-17.783 247 97 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -17.783 247 97(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
-17.783 247 97(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:

|-17.783 247 97| = 17.783 247 97


2. First, convert to binary (in base 2) the integer part: 17.
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;
  • 17 ÷ 2 = 8 + 1;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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.

17(10) =


1 0001(2)


4. Convert to binary (base 2) the fractional part: 0.783 247 97.

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) 0.783 247 97 × 2 = 1 + 0.566 495 94;
  • 2) 0.566 495 94 × 2 = 1 + 0.132 991 88;
  • 3) 0.132 991 88 × 2 = 0 + 0.265 983 76;
  • 4) 0.265 983 76 × 2 = 0 + 0.531 967 52;
  • 5) 0.531 967 52 × 2 = 1 + 0.063 935 04;
  • 6) 0.063 935 04 × 2 = 0 + 0.127 870 08;
  • 7) 0.127 870 08 × 2 = 0 + 0.255 740 16;
  • 8) 0.255 740 16 × 2 = 0 + 0.511 480 32;
  • 9) 0.511 480 32 × 2 = 1 + 0.022 960 64;
  • 10) 0.022 960 64 × 2 = 0 + 0.045 921 28;
  • 11) 0.045 921 28 × 2 = 0 + 0.091 842 56;
  • 12) 0.091 842 56 × 2 = 0 + 0.183 685 12;
  • 13) 0.183 685 12 × 2 = 0 + 0.367 370 24;
  • 14) 0.367 370 24 × 2 = 0 + 0.734 740 48;
  • 15) 0.734 740 48 × 2 = 1 + 0.469 480 96;
  • 16) 0.469 480 96 × 2 = 0 + 0.938 961 92;
  • 17) 0.938 961 92 × 2 = 1 + 0.877 923 84;
  • 18) 0.877 923 84 × 2 = 1 + 0.755 847 68;
  • 19) 0.755 847 68 × 2 = 1 + 0.511 695 36;
  • 20) 0.511 695 36 × 2 = 1 + 0.023 390 72;
  • 21) 0.023 390 72 × 2 = 0 + 0.046 781 44;
  • 22) 0.046 781 44 × 2 = 0 + 0.093 562 88;
  • 23) 0.093 562 88 × 2 = 0 + 0.187 125 76;
  • 24) 0.187 125 76 × 2 = 0 + 0.374 251 52;
  • 25) 0.374 251 52 × 2 = 0 + 0.748 503 04;
  • 26) 0.748 503 04 × 2 = 1 + 0.497 006 08;
  • 27) 0.497 006 08 × 2 = 0 + 0.994 012 16;
  • 28) 0.994 012 16 × 2 = 1 + 0.988 024 32;
  • 29) 0.988 024 32 × 2 = 1 + 0.976 048 64;
  • 30) 0.976 048 64 × 2 = 1 + 0.952 097 28;
  • 31) 0.952 097 28 × 2 = 1 + 0.904 194 56;
  • 32) 0.904 194 56 × 2 = 1 + 0.808 389 12;
  • 33) 0.808 389 12 × 2 = 1 + 0.616 778 24;
  • 34) 0.616 778 24 × 2 = 1 + 0.233 556 48;
  • 35) 0.233 556 48 × 2 = 0 + 0.467 112 96;
  • 36) 0.467 112 96 × 2 = 0 + 0.934 225 92;
  • 37) 0.934 225 92 × 2 = 1 + 0.868 451 84;
  • 38) 0.868 451 84 × 2 = 1 + 0.736 903 68;
  • 39) 0.736 903 68 × 2 = 1 + 0.473 807 36;
  • 40) 0.473 807 36 × 2 = 0 + 0.947 614 72;
  • 41) 0.947 614 72 × 2 = 1 + 0.895 229 44;
  • 42) 0.895 229 44 × 2 = 1 + 0.790 458 88;
  • 43) 0.790 458 88 × 2 = 1 + 0.580 917 76;
  • 44) 0.580 917 76 × 2 = 1 + 0.161 835 52;
  • 45) 0.161 835 52 × 2 = 0 + 0.323 671 04;
  • 46) 0.323 671 04 × 2 = 0 + 0.647 342 08;
  • 47) 0.647 342 08 × 2 = 1 + 0.294 684 16;
  • 48) 0.294 684 16 × 2 = 0 + 0.589 368 32;
  • 49) 0.589 368 32 × 2 = 1 + 0.178 736 64;
  • 50) 0.178 736 64 × 2 = 0 + 0.357 473 28;
  • 51) 0.357 473 28 × 2 = 0 + 0.714 946 56;
  • 52) 0.714 946 56 × 2 = 1 + 0.429 893 12;
  • 53) 0.429 893 12 × 2 = 0 + 0.859 786 24;

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:


0.783 247 97(10) =


0.1100 1000 1000 0010 1111 0000 0101 1111 1100 1110 1111 0010 1001 0(2)

6. Positive number before normalization:

17.783 247 97(10) =


1 0001.1100 1000 1000 0010 1111 0000 0101 1111 1100 1110 1111 0010 1001 0(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 4 positions to the left, so that only one non zero digit remains to the left of it:


17.783 247 97(10) =


1 0001.1100 1000 1000 0010 1111 0000 0101 1111 1100 1110 1111 0010 1001 0(2) =


1 0001.1100 1000 1000 0010 1111 0000 0101 1111 1100 1110 1111 0010 1001 0(2) × 20 =


1.0001 1100 1000 1000 0010 1111 0000 0101 1111 1100 1110 1111 0010 1001 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):
1.0001 1100 1000 1000 0010 1111 0000 0101 1111 1100 1110 1111 0010 1001 0


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


4 + 2(11-1) - 1 =


(4 + 1 023)(10) =


1 027(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;
  • 1 027 ÷ 2 = 513 + 1;
  • 513 ÷ 2 = 256 + 1;
  • 256 ÷ 2 = 128 + 0;
  • 128 ÷ 2 = 64 + 0;
  • 64 ÷ 2 = 32 + 0;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 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) =


1027(10) =


100 0000 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, by removing the excess bits, from the right (if any of the excess bits is set on 1, we are losing precision...).


Mantissa (normalized) =


1. 0001 1100 1000 1000 0010 1111 0000 0101 1111 1100 1110 1111 0010 1 0010 =


0001 1100 1000 1000 0010 1111 0000 0101 1111 1100 1110 1111 0010


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) =
100 0000 0011


Mantissa (52 bits) =
0001 1100 1000 1000 0010 1111 0000 0101 1111 1100 1110 1111 0010


Decimal number -17.783 247 97 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 0011 - 0001 1100 1000 1000 0010 1111 0000 0101 1111 1100 1110 1111 0010


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