-17.783 247 610 922 15 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -17.783 247 610 922 15(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
-17.783 247 610 922 15(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:

|-17.783 247 610 922 15| = 17.783 247 610 922 15


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: 0.783 247 610 922 15.

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) 0.783 247 610 922 15 × 2 = 1 + 0.566 495 221 844 3;
  • 2) 0.566 495 221 844 3 × 2 = 1 + 0.132 990 443 688 6;
  • 3) 0.132 990 443 688 6 × 2 = 0 + 0.265 980 887 377 2;
  • 4) 0.265 980 887 377 2 × 2 = 0 + 0.531 961 774 754 4;
  • 5) 0.531 961 774 754 4 × 2 = 1 + 0.063 923 549 508 8;
  • 6) 0.063 923 549 508 8 × 2 = 0 + 0.127 847 099 017 6;
  • 7) 0.127 847 099 017 6 × 2 = 0 + 0.255 694 198 035 2;
  • 8) 0.255 694 198 035 2 × 2 = 0 + 0.511 388 396 070 4;
  • 9) 0.511 388 396 070 4 × 2 = 1 + 0.022 776 792 140 8;
  • 10) 0.022 776 792 140 8 × 2 = 0 + 0.045 553 584 281 6;
  • 11) 0.045 553 584 281 6 × 2 = 0 + 0.091 107 168 563 2;
  • 12) 0.091 107 168 563 2 × 2 = 0 + 0.182 214 337 126 4;
  • 13) 0.182 214 337 126 4 × 2 = 0 + 0.364 428 674 252 8;
  • 14) 0.364 428 674 252 8 × 2 = 0 + 0.728 857 348 505 6;
  • 15) 0.728 857 348 505 6 × 2 = 1 + 0.457 714 697 011 2;
  • 16) 0.457 714 697 011 2 × 2 = 0 + 0.915 429 394 022 4;
  • 17) 0.915 429 394 022 4 × 2 = 1 + 0.830 858 788 044 8;
  • 18) 0.830 858 788 044 8 × 2 = 1 + 0.661 717 576 089 6;
  • 19) 0.661 717 576 089 6 × 2 = 1 + 0.323 435 152 179 2;
  • 20) 0.323 435 152 179 2 × 2 = 0 + 0.646 870 304 358 4;
  • 21) 0.646 870 304 358 4 × 2 = 1 + 0.293 740 608 716 8;
  • 22) 0.293 740 608 716 8 × 2 = 0 + 0.587 481 217 433 6;
  • 23) 0.587 481 217 433 6 × 2 = 1 + 0.174 962 434 867 2;
  • 24) 0.174 962 434 867 2 × 2 = 0 + 0.349 924 869 734 4;
  • 25) 0.349 924 869 734 4 × 2 = 0 + 0.699 849 739 468 8;
  • 26) 0.699 849 739 468 8 × 2 = 1 + 0.399 699 478 937 6;
  • 27) 0.399 699 478 937 6 × 2 = 0 + 0.799 398 957 875 2;
  • 28) 0.799 398 957 875 2 × 2 = 1 + 0.598 797 915 750 4;
  • 29) 0.598 797 915 750 4 × 2 = 1 + 0.197 595 831 500 8;
  • 30) 0.197 595 831 500 8 × 2 = 0 + 0.395 191 663 001 6;
  • 31) 0.395 191 663 001 6 × 2 = 0 + 0.790 383 326 003 2;
  • 32) 0.790 383 326 003 2 × 2 = 1 + 0.580 766 652 006 4;
  • 33) 0.580 766 652 006 4 × 2 = 1 + 0.161 533 304 012 8;
  • 34) 0.161 533 304 012 8 × 2 = 0 + 0.323 066 608 025 6;
  • 35) 0.323 066 608 025 6 × 2 = 0 + 0.646 133 216 051 2;
  • 36) 0.646 133 216 051 2 × 2 = 1 + 0.292 266 432 102 4;
  • 37) 0.292 266 432 102 4 × 2 = 0 + 0.584 532 864 204 8;
  • 38) 0.584 532 864 204 8 × 2 = 1 + 0.169 065 728 409 6;
  • 39) 0.169 065 728 409 6 × 2 = 0 + 0.338 131 456 819 2;
  • 40) 0.338 131 456 819 2 × 2 = 0 + 0.676 262 913 638 4;
  • 41) 0.676 262 913 638 4 × 2 = 1 + 0.352 525 827 276 8;
  • 42) 0.352 525 827 276 8 × 2 = 0 + 0.705 051 654 553 6;
  • 43) 0.705 051 654 553 6 × 2 = 1 + 0.410 103 309 107 2;
  • 44) 0.410 103 309 107 2 × 2 = 0 + 0.820 206 618 214 4;
  • 45) 0.820 206 618 214 4 × 2 = 1 + 0.640 413 236 428 8;
  • 46) 0.640 413 236 428 8 × 2 = 1 + 0.280 826 472 857 6;
  • 47) 0.280 826 472 857 6 × 2 = 0 + 0.561 652 945 715 2;
  • 48) 0.561 652 945 715 2 × 2 = 1 + 0.123 305 891 430 4;
  • 49) 0.123 305 891 430 4 × 2 = 0 + 0.246 611 782 860 8;
  • 50) 0.246 611 782 860 8 × 2 = 0 + 0.493 223 565 721 6;
  • 51) 0.493 223 565 721 6 × 2 = 0 + 0.986 447 131 443 2;
  • 52) 0.986 447 131 443 2 × 2 = 1 + 0.972 894 262 886 4;
  • 53) 0.972 894 262 886 4 × 2 = 1 + 0.945 788 525 772 8;

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:


0.783 247 610 922 15(10) =


0.1100 1000 1000 0010 1110 1010 0101 1001 1001 0100 1010 1101 0001 1(2)

6. Positive number before normalization:

17.783 247 610 922 15(10) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1001 0100 1010 1101 0001 1(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:


17.783 247 610 922 15(10) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1001 0100 1010 1101 0001 1(2) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1001 0100 1010 1101 0001 1(2) × 20 =


1.0001 1100 1000 1000 0010 1110 1010 0101 1001 1001 0100 1010 1101 0001 1(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 1110 1010 0101 1001 1001 0100 1010 1101 0001 1


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 1110 1010 0101 1001 1001 0100 1010 1101 0 0011 =


0001 1100 1000 1000 0010 1110 1010 0101 1001 1001 0100 1010 1101


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 1110 1010 0101 1001 1001 0100 1010 1101


Decimal number -17.783 247 610 922 15 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 0011 - 0001 1100 1000 1000 0010 1110 1010 0101 1001 1001 0100 1010 1101


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