707 030 323 2;
  • 21) 0.707 030 323 2 × 2 = 1 + 0.414 060 646 4;
  • 22) 0.414 060 646 4 × 2 = 0 + 0.828 121 292 8;
  • 23) 0.828 121 292 8 × 2 = 1 + 0.656 242 585 6;
  • 24) 0.656 242 585 6 × 2 = 1 + 0.312 485 171 2;
  • 25) 0.312 485 171 2 × 2 = 0 + 0.624 970 342 4;
  • 26) 0.624 970 342 4 × 2 = 1 + 0.249 940 684 8;
  • 27) 0.249 940 684 8 × 2 = 0 + 0.499 881 369 6;
  • 28) 0.499 881 369 6 × 2 = 0 + 0.999 762 739 2;
  • 29) 0.999 762 739 2 × 2 = 1 + 0.999 525 478 4;
  • 30) 0.999 525 478 4 × 2 = 1 + 0.999 050 956 8;
  • 31) 0.999 050 956 8 × 2 = 1 + 0.998 101 913 6;
  • 32) 0.998 101 913 6 × 2 = 1 + 0.996 203 827 2;
  • 33) 0.996 203 827 2 × 2 = 1 + 0.992 407 654 4;
  • 34) 0.992 407 654 4 × 2 = 1 + 0.984 815 308 8;
  • 35) 0.984 815 308 8 × 2 = 1 + 0.969 630 617 6;
  • 36) 0.969 630 617 6 × 2 = 1 + 0.939 261 235 2;
  • 37) 0.939 261 235 2 × 2 = 1 + 0.878 522 470 4;
  • 38) 0.878 522 470 4 × 2 = 1 + 0.757 044 940 8;
  • 39) 0.757 044 940 8 × 2 = 1 + 0.514 089 881 6;
  • 40) 0.514 089 881 6 × 2 = 1 + 0.028 179 763 2;
  • 41) 0.028 179 763 2 × 2 = 0 + 0.056 359 526 4;
  • 42) 0.056 359 526 4 × 2 = 0 + 0.112 719 052 8;
  • 43) 0.112 719 052 8 × 2 = 0 + 0.225 438 105 6;
  • 44) 0.225 438 105 6 × 2 = 0 + 0.450 876 211 2;
  • 45) 0.450 876 211 2 × 2 = 0 + 0.901 752 422 4;
  • 46) 0.901 752 422 4 × 2 = 1 + 0.803 504 844 8;
  • 47) 0.803 504 844 8 × 2 = 1 + 0.607 009 689 6;
  • 48) 0.607 009 689 6 × 2 = 1 + 0.214 019 379 2;
  • 49) 0.214 019 379 2 × 2 = 0 + 0.428 038 758 4;
  • 50) 0.428 038 758 4 × 2 = 0 + 0.856 077 516 8;
  • 51) 0.856 077 516 8 × 2 = 1 + 0.712 155 033 6;
  • 52) 0.712 155 033 6 × 2 = 1 + 0.424 310 067 2;
  • 53) 0.424 310 067 2 × 2 = 0 + 0.848 620 134 4;
  • 54) 0.848 620 134 4 × 2 = 1 + 0.697 240 268 8;
  • 55) 0.697 240 268 8 × 2 = 1 + 0.394 480 537 6;
  • 56) 0.394 480 537 6 × 2 = 0 + 0.788 961 075 2;
  • 57) 0.788 961 075 2 × 2 = 1 + 0.577 922 150 4;
  • 58) 0.577 922 150 4 × 2 = 1 + 0.155 844 300 8;
  • 59) 0.155 844 300 8 × 2 = 0 + 0.311 688 601 6;
  • 60) 0.311 688 601 6 × 2 = 0 + 0.623 377 203 2;
  • 61) 0.623 377 203 2 × 2 = 1 + 0.246 754 406 4;
  • 62) 0.246 754 406 4 × 2 = 0 + 0.493 508 812 8;
  • 63) 0.493 508 812 8 × 2 = 0 + 0.987 017 625 6;
  • 64) 0.987 017 625 6 × 2 = 1 + 0.974 035 251 2;

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:


0.000 282 008 2(10) =


0.0000 0000 0001 0010 0111 1011 0100 1111 1111 1111 0000 0111 0011 0110 1100 1001(2)

6. Positive number before normalization:

0.000 282 008 2(10) =


0.0000 0000 0001 0010 0111 1011 0100 1111 1111 1111 0000 0111 0011 0110 1100 1001(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:


0.000 282 008 2(10) =


0.0000 0000 0001 0010 0111 1011 0100 1111 1111 1111 0000 0111 0011 0110 1100 1001(2) =


0.0000 0000 0001 0010 0111 1011 0100 1111 1111 1111 0000 0111 0011 0110 1100 1001(2) × 20 =


1.0010 0111 1011 0100 1111 1111 1111 0000 0111 0011 0110 1100 1001(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 0100 1111 1111 1111 0000 0111 0011 0110 1100 1001


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 0100 1111 1111 1111 0000 0111 0011 0110 1100 1001 =


0010 0111 1011 0100 1111 1111 1111 0000 0111 0011 0110 1100 1001


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 0100 1111 1111 1111 0000 0111 0011 0110 1100 1001


Decimal number -0.000 282 008 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 1111 1111 1111 0000 0111 0011 0110 1100 1001


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