2.225 073 858 506 91 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.225 073 858 506 91(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
2.225 073 858 506 91(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: 2.
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;
  • 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.

2(10) =


10(2)


3. Convert to binary (base 2) the fractional part: 0.225 073 858 506 91.

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) 0.225 073 858 506 91 × 2 = 0 + 0.450 147 717 013 82;
  • 2) 0.450 147 717 013 82 × 2 = 0 + 0.900 295 434 027 64;
  • 3) 0.900 295 434 027 64 × 2 = 1 + 0.800 590 868 055 28;
  • 4) 0.800 590 868 055 28 × 2 = 1 + 0.601 181 736 110 56;
  • 5) 0.601 181 736 110 56 × 2 = 1 + 0.202 363 472 221 12;
  • 6) 0.202 363 472 221 12 × 2 = 0 + 0.404 726 944 442 24;
  • 7) 0.404 726 944 442 24 × 2 = 0 + 0.809 453 888 884 48;
  • 8) 0.809 453 888 884 48 × 2 = 1 + 0.618 907 777 768 96;
  • 9) 0.618 907 777 768 96 × 2 = 1 + 0.237 815 555 537 92;
  • 10) 0.237 815 555 537 92 × 2 = 0 + 0.475 631 111 075 84;
  • 11) 0.475 631 111 075 84 × 2 = 0 + 0.951 262 222 151 68;
  • 12) 0.951 262 222 151 68 × 2 = 1 + 0.902 524 444 303 36;
  • 13) 0.902 524 444 303 36 × 2 = 1 + 0.805 048 888 606 72;
  • 14) 0.805 048 888 606 72 × 2 = 1 + 0.610 097 777 213 44;
  • 15) 0.610 097 777 213 44 × 2 = 1 + 0.220 195 554 426 88;
  • 16) 0.220 195 554 426 88 × 2 = 0 + 0.440 391 108 853 76;
  • 17) 0.440 391 108 853 76 × 2 = 0 + 0.880 782 217 707 52;
  • 18) 0.880 782 217 707 52 × 2 = 1 + 0.761 564 435 415 04;
  • 19) 0.761 564 435 415 04 × 2 = 1 + 0.523 128 870 830 08;
  • 20) 0.523 128 870 830 08 × 2 = 1 + 0.046 257 741 660 16;
  • 21) 0.046 257 741 660 16 × 2 = 0 + 0.092 515 483 320 32;
  • 22) 0.092 515 483 320 32 × 2 = 0 + 0.185 030 966 640 64;
  • 23) 0.185 030 966 640 64 × 2 = 0 + 0.370 061 933 281 28;
  • 24) 0.370 061 933 281 28 × 2 = 0 + 0.740 123 866 562 56;
  • 25) 0.740 123 866 562 56 × 2 = 1 + 0.480 247 733 125 12;
  • 26) 0.480 247 733 125 12 × 2 = 0 + 0.960 495 466 250 24;
  • 27) 0.960 495 466 250 24 × 2 = 1 + 0.920 990 932 500 48;
  • 28) 0.920 990 932 500 48 × 2 = 1 + 0.841 981 865 000 96;
  • 29) 0.841 981 865 000 96 × 2 = 1 + 0.683 963 730 001 92;
  • 30) 0.683 963 730 001 92 × 2 = 1 + 0.367 927 460 003 84;
  • 31) 0.367 927 460 003 84 × 2 = 0 + 0.735 854 920 007 68;
  • 32) 0.735 854 920 007 68 × 2 = 1 + 0.471 709 840 015 36;
  • 33) 0.471 709 840 015 36 × 2 = 0 + 0.943 419 680 030 72;
  • 34) 0.943 419 680 030 72 × 2 = 1 + 0.886 839 360 061 44;
  • 35) 0.886 839 360 061 44 × 2 = 1 + 0.773 678 720 122 88;
  • 36) 0.773 678 720 122 88 × 2 = 1 + 0.547 357 440 245 76;
  • 37) 0.547 357 440 245 76 × 2 = 1 + 0.094 714 880 491 52;
  • 38) 0.094 714 880 491 52 × 2 = 0 + 0.189 429 760 983 04;
  • 39) 0.189 429 760 983 04 × 2 = 0 + 0.378 859 521 966 08;
  • 40) 0.378 859 521 966 08 × 2 = 0 + 0.757 719 043 932 16;
  • 41) 0.757 719 043 932 16 × 2 = 1 + 0.515 438 087 864 32;
  • 42) 0.515 438 087 864 32 × 2 = 1 + 0.030 876 175 728 64;
  • 43) 0.030 876 175 728 64 × 2 = 0 + 0.061 752 351 457 28;
  • 44) 0.061 752 351 457 28 × 2 = 0 + 0.123 504 702 914 56;
  • 45) 0.123 504 702 914 56 × 2 = 0 + 0.247 009 405 829 12;
  • 46) 0.247 009 405 829 12 × 2 = 0 + 0.494 018 811 658 24;
  • 47) 0.494 018 811 658 24 × 2 = 0 + 0.988 037 623 316 48;
  • 48) 0.988 037 623 316 48 × 2 = 1 + 0.976 075 246 632 96;
  • 49) 0.976 075 246 632 96 × 2 = 1 + 0.952 150 493 265 92;
  • 50) 0.952 150 493 265 92 × 2 = 1 + 0.904 300 986 531 84;
  • 51) 0.904 300 986 531 84 × 2 = 1 + 0.808 601 973 063 68;
  • 52) 0.808 601 973 063 68 × 2 = 1 + 0.617 203 946 127 36;
  • 53) 0.617 203 946 127 36 × 2 = 1 + 0.234 407 892 254 72;

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:


0.225 073 858 506 91(10) =


0.0011 1001 1001 1110 0111 0000 1011 1101 0111 1000 1100 0001 1111 1(2)

5. Positive number before normalization:

2.225 073 858 506 91(10) =


10.0011 1001 1001 1110 0111 0000 1011 1101 0111 1000 1100 0001 1111 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 1 positions to the left, so that only one non zero digit remains to the left of it:


2.225 073 858 506 91(10) =


10.0011 1001 1001 1110 0111 0000 1011 1101 0111 1000 1100 0001 1111 1(2) =


10.0011 1001 1001 1110 0111 0000 1011 1101 0111 1000 1100 0001 1111 1(2) × 20 =


1.0001 1100 1100 1111 0011 1000 0101 1110 1011 1100 0110 0000 1111 11(2) × 21


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): 1


Mantissa (not normalized):
1.0001 1100 1100 1111 0011 1000 0101 1110 1011 1100 0110 0000 1111 11


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


1 + 2(11-1) - 1 =


(1 + 1 023)(10) =


1 024(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;
  • 1 024 ÷ 2 = 512 + 0;
  • 512 ÷ 2 = 256 + 0;
  • 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) =


1024(10) =


100 0000 0000(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. 0001 1100 1100 1111 0011 1000 0101 1110 1011 1100 0110 0000 1111 11 =


0001 1100 1100 1111 0011 1000 0101 1110 1011 1100 0110 0000 1111


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 0000


Mantissa (52 bits) =
0001 1100 1100 1111 0011 1000 0101 1110 1011 1100 0110 0000 1111


Decimal number 2.225 073 858 506 91 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0001 1100 1100 1111 0011 1000 0101 1110 1011 1100 0110 0000 1111


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