-17.783 247 610 924 9 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -17.783 247 610 924 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
-17.783 247 610 924 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:

|-17.783 247 610 924 9| = 17.783 247 610 924 9


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: 0.783 247 610 924 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) 0.783 247 610 924 9 × 2 = 1 + 0.566 495 221 849 8;
  • 2) 0.566 495 221 849 8 × 2 = 1 + 0.132 990 443 699 6;
  • 3) 0.132 990 443 699 6 × 2 = 0 + 0.265 980 887 399 2;
  • 4) 0.265 980 887 399 2 × 2 = 0 + 0.531 961 774 798 4;
  • 5) 0.531 961 774 798 4 × 2 = 1 + 0.063 923 549 596 8;
  • 6) 0.063 923 549 596 8 × 2 = 0 + 0.127 847 099 193 6;
  • 7) 0.127 847 099 193 6 × 2 = 0 + 0.255 694 198 387 2;
  • 8) 0.255 694 198 387 2 × 2 = 0 + 0.511 388 396 774 4;
  • 9) 0.511 388 396 774 4 × 2 = 1 + 0.022 776 793 548 8;
  • 10) 0.022 776 793 548 8 × 2 = 0 + 0.045 553 587 097 6;
  • 11) 0.045 553 587 097 6 × 2 = 0 + 0.091 107 174 195 2;
  • 12) 0.091 107 174 195 2 × 2 = 0 + 0.182 214 348 390 4;
  • 13) 0.182 214 348 390 4 × 2 = 0 + 0.364 428 696 780 8;
  • 14) 0.364 428 696 780 8 × 2 = 0 + 0.728 857 393 561 6;
  • 15) 0.728 857 393 561 6 × 2 = 1 + 0.457 714 787 123 2;
  • 16) 0.457 714 787 123 2 × 2 = 0 + 0.915 429 574 246 4;
  • 17) 0.915 429 574 246 4 × 2 = 1 + 0.830 859 148 492 8;
  • 18) 0.830 859 148 492 8 × 2 = 1 + 0.661 718 296 985 6;
  • 19) 0.661 718 296 985 6 × 2 = 1 + 0.323 436 593 971 2;
  • 20) 0.323 436 593 971 2 × 2 = 0 + 0.646 873 187 942 4;
  • 21) 0.646 873 187 942 4 × 2 = 1 + 0.293 746 375 884 8;
  • 22) 0.293 746 375 884 8 × 2 = 0 + 0.587 492 751 769 6;
  • 23) 0.587 492 751 769 6 × 2 = 1 + 0.174 985 503 539 2;
  • 24) 0.174 985 503 539 2 × 2 = 0 + 0.349 971 007 078 4;
  • 25) 0.349 971 007 078 4 × 2 = 0 + 0.699 942 014 156 8;
  • 26) 0.699 942 014 156 8 × 2 = 1 + 0.399 884 028 313 6;
  • 27) 0.399 884 028 313 6 × 2 = 0 + 0.799 768 056 627 2;
  • 28) 0.799 768 056 627 2 × 2 = 1 + 0.599 536 113 254 4;
  • 29) 0.599 536 113 254 4 × 2 = 1 + 0.199 072 226 508 8;
  • 30) 0.199 072 226 508 8 × 2 = 0 + 0.398 144 453 017 6;
  • 31) 0.398 144 453 017 6 × 2 = 0 + 0.796 288 906 035 2;
  • 32) 0.796 288 906 035 2 × 2 = 1 + 0.592 577 812 070 4;
  • 33) 0.592 577 812 070 4 × 2 = 1 + 0.185 155 624 140 8;
  • 34) 0.185 155 624 140 8 × 2 = 0 + 0.370 311 248 281 6;
  • 35) 0.370 311 248 281 6 × 2 = 0 + 0.740 622 496 563 2;
  • 36) 0.740 622 496 563 2 × 2 = 1 + 0.481 244 993 126 4;
  • 37) 0.481 244 993 126 4 × 2 = 0 + 0.962 489 986 252 8;
  • 38) 0.962 489 986 252 8 × 2 = 1 + 0.924 979 972 505 6;
  • 39) 0.924 979 972 505 6 × 2 = 1 + 0.849 959 945 011 2;
  • 40) 0.849 959 945 011 2 × 2 = 1 + 0.699 919 890 022 4;
  • 41) 0.699 919 890 022 4 × 2 = 1 + 0.399 839 780 044 8;
  • 42) 0.399 839 780 044 8 × 2 = 0 + 0.799 679 560 089 6;
  • 43) 0.799 679 560 089 6 × 2 = 1 + 0.599 359 120 179 2;
  • 44) 0.599 359 120 179 2 × 2 = 1 + 0.198 718 240 358 4;
  • 45) 0.198 718 240 358 4 × 2 = 0 + 0.397 436 480 716 8;
  • 46) 0.397 436 480 716 8 × 2 = 0 + 0.794 872 961 433 6;
  • 47) 0.794 872 961 433 6 × 2 = 1 + 0.589 745 922 867 2;
  • 48) 0.589 745 922 867 2 × 2 = 1 + 0.179 491 845 734 4;
  • 49) 0.179 491 845 734 4 × 2 = 0 + 0.358 983 691 468 8;
  • 50) 0.358 983 691 468 8 × 2 = 0 + 0.717 967 382 937 6;
  • 51) 0.717 967 382 937 6 × 2 = 1 + 0.435 934 765 875 2;
  • 52) 0.435 934 765 875 2 × 2 = 0 + 0.871 869 531 750 4;
  • 53) 0.871 869 531 750 4 × 2 = 1 + 0.743 739 063 500 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:


0.783 247 610 924 9(10) =


0.1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1011 0011 0010 1(2)

6. Positive number before normalization:

17.783 247 610 924 9(10) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1011 0011 0010 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:


17.783 247 610 924 9(10) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1011 0011 0010 1(2) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1011 0011 0010 1(2) × 20 =


1.0001 1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1011 0011 0010 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 0111 1011 0011 0010 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 0111 1011 0011 0 0101 =


0001 1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1011 0011


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 0111 1011 0011


Decimal number -17.783 247 610 924 9 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 0111 1011 0011


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