18.269 999 999 999 999 573 675 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 18.269 999 999 999 999 573 675(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
18.269 999 999 999 999 573 675(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. First, convert to binary (in base 2) the integer part: 18.
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;
  • 18 ÷ 2 = 9 + 0;
  • 9 ÷ 2 = 4 + 1;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

2. 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.

18(10) =


1 0010(2)


3. Convert to binary (base 2) the fractional part: 0.269 999 999 999 999 573 675.

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) 0.269 999 999 999 999 573 675 × 2 = 0 + 0.539 999 999 999 999 147 35;
  • 2) 0.539 999 999 999 999 147 35 × 2 = 1 + 0.079 999 999 999 998 294 7;
  • 3) 0.079 999 999 999 998 294 7 × 2 = 0 + 0.159 999 999 999 996 589 4;
  • 4) 0.159 999 999 999 996 589 4 × 2 = 0 + 0.319 999 999 999 993 178 8;
  • 5) 0.319 999 999 999 993 178 8 × 2 = 0 + 0.639 999 999 999 986 357 6;
  • 6) 0.639 999 999 999 986 357 6 × 2 = 1 + 0.279 999 999 999 972 715 2;
  • 7) 0.279 999 999 999 972 715 2 × 2 = 0 + 0.559 999 999 999 945 430 4;
  • 8) 0.559 999 999 999 945 430 4 × 2 = 1 + 0.119 999 999 999 890 860 8;
  • 9) 0.119 999 999 999 890 860 8 × 2 = 0 + 0.239 999 999 999 781 721 6;
  • 10) 0.239 999 999 999 781 721 6 × 2 = 0 + 0.479 999 999 999 563 443 2;
  • 11) 0.479 999 999 999 563 443 2 × 2 = 0 + 0.959 999 999 999 126 886 4;
  • 12) 0.959 999 999 999 126 886 4 × 2 = 1 + 0.919 999 999 998 253 772 8;
  • 13) 0.919 999 999 998 253 772 8 × 2 = 1 + 0.839 999 999 996 507 545 6;
  • 14) 0.839 999 999 996 507 545 6 × 2 = 1 + 0.679 999 999 993 015 091 2;
  • 15) 0.679 999 999 993 015 091 2 × 2 = 1 + 0.359 999 999 986 030 182 4;
  • 16) 0.359 999 999 986 030 182 4 × 2 = 0 + 0.719 999 999 972 060 364 8;
  • 17) 0.719 999 999 972 060 364 8 × 2 = 1 + 0.439 999 999 944 120 729 6;
  • 18) 0.439 999 999 944 120 729 6 × 2 = 0 + 0.879 999 999 888 241 459 2;
  • 19) 0.879 999 999 888 241 459 2 × 2 = 1 + 0.759 999 999 776 482 918 4;
  • 20) 0.759 999 999 776 482 918 4 × 2 = 1 + 0.519 999 999 552 965 836 8;
  • 21) 0.519 999 999 552 965 836 8 × 2 = 1 + 0.039 999 999 105 931 673 6;
  • 22) 0.039 999 999 105 931 673 6 × 2 = 0 + 0.079 999 998 211 863 347 2;
  • 23) 0.079 999 998 211 863 347 2 × 2 = 0 + 0.159 999 996 423 726 694 4;
  • 24) 0.159 999 996 423 726 694 4 × 2 = 0 + 0.319 999 992 847 453 388 8;
  • 25) 0.319 999 992 847 453 388 8 × 2 = 0 + 0.639 999 985 694 906 777 6;
  • 26) 0.639 999 985 694 906 777 6 × 2 = 1 + 0.279 999 971 389 813 555 2;
  • 27) 0.279 999 971 389 813 555 2 × 2 = 0 + 0.559 999 942 779 627 110 4;
  • 28) 0.559 999 942 779 627 110 4 × 2 = 1 + 0.119 999 885 559 254 220 8;
  • 29) 0.119 999 885 559 254 220 8 × 2 = 0 + 0.239 999 771 118 508 441 6;
  • 30) 0.239 999 771 118 508 441 6 × 2 = 0 + 0.479 999 542 237 016 883 2;
  • 31) 0.479 999 542 237 016 883 2 × 2 = 0 + 0.959 999 084 474 033 766 4;
  • 32) 0.959 999 084 474 033 766 4 × 2 = 1 + 0.919 998 168 948 067 532 8;
  • 33) 0.919 998 168 948 067 532 8 × 2 = 1 + 0.839 996 337 896 135 065 6;
  • 34) 0.839 996 337 896 135 065 6 × 2 = 1 + 0.679 992 675 792 270 131 2;
  • 35) 0.679 992 675 792 270 131 2 × 2 = 1 + 0.359 985 351 584 540 262 4;
  • 36) 0.359 985 351 584 540 262 4 × 2 = 0 + 0.719 970 703 169 080 524 8;
  • 37) 0.719 970 703 169 080 524 8 × 2 = 1 + 0.439 941 406 338 161 049 6;
  • 38) 0.439 941 406 338 161 049 6 × 2 = 0 + 0.879 882 812 676 322 099 2;
  • 39) 0.879 882 812 676 322 099 2 × 2 = 1 + 0.759 765 625 352 644 198 4;
  • 40) 0.759 765 625 352 644 198 4 × 2 = 1 + 0.519 531 250 705 288 396 8;
  • 41) 0.519 531 250 705 288 396 8 × 2 = 1 + 0.039 062 501 410 576 793 6;
  • 42) 0.039 062 501 410 576 793 6 × 2 = 0 + 0.078 125 002 821 153 587 2;
  • 43) 0.078 125 002 821 153 587 2 × 2 = 0 + 0.156 250 005 642 307 174 4;
  • 44) 0.156 250 005 642 307 174 4 × 2 = 0 + 0.312 500 011 284 614 348 8;
  • 45) 0.312 500 011 284 614 348 8 × 2 = 0 + 0.625 000 022 569 228 697 6;
  • 46) 0.625 000 022 569 228 697 6 × 2 = 1 + 0.250 000 045 138 457 395 2;
  • 47) 0.250 000 045 138 457 395 2 × 2 = 0 + 0.500 000 090 276 914 790 4;
  • 48) 0.500 000 090 276 914 790 4 × 2 = 1 + 0.000 000 180 553 829 580 8;
  • 49) 0.000 000 180 553 829 580 8 × 2 = 0 + 0.000 000 361 107 659 161 6;
  • 50) 0.000 000 361 107 659 161 6 × 2 = 0 + 0.000 000 722 215 318 323 2;
  • 51) 0.000 000 722 215 318 323 2 × 2 = 0 + 0.000 001 444 430 636 646 4;
  • 52) 0.000 001 444 430 636 646 4 × 2 = 0 + 0.000 002 888 861 273 292 8;
  • 53) 0.000 002 888 861 273 292 8 × 2 = 0 + 0.000 005 777 722 546 585 6;

