-0.000 281 989 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 281 989 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
-0.000 281 989 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:

|-0.000 281 989 2| = 0.000 281 989 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: 0.000 281 989 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) 0.000 281 989 2 × 2 = 0 + 0.000 563 978 4;
  • 2) 0.000 563 978 4 × 2 = 0 + 0.001 127 956 8;
  • 3) 0.001 127 956 8 × 2 = 0 + 0.002 255 913 6;
  • 4) 0.002 255 913 6 × 2 = 0 + 0.004 511 827 2;
  • 5) 0.004 511 827 2 × 2 = 0 + 0.009 023 654 4;
  • 6) 0.009 023 654 4 × 2 = 0 + 0.018 047 308 8;
  • 7) 0.018 047 308 8 × 2 = 0 + 0.036 094 617 6;
  • 8) 0.036 094 617 6 × 2 = 0 + 0.072 189 235 2;
  • 9) 0.072 189 235 2 × 2 = 0 + 0.144 378 470 4;
  • 10) 0.144 378 470 4 × 2 = 0 + 0.288 756 940 8;
  • 11) 0.288 756 940 8 × 2 = 0 + 0.577 513 881 6;
  • 12) 0.577 513 881 6 × 2 = 1 + 0.155 027 763 2;
  • 13) 0.155 027 763 2 × 2 = 0 + 0.310 055 526 4;
  • 14) 0.310 055 526 4 × 2 = 0 + 0.620 111 052 8;
  • 15) 0.620 111 052 8 × 2 = 1 + 0.240 222 105 6;
  • 16) 0.240 222 105 6 × 2 = 0 + 0.480 444 211 2;
  • 17) 0.480 444 211 2 × 2 = 0 + 0.960 888 422 4;
  • 18) 0.960 888 422 4 × 2 = 1 + 0.921 776 844 8;
  • 19) 0.921 776 844 8 × 2 = 1 + 0.843 553 689 6;
  • 20) 0.843 553 689 6 × 2 = 1 + 0.687 107 379 2;
  • 21) 0.687 107 379 2 × 2 = 1 + 0.374 214 758 4;
  • 22) 0.374 214 758 4 × 2 = 0 + 0.748 429 516 8;
  • 23) 0.748 429 516 8 × 2 = 1 + 0.496 859 033 6;
  • 24) 0.496 859 033 6 × 2 = 0 + 0.993 718 067 2;
  • 25) 0.993 718 067 2 × 2 = 1 + 0.987 436 134 4;
  • 26) 0.987 436 134 4 × 2 = 1 + 0.974 872 268 8;
  • 27) 0.974 872 268 8 × 2 = 1 + 0.949 744 537 6;
  • 28) 0.949 744 537 6 × 2 = 1 + 0.899 489 075 2;
  • 29) 0.899 489 075 2 × 2 = 1 + 0.798 978 150 4;
  • 30) 0.798 978 150 4 × 2 = 1 + 0.597 956 300 8;
  • 31) 0.597 956 300 8 × 2 = 1 + 0.195 912 601 6;
  • 32) 0.195 912 601 6 × 2 = 0 + 0.391 825 203 2;
  • 33) 0.391 825 203 2 × 2 = 0 + 0.783 650 406 4;
  • 34) 0.783 650 406 4 × 2 = 1 + 0.567 300 812 8;
  • 35) 0.567 300 812 8 × 2 = 1 + 0.134 601 625 6;
  • 36) 0.134 601 625 6 × 2 = 0 + 0.269 203 251 2;
  • 37) 0.269 203 251 2 × 2 = 0 + 0.538 406 502 4;
  • 38) 0.538 406 502 4 × 2 = 1 + 0.076 813 004 8;
  • 39) 0.076 813 004 8 × 2 = 0 + 0.153 626 009 6;
  • 40) 0.153 626 009 6 × 2 = 0 + 0.307 252 019 2;
  • 41) 0.307 252 019 2 × 2 = 0 + 0.614 504 038 4;
  • 42) 0.614 504 038 4 × 2 = 1 + 0.229 008 076 8;
  • 43) 0.229 008 076 8 × 2 = 0 + 0.458 016 153 6;
  • 44) 0.458 016 153 6 × 2 = 0 + 0.916 032 307 2;
  • 45) 0.916 032 307 2 × 2 = 1 + 0.832 064 614 4;
  • 46) 0.832 064 614 4 × 2 = 1 + 0.664 129 228 8;
  • 47) 0.664 129 228 8 × 2 = 1 + 0.328 258 457 6;
  • 48) 0.328 258 457 6 × 2 = 0 + 0.656 516 915 2;
  • 49) 0.656 516 915 2 × 2 = 1 + 0.313 033 830 4;
  • 50) 0.313 033 830 4 × 2 = 0 + 0.626 067 660 8;
  • 51) 0.626 067 660 8 × 2 = 1 + 0.252 135 321 6;
  • 52) 0.252 135 321 6 × 2 = 0 + 0.504 270 643 2;
  • 53) 0.504 270 643 2 × 2 = 1 + 0.008 541 286 4;
  • 54) 0.008 541 286 4 × 2 = 0 + 0.017 082 572 8;
  • 55) 0.017 082 572 8 × 2 = 0 + 0.034 165 145 6;
  • 56) 0.034 165 145 6 × 2 = 0 + 0.068 330 291 2;
  • 57) 0.068 330 291 2 × 2 = 0 + 0.136 660 582 4;
  • 58) 0.136 660 582 4 × 2 = 0 + 0.273 321 164 8;
  • 59) 0.273 321 164 8 × 2 = 0 + 0.546 642 329 6;
  • 60) 0.546 642 329 6 × 2 = 1 + 0.093 284 659 2;
  • 61) 0.093 284 659 2 × 2 = 0 + 0.186 569 318 4;
  • 62) 0.186 569 318 4 × 2 = 0 + 0.373 138 636 8;
  • 63) 0.373 138 636 8 × 2 = 0 + 0.746 277 273 6;
  • 64) 0.746 277 273 6 × 2 = 1 + 0.492 554 547 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:


0.000 281 989 2(10) =


0.0000 0000 0001 0010 0111 1010 1111 1110 0110 0100 0100 1110 1010 1000 0001 0001(2)

6. Positive number before normalization:

0.000 281 989 2(10) =


0.0000 0000 0001 0010 0111 1010 1111 1110 0110 0100 0100 1110 1010 1000 0001 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:


0.000 281 989 2(10) =


0.0000 0000 0001 0010 0111 1010 1111 1110 0110 0100 0100 1110 1010 1000 0001 0001(2) =


0.0000 0000 0001 0010 0111 1010 1111 1110 0110 0100 0100 1110 1010 1000 0001 0001(2) × 20 =


1.0010 0111 1010 1111 1110 0110 0100 0100 1110 1010 1000 0001 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 1010 1111 1110 0110 0100 0100 1110 1010 1000 0001 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 1010 1111 1110 0110 0100 0100 1110 1010 1000 0001 0001 =


0010 0111 1010 1111 1110 0110 0100 0100 1110 1010 1000 0001 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 1010 1111 1110 0110 0100 0100 1110 1010 1000 0001 0001


Decimal number -0.000 281 989 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1010 1111 1110 0110 0100 0100 1110 1010 1000 0001 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