23.922 727 272 725 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 23.922 727 272 725 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
23.922 727 272 725 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. First, convert to binary (in base 2) the integer part: 23.
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;
  • 23 ÷ 2 = 11 + 1;
  • 11 ÷ 2 = 5 + 1;
  • 5 ÷ 2 = 2 + 1;
  • 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.

23(10) =


1 0111(2)


3. Convert to binary (base 2) the fractional part: 0.922 727 272 725 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) 0.922 727 272 725 2 × 2 = 1 + 0.845 454 545 450 4;
  • 2) 0.845 454 545 450 4 × 2 = 1 + 0.690 909 090 900 8;
  • 3) 0.690 909 090 900 8 × 2 = 1 + 0.381 818 181 801 6;
  • 4) 0.381 818 181 801 6 × 2 = 0 + 0.763 636 363 603 2;
  • 5) 0.763 636 363 603 2 × 2 = 1 + 0.527 272 727 206 4;
  • 6) 0.527 272 727 206 4 × 2 = 1 + 0.054 545 454 412 8;
  • 7) 0.054 545 454 412 8 × 2 = 0 + 0.109 090 908 825 6;
  • 8) 0.109 090 908 825 6 × 2 = 0 + 0.218 181 817 651 2;
  • 9) 0.218 181 817 651 2 × 2 = 0 + 0.436 363 635 302 4;
  • 10) 0.436 363 635 302 4 × 2 = 0 + 0.872 727 270 604 8;
  • 11) 0.872 727 270 604 8 × 2 = 1 + 0.745 454 541 209 6;
  • 12) 0.745 454 541 209 6 × 2 = 1 + 0.490 909 082 419 2;
  • 13) 0.490 909 082 419 2 × 2 = 0 + 0.981 818 164 838 4;
  • 14) 0.981 818 164 838 4 × 2 = 1 + 0.963 636 329 676 8;
  • 15) 0.963 636 329 676 8 × 2 = 1 + 0.927 272 659 353 6;
  • 16) 0.927 272 659 353 6 × 2 = 1 + 0.854 545 318 707 2;
  • 17) 0.854 545 318 707 2 × 2 = 1 + 0.709 090 637 414 4;
  • 18) 0.709 090 637 414 4 × 2 = 1 + 0.418 181 274 828 8;
  • 19) 0.418 181 274 828 8 × 2 = 0 + 0.836 362 549 657 6;
  • 20) 0.836 362 549 657 6 × 2 = 1 + 0.672 725 099 315 2;
  • 21) 0.672 725 099 315 2 × 2 = 1 + 0.345 450 198 630 4;
  • 22) 0.345 450 198 630 4 × 2 = 0 + 0.690 900 397 260 8;
  • 23) 0.690 900 397 260 8 × 2 = 1 + 0.381 800 794 521 6;
  • 24) 0.381 800 794 521 6 × 2 = 0 + 0.763 601 589 043 2;
  • 25) 0.763 601 589 043 2 × 2 = 1 + 0.527 203 178 086 4;
  • 26) 0.527 203 178 086 4 × 2 = 1 + 0.054 406 356 172 8;
  • 27) 0.054 406 356 172 8 × 2 = 0 + 0.108 812 712 345 6;
  • 28) 0.108 812 712 345 6 × 2 = 0 + 0.217 625 424 691 2;
  • 29) 0.217 625 424 691 2 × 2 = 0 + 0.435 250 849 382 4;
  • 30) 0.435 250 849 382 4 × 2 = 0 + 0.870 501 698 764 8;
  • 31) 0.870 501 698 764 8 × 2 = 1 + 0.741 003 397 529 6;
  • 32) 0.741 003 397 529 6 × 2 = 1 + 0.482 006 795 059 2;
  • 33) 0.482 006 795 059 2 × 2 = 0 + 0.964 013 590 118 4;
  • 34) 0.964 013 590 118 4 × 2 = 1 + 0.928 027 180 236 8;
  • 35) 0.928 027 180 236 8 × 2 = 1 + 0.856 054 360 473 6;
  • 36) 0.856 054 360 473 6 × 2 = 1 + 0.712 108 720 947 2;
  • 37) 0.712 108 720 947 2 × 2 = 1 + 0.424 217 441 894 4;
  • 38) 0.424 217 441 894 4 × 2 = 0 + 0.848 434 883 788 8;
  • 39) 0.848 434 883 788 8 × 2 = 1 + 0.696 869 767 577 6;
  • 40) 0.696 869 767 577 6 × 2 = 1 + 0.393 739 535 155 2;
  • 41) 0.393 739 535 155 2 × 2 = 0 + 0.787 479 070 310 4;
  • 42) 0.787 479 070 310 4 × 2 = 1 + 0.574 958 140 620 8;
  • 43) 0.574 958 140 620 8 × 2 = 1 + 0.149 916 281 241 6;
  • 44) 0.149 916 281 241 6 × 2 = 0 + 0.299 832 562 483 2;
  • 45) 0.299 832 562 483 2 × 2 = 0 + 0.599 665 124 966 4;
  • 46) 0.599 665 124 966 4 × 2 = 1 + 0.199 330 249 932 8;
  • 47) 0.199 330 249 932 8 × 2 = 0 + 0.398 660 499 865 6;
  • 48) 0.398 660 499 865 6 × 2 = 0 + 0.797 320 999 731 2;
  • 49) 0.797 320 999 731 2 × 2 = 1 + 0.594 641 999 462 4;
  • 50) 0.594 641 999 462 4 × 2 = 1 + 0.189 283 998 924 8;
  • 51) 0.189 283 998 924 8 × 2 = 0 + 0.378 567 997 849 6;
  • 52) 0.378 567 997 849 6 × 2 = 0 + 0.757 135 995 699 2;
  • 53) 0.757 135 995 699 2 × 2 = 1 + 0.514 271 991 398 4;

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:


0.922 727 272 725 2(10) =


0.1110 1100 0011 0111 1101 1010 1100 0011 0111 1011 0110 0100 1100 1(2)

5. Positive number before normalization:

23.922 727 272 725 2(10) =


1 0111.1110 1100 0011 0111 1101 1010 1100 0011 0111 1011 0110 0100 1100 1(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:


23.922 727 272 725 2(10) =


1 0111.1110 1100 0011 0111 1101 1010 1100 0011 0111 1011 0110 0100 1100 1(2) =


1 0111.1110 1100 0011 0111 1101 1010 1100 0011 0111 1011 0110 0100 1100 1(2) × 20 =


1.0111 1110 1100 0011 0111 1101 1010 1100 0011 0111 1011 0110 0100 1100 1(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):
1.0111 1110 1100 0011 0111 1101 1010 1100 0011 0111 1011 0110 0100 1100 1


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. 0111 1110 1100 0011 0111 1101 1010 1100 0011 0111 1011 0110 0100 1 1001 =


0111 1110 1100 0011 0111 1101 1010 1100 0011 0111 1011 0110 0100


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) =
0111 1110 1100 0011 0111 1101 1010 1100 0011 0111 1011 0110 0100


Decimal number 23.922 727 272 725 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0011 - 0111 1110 1100 0011 0111 1101 1010 1100 0011 0111 1011 0110 0100

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