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).


4. 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:


0.269 999 999 999 999 573 675(10) =


0.0100 0101 0001 1110 1011 1000 0101 0001 1110 1011 1000 0101 0000 0(2)

5. Positive number before normalization:

18.269 999 999 999 999 573 675(10) =


1 0010.0100 0101 0001 1110 1011 1000 0101 0001 1110 1011 1000 0101 0000 0(2)

6. 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:


18.269 999 999 999 999 573 675(10) =


1 0010.0100 0101 0001 1110 1011 1000 0101 0001 1110 1011 1000 0101 0000 0(2) =


1 0010.0100 0101 0001 1110 1011 1000 0101 0001 1110 1011 1000 0101 0000 0(2) × 20 =


1.0010 0100 0101 0001 1110 1011 1000 0101 0001 1110 1011 1000 0101 0000 0(2) × 24


7. 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 0 (a positive number)


Exponent (unadjusted): 4


Mantissa (not normalized):
1.0010 0100 0101 0001 1110 1011 1000 0101 0001 1110 1011 1000 0101 0000 0


8. 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)


9. 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;

10. 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)


11. 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. 0010 0100 0101 0001 1110 1011 1000 0101 0001 1110 1011 1000 0101 0 0000 =


0010 0100 0101 0001 1110 1011 1000 0101 0001 1110 1011 1000 0101


12. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
0 (a positive number)


Exponent (11 bits) =
100 0000 0011


Mantissa (52 bits) =
0010 0100 0101 0001 1110 1011 1000 0101 0001 1110 1011 1000 0101


Decimal number 18.269 999 999 999 999 573 675 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0011 - 0010 0100 0101 0001 1110 1011 1000 0101 0001 1110 1011 1000 0101


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