2.225 073 858 507 201 383 06 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.225 073 858 507 201 383 06(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 06(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 06.

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 06 × 2 = 0 + 0.450 147 717 014 402 766 12;
  • 2) 0.450 147 717 014 402 766 12 × 2 = 0 + 0.900 295 434 028 805 532 24;
  • 3) 0.900 295 434 028 805 532 24 × 2 = 1 + 0.800 590 868 057 611 064 48;
  • 4) 0.800 590 868 057 611 064 48 × 2 = 1 + 0.601 181 736 115 222 128 96;
  • 5) 0.601 181 736 115 222 128 96 × 2 = 1 + 0.202 363 472 230 444 257 92;
  • 6) 0.202 363 472 230 444 257 92 × 2 = 0 + 0.404 726 944 460 888 515 84;
  • 7) 0.404 726 944 460 888 515 84 × 2 = 0 + 0.809 453 888 921 777 031 68;
  • 8) 0.809 453 888 921 777 031 68 × 2 = 1 + 0.618 907 777 843 554 063 36;
  • 9) 0.618 907 777 843 554 063 36 × 2 = 1 + 0.237 815 555 687 108 126 72;
  • 10) 0.237 815 555 687 108 126 72 × 2 = 0 + 0.475 631 111 374 216 253 44;
  • 11) 0.475 631 111 374 216 253 44 × 2 = 0 + 0.951 262 222 748 432 506 88;
  • 12) 0.951 262 222 748 432 506 88 × 2 = 1 + 0.902 524 445 496 865 013 76;
  • 13) 0.902 524 445 496 865 013 76 × 2 = 1 + 0.805 048 890 993 730 027 52;
  • 14) 0.805 048 890 993 730 027 52 × 2 = 1 + 0.610 097 781 987 460 055 04;
  • 15) 0.610 097 781 987 460 055 04 × 2 = 1 + 0.220 195 563 974 920 110 08;
  • 16) 0.220 195 563 974 920 110 08 × 2 = 0 + 0.440 391 127 949 840 220 16;
  • 17) 0.440 391 127 949 840 220 16 × 2 = 0 + 0.880 782 255 899 680 440 32;
  • 18) 0.880 782 255 899 680 440 32 × 2 = 1 + 0.761 564 511 799 360 880 64;
  • 19) 0.761 564 511 799 360 880 64 × 2 = 1 + 0.523 129 023 598 721 761 28;
  • 20) 0.523 129 023 598 721 761 28 × 2 = 1 + 0.046 258 047 197 443 522 56;
  • 21) 0.046 258 047 197 443 522 56 × 2 = 0 + 0.092 516 094 394 887 045 12;
  • 22) 0.092 516 094 394 887 045 12 × 2 = 0 + 0.185 032 188 789 774 090 24;
  • 23) 0.185 032 188 789 774 090 24 × 2 = 0 + 0.370 064 377 579 548 180 48;
  • 24) 0.370 064 377 579 548 180 48 × 2 = 0 + 0.740 128 755 159 096 360 96;
  • 25) 0.740 128 755 159 096 360 96 × 2 = 1 + 0.480 257 510 318 192 721 92;
  • 26) 0.480 257 510 318 192 721 92 × 2 = 0 + 0.960 515 020 636 385 443 84;
  • 27) 0.960 515 020 636 385 443 84 × 2 = 1 + 0.921 030 041 272 770 887 68;
  • 28) 0.921 030 041 272 770 887 68 × 2 = 1 + 0.842 060 082 545 541 775 36;
  • 29) 0.842 060 082 545 541 775 36 × 2 = 1 + 0.684 120 165 091 083 550 72;
  • 30) 0.684 120 165 091 083 550 72 × 2 = 1 + 0.368 240 330 182 167 101 44;
  • 31) 0.368 240 330 182 167 101 44 × 2 = 0 + 0.736 480 660 364 334 202 88;
  • 32) 0.736 480 660 364 334 202 88 × 2 = 1 + 0.472 961 320 728 668 405 76;
  • 33) 0.472 961 320 728 668 405 76 × 2 = 0 + 0.945 922 641 457 336 811 52;
  • 34) 0.945 922 641 457 336 811 52 × 2 = 1 + 0.891 845 282 914 673 623 04;
  • 35) 0.891 845 282 914 673 623 04 × 2 = 1 + 0.783 690 565 829 347 246 08;
  • 36) 0.783 690 565 829 347 246 08 × 2 = 1 + 0.567 381 131 658 694 492 16;
  • 37) 0.567 381 131 658 694 492 16 × 2 = 1 + 0.134 762 263 317 388 984 32;
  • 38) 0.134 762 263 317 388 984 32 × 2 = 0 + 0.269 524 526 634 777 968 64;
  • 39) 0.269 524 526 634 777 968 64 × 2 = 0 + 0.539 049 053 269 555 937 28;
  • 40) 0.539 049 053 269 555 937 28 × 2 = 1 + 0.078 098 106 539 111 874 56;
  • 41) 0.078 098 106 539 111 874 56 × 2 = 0 + 0.156 196 213 078 223 749 12;
  • 42) 0.156 196 213 078 223 749 12 × 2 = 0 + 0.312 392 426 156 447 498 24;
  • 43) 0.312 392 426 156 447 498 24 × 2 = 0 + 0.624 784 852 312 894 996 48;
  • 44) 0.624 784 852 312 894 996 48 × 2 = 1 + 0.249 569 704 625 789 992 96;
  • 45) 0.249 569 704 625 789 992 96 × 2 = 0 + 0.499 139 409 251 579 985 92;
  • 46) 0.499 139 409 251 579 985 92 × 2 = 0 + 0.998 278 818 503 159 971 84;
  • 47) 0.998 278 818 503 159 971 84 × 2 = 1 + 0.996 557 637 006 319 943 68;
  • 48) 0.996 557 637 006 319 943 68 × 2 = 1 + 0.993 115 274 012 639 887 36;
  • 49) 0.993 115 274 012 639 887 36 × 2 = 1 + 0.986 230 548 025 279 774 72;
  • 50) 0.986 230 548 025 279 774 72 × 2 = 1 + 0.972 461 096 050 559 549 44;
  • 51) 0.972 461 096 050 559 549 44 × 2 = 1 + 0.944 922 192 101 119 098 88;
  • 52) 0.944 922 192 101 119 098 88 × 2 = 1 + 0.889 844 384 202 238 197 76;
  • 53) 0.889 844 384 202 238 197 76 × 2 = 1 + 0.779 688 768 404 476 395 52;

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 06(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 06(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 06(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 06 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