0.026 916 503 899 9 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.026 916 503 899 9(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
0.026 916 503 899 9(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: 0.
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;
  • 0 ÷ 2 = 0 + 0;

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.

0(10) =


0(2)


3. Convert to binary (base 2) the fractional part: 0.026 916 503 899 9.

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) 0.026 916 503 899 9 × 2 = 0 + 0.053 833 007 799 8;
  • 2) 0.053 833 007 799 8 × 2 = 0 + 0.107 666 015 599 6;
  • 3) 0.107 666 015 599 6 × 2 = 0 + 0.215 332 031 199 2;
  • 4) 0.215 332 031 199 2 × 2 = 0 + 0.430 664 062 398 4;
  • 5) 0.430 664 062 398 4 × 2 = 0 + 0.861 328 124 796 8;
  • 6) 0.861 328 124 796 8 × 2 = 1 + 0.722 656 249 593 6;
  • 7) 0.722 656 249 593 6 × 2 = 1 + 0.445 312 499 187 2;
  • 8) 0.445 312 499 187 2 × 2 = 0 + 0.890 624 998 374 4;
  • 9) 0.890 624 998 374 4 × 2 = 1 + 0.781 249 996 748 8;
  • 10) 0.781 249 996 748 8 × 2 = 1 + 0.562 499 993 497 6;
  • 11) 0.562 499 993 497 6 × 2 = 1 + 0.124 999 986 995 2;
  • 12) 0.124 999 986 995 2 × 2 = 0 + 0.249 999 973 990 4;
  • 13) 0.249 999 973 990 4 × 2 = 0 + 0.499 999 947 980 8;
  • 14) 0.499 999 947 980 8 × 2 = 0 + 0.999 999 895 961 6;
  • 15) 0.999 999 895 961 6 × 2 = 1 + 0.999 999 791 923 2;
  • 16) 0.999 999 791 923 2 × 2 = 1 + 0.999 999 583 846 4;
  • 17) 0.999 999 583 846 4 × 2 = 1 + 0.999 999 167 692 8;
  • 18) 0.999 999 167 692 8 × 2 = 1 + 0.999 998 335 385 6;
  • 19) 0.999 998 335 385 6 × 2 = 1 + 0.999 996 670 771 2;
  • 20) 0.999 996 670 771 2 × 2 = 1 + 0.999 993 341 542 4;
  • 21) 0.999 993 341 542 4 × 2 = 1 + 0.999 986 683 084 8;
  • 22) 0.999 986 683 084 8 × 2 = 1 + 0.999 973 366 169 6;
  • 23) 0.999 973 366 169 6 × 2 = 1 + 0.999 946 732 339 2;
  • 24) 0.999 946 732 339 2 × 2 = 1 + 0.999 893 464 678 4;
  • 25) 0.999 893 464 678 4 × 2 = 1 + 0.999 786 929 356 8;
  • 26) 0.999 786 929 356 8 × 2 = 1 + 0.999 573 858 713 6;
  • 27) 0.999 573 858 713 6 × 2 = 1 + 0.999 147 717 427 2;
  • 28) 0.999 147 717 427 2 × 2 = 1 + 0.998 295 434 854 4;
  • 29) 0.998 295 434 854 4 × 2 = 1 + 0.996 590 869 708 8;
  • 30) 0.996 590 869 708 8 × 2 = 1 + 0.993 181 739 417 6;
  • 31) 0.993 181 739 417 6 × 2 = 1 + 0.986 363 478 835 2;
  • 32) 0.986 363 478 835 2 × 2 = 1 + 0.972 726 957 670 4;
  • 33) 0.972 726 957 670 4 × 2 = 1 + 0.945 453 915 340 8;
  • 34) 0.945 453 915 340 8 × 2 = 1 + 0.890 907 830 681 6;
  • 35) 0.890 907 830 681 6 × 2 = 1 + 0.781 815 661 363 2;
  • 36) 0.781 815 661 363 2 × 2 = 1 + 0.563 631 322 726 4;
  • 37) 0.563 631 322 726 4 × 2 = 1 + 0.127 262 645 452 8;
  • 38) 0.127 262 645 452 8 × 2 = 0 + 0.254 525 290 905 6;
  • 39) 0.254 525 290 905 6 × 2 = 0 + 0.509 050 581 811 2;
  • 40) 0.509 050 581 811 2 × 2 = 1 + 0.018 101 163 622 4;
  • 41) 0.018 101 163 622 4 × 2 = 0 + 0.036 202 327 244 8;
  • 42) 0.036 202 327 244 8 × 2 = 0 + 0.072 404 654 489 6;
  • 43) 0.072 404 654 489 6 × 2 = 0 + 0.144 809 308 979 2;
  • 44) 0.144 809 308 979 2 × 2 = 0 + 0.289 618 617 958 4;
  • 45) 0.289 618 617 958 4 × 2 = 0 + 0.579 237 235 916 8;
  • 46) 0.579 237 235 916 8 × 2 = 1 + 0.158 474 471 833 6;
  • 47) 0.158 474 471 833 6 × 2 = 0 + 0.316 948 943 667 2;
  • 48) 0.316 948 943 667 2 × 2 = 0 + 0.633 897 887 334 4;
  • 49) 0.633 897 887 334 4 × 2 = 1 + 0.267 795 774 668 8;
  • 50) 0.267 795 774 668 8 × 2 = 0 + 0.535 591 549 337 6;
  • 51) 0.535 591 549 337 6 × 2 = 1 + 0.071 183 098 675 2;
  • 52) 0.071 183 098 675 2 × 2 = 0 + 0.142 366 197 350 4;
  • 53) 0.142 366 197 350 4 × 2 = 0 + 0.284 732 394 700 8;
  • 54) 0.284 732 394 700 8 × 2 = 0 + 0.569 464 789 401 6;
  • 55) 0.569 464 789 401 6 × 2 = 1 + 0.138 929 578 803 2;
  • 56) 0.138 929 578 803 2 × 2 = 0 + 0.277 859 157 606 4;
  • 57) 0.277 859 157 606 4 × 2 = 0 + 0.555 718 315 212 8;
  • 58) 0.555 718 315 212 8 × 2 = 1 + 0.111 436 630 425 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:


