2.225 073 858 507 201 383 85 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.225 073 858 507 201 383 85(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
2.225 073 858 507 201 383 85(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: 0.225 073 858 507 201 383 85.

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) 0.225 073 858 507 201 383 85 × 2 = 0 + 0.450 147 717 014 402 767 7;
  • 2) 0.450 147 717 014 402 767 7 × 2 = 0 + 0.900 295 434 028 805 535 4;
  • 3) 0.900 295 434 028 805 535 4 × 2 = 1 + 0.800 590 868 057 611 070 8;
  • 4) 0.800 590 868 057 611 070 8 × 2 = 1 + 0.601 181 736 115 222 141 6;
  • 5) 0.601 181 736 115 222 141 6 × 2 = 1 + 0.202 363 472 230 444 283 2;
  • 6) 0.202 363 472 230 444 283 2 × 2 = 0 + 0.404 726 944 460 888 566 4;
  • 7) 0.404 726 944 460 888 566 4 × 2 = 0 + 0.809 453 888 921 777 132 8;
  • 8) 0.809 453 888 921 777 132 8 × 2 = 1 + 0.618 907 777 843 554 265 6;
  • 9) 0.618 907 777 843 554 265 6 × 2 = 1 + 0.237 815 555 687 108 531 2;
  • 10) 0.237 815 555 687 108 531 2 × 2 = 0 + 0.475 631 111 374 217 062 4;
  • 11) 0.475 631 111 374 217 062 4 × 2 = 0 + 0.951 262 222 748 434 124 8;
  • 12) 0.951 262 222 748 434 124 8 × 2 = 1 + 0.902 524 445 496 868 249 6;
  • 13) 0.902 524 445 496 868 249 6 × 2 = 1 + 0.805 048 890 993 736 499 2;
  • 14) 0.805 048 890 993 736 499 2 × 2 = 1 + 0.610 097 781 987 472 998 4;
  • 15) 0.610 097 781 987 472 998 4 × 2 = 1 + 0.220 195 563 974 945 996 8;
  • 16) 0.220 195 563 974 945 996 8 × 2 = 0 + 0.440 391 127 949 891 993 6;
  • 17) 0.440 391 127 949 891 993 6 × 2 = 0 + 0.880 782 255 899 783 987 2;
  • 18) 0.880 782 255 899 783 987 2 × 2 = 1 + 0.761 564 511 799 567 974 4;
  • 19) 0.761 564 511 799 567 974 4 × 2 = 1 + 0.523 129 023 599 135 948 8;
  • 20) 0.523 129 023 599 135 948 8 × 2 = 1 + 0.046 258 047 198 271 897 6;
  • 21) 0.046 258 047 198 271 897 6 × 2 = 0 + 0.092 516 094 396 543 795 2;
  • 22) 0.092 516 094 396 543 795 2 × 2 = 0 + 0.185 032 188 793 087 590 4;
  • 23) 0.185 032 188 793 087 590 4 × 2 = 0 + 0.370 064 377 586 175 180 8;
  • 24) 0.370 064 377 586 175 180 8 × 2 = 0 + 0.740 128 755 172 350 361 6;
  • 25) 0.740 128 755 172 350 361 6 × 2 = 1 + 0.480 257 510 344 700 723 2;
  • 26) 0.480 257 510 344 700 723 2 × 2 = 0 + 0.960 515 020 689 401 446 4;
  • 27) 0.960 515 020 689 401 446 4 × 2 = 1 + 0.921 030 041 378 802 892 8;
  • 28) 0.921 030 041 378 802 892 8 × 2 = 1 + 0.842 060 082 757 605 785 6;
  • 29) 0.842 060 082 757 605 785 6 × 2 = 1 + 0.684 120 165 515 211 571 2;
  • 30) 0.684 120 165 515 211 571 2 × 2 = 1 + 0.368 240 331 030 423 142 4;
  • 31) 0.368 240 331 030 423 142 4 × 2 = 0 + 0.736 480 662 060 846 284 8;
  • 32) 0.736 480 662 060 846 284 8 × 2 = 1 + 0.472 961 324 121 692 569 6;
  • 33) 0.472 961 324 121 692 569 6 × 2 = 0 + 0.945 922 648 243 385 139 2;
  • 34) 0.945 922 648 243 385 139 2 × 2 = 1 + 0.891 845 296 486 770 278 4;
  • 35) 0.891 845 296 486 770 278 4 × 2 = 1 + 0.783 690 592 973 540 556 8;
  • 36) 0.783 690 592 973 540 556 8 × 2 = 1 + 0.567 381 185 947 081 113 6;
  • 37) 0.567 381 185 947 081 113 6 × 2 = 1 + 0.134 762 371 894 162 227 2;
  • 38) 0.134 762 371 894 162 227 2 × 2 = 0 + 0.269 524 743 788 324 454 4;
  • 39) 0.269 524 743 788 324 454 4 × 2 = 0 + 0.539 049 487 576 648 908 8;
  • 40) 0.539 049 487 576 648 908 8 × 2 = 1 + 0.078 098 975 153 297 817 6;
  • 41) 0.078 098 975 153 297 817 6 × 2 = 0 + 0.156 197 950 306 595 635 2;
  • 42) 0.156 197 950 306 595 635 2 × 2 = 0 + 0.312 395 900 613 191 270 4;
  • 43) 0.312 395 900 613 191 270 4 × 2 = 0 + 0.624 791 801 226 382 540 8;
  • 44) 0.624 791 801 226 382 540 8 × 2 = 1 + 0.249 583 602 452 765 081 6;
  • 45) 0.249 583 602 452 765 081 6 × 2 = 0 + 0.499 167 204 905 530 163 2;
  • 46) 0.499 167 204 905 530 163 2 × 2 = 0 + 0.998 334 409 811 060 326 4;
  • 47) 0.998 334 409 811 060 326 4 × 2 = 1 + 0.996 668 819 622 120 652 8;
  • 48) 0.996 668 819 622 120 652 8 × 2 = 1 + 0.993 337 639 244 241 305 6;
  • 49) 0.993 337 639 244 241 305 6 × 2 = 1 + 0.986 675 278 488 482 611 2;
  • 50) 0.986 675 278 488 482 611 2 × 2 = 1 + 0.973 350 556 976 965 222 4;
  • 51) 0.973 350 556 976 965 222 4 × 2 = 1 + 0.946 701 113 953 930 444 8;
  • 52) 0.946 701 113 953 930 444 8 × 2 = 1 + 0.893 402 227 907 860 889 6;
  • 53) 0.893 402 227 907 860 889 6 × 2 = 1 + 0.786 804 455 815 721 779 2;

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:


0.225 073 858 507 201 383 85(10) =


0.0011 1001 1001 1110 0111 0000 1011 1101 0111 1001 0001 0011 1111 1(2)

5. Positive number before normalization:

2.225 073 858 507 201 383 85(10) =


10.0011 1001 1001 1110 0111 0000 1011 1101 0111 1001 0001 0011 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:


2.225 073 858 507 201 383 85(10) =


10.0011 1001 1001 1110 0111 0000 1011 1101 0111 1001 0001 0011 1111 1(2) =


10.0011 1001 1001 1110 0111 0000 1011 1101 0111 1001 0001 0011 1111 1(2) × 20 =


1.0001 1100 1100 1111 0011 1000 0101 1110 1011 1100 1000 1001 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 1000 1001 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 1000 1001 1111 11 =


0001 1100 1100 1111 0011 1000 0101 1110 1011 1100 1000 1001 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 1000 1001 1111


Decimal number 2.225 073 858 507 201 383 85 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 1000 1001 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