0.026 916 503 899 9(10) =


0.0000 0110 1110 0011 1111 1111 1111 1111 1111 1001 0000 0100 1010 0010 01(2)

5. Positive number before normalization:

0.026 916 503 899 9(10) =


0.0000 0110 1110 0011 1111 1111 1111 1111 1111 1001 0000 0100 1010 0010 01(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 6 positions to the right, so that only one non zero digit remains to the left of it:


0.026 916 503 899 9(10) =


0.0000 0110 1110 0011 1111 1111 1111 1111 1111 1001 0000 0100 1010 0010 01(2) =


0.0000 0110 1110 0011 1111 1111 1111 1111 1111 1001 0000 0100 1010 0010 01(2) × 20 =


1.1011 1000 1111 1111 1111 1111 1111 1110 0100 0001 0010 1000 1001(2) × 2-6


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): -6


Mantissa (not normalized):
1.1011 1000 1111 1111 1111 1111 1111 1110 0100 0001 0010 1000 1001


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-6 + 2(11-1) - 1 =


(-6 + 1 023)(10) =


1 017(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;
  • 1 017 ÷ 2 = 508 + 1;
  • 508 ÷ 2 = 254 + 0;
  • 254 ÷ 2 = 127 + 0;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


1017(10) =


011 1111 1001(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, only if necessary (not the case here).


Mantissa (normalized) =


1. 1011 1000 1111 1111 1111 1111 1111 1110 0100 0001 0010 1000 1001 =


1011 1000 1111 1111 1111 1111 1111 1110 0100 0001 0010 1000 1001


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) =
011 1111 1001


Mantissa (52 bits) =
1011 1000 1111 1111 1111 1111 1111 1110 0100 0001 0010 1000 1001


Decimal number 0.026 916 503 899 9 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1001 - 1011 1000 1111 1111 1111 1111 1111 1110 0100 0001 0010 1000 1001


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