14 897.799 651 568 84 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 14 897.799 651 568 84(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
14 897.799 651 568 84(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: 14 897.
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;
  • 14 897 ÷ 2 = 7 448 + 1;
  • 7 448 ÷ 2 = 3 724 + 0;
  • 3 724 ÷ 2 = 1 862 + 0;
  • 1 862 ÷ 2 = 931 + 0;
  • 931 ÷ 2 = 465 + 1;
  • 465 ÷ 2 = 232 + 1;
  • 232 ÷ 2 = 116 + 0;
  • 116 ÷ 2 = 58 + 0;
  • 58 ÷ 2 = 29 + 0;
  • 29 ÷ 2 = 14 + 1;
  • 14 ÷ 2 = 7 + 0;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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.

14 897(10) =


11 1010 0011 0001(2)


3. Convert to binary (base 2) the fractional part: 0.799 651 568 84.

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) 0.799 651 568 84 × 2 = 1 + 0.599 303 137 68;
  • 2) 0.599 303 137 68 × 2 = 1 + 0.198 606 275 36;
  • 3) 0.198 606 275 36 × 2 = 0 + 0.397 212 550 72;
  • 4) 0.397 212 550 72 × 2 = 0 + 0.794 425 101 44;
  • 5) 0.794 425 101 44 × 2 = 1 + 0.588 850 202 88;
  • 6) 0.588 850 202 88 × 2 = 1 + 0.177 700 405 76;
  • 7) 0.177 700 405 76 × 2 = 0 + 0.355 400 811 52;
  • 8) 0.355 400 811 52 × 2 = 0 + 0.710 801 623 04;
  • 9) 0.710 801 623 04 × 2 = 1 + 0.421 603 246 08;
  • 10) 0.421 603 246 08 × 2 = 0 + 0.843 206 492 16;
  • 11) 0.843 206 492 16 × 2 = 1 + 0.686 412 984 32;
  • 12) 0.686 412 984 32 × 2 = 1 + 0.372 825 968 64;
  • 13) 0.372 825 968 64 × 2 = 0 + 0.745 651 937 28;
  • 14) 0.745 651 937 28 × 2 = 1 + 0.491 303 874 56;
  • 15) 0.491 303 874 56 × 2 = 0 + 0.982 607 749 12;
  • 16) 0.982 607 749 12 × 2 = 1 + 0.965 215 498 24;
  • 17) 0.965 215 498 24 × 2 = 1 + 0.930 430 996 48;
  • 18) 0.930 430 996 48 × 2 = 1 + 0.860 861 992 96;
  • 19) 0.860 861 992 96 × 2 = 1 + 0.721 723 985 92;
  • 20) 0.721 723 985 92 × 2 = 1 + 0.443 447 971 84;
  • 21) 0.443 447 971 84 × 2 = 0 + 0.886 895 943 68;
  • 22) 0.886 895 943 68 × 2 = 1 + 0.773 791 887 36;
  • 23) 0.773 791 887 36 × 2 = 1 + 0.547 583 774 72;
  • 24) 0.547 583 774 72 × 2 = 1 + 0.095 167 549 44;
  • 25) 0.095 167 549 44 × 2 = 0 + 0.190 335 098 88;
  • 26) 0.190 335 098 88 × 2 = 0 + 0.380 670 197 76;
  • 27) 0.380 670 197 76 × 2 = 0 + 0.761 340 395 52;
  • 28) 0.761 340 395 52 × 2 = 1 + 0.522 680 791 04;
  • 29) 0.522 680 791 04 × 2 = 1 + 0.045 361 582 08;
  • 30) 0.045 361 582 08 × 2 = 0 + 0.090 723 164 16;
  • 31) 0.090 723 164 16 × 2 = 0 + 0.181 446 328 32;
  • 32) 0.181 446 328 32 × 2 = 0 + 0.362 892 656 64;
  • 33) 0.362 892 656 64 × 2 = 0 + 0.725 785 313 28;
  • 34) 0.725 785 313 28 × 2 = 1 + 0.451 570 626 56;
  • 35) 0.451 570 626 56 × 2 = 0 + 0.903 141 253 12;
  • 36) 0.903 141 253 12 × 2 = 1 + 0.806 282 506 24;
  • 37) 0.806 282 506 24 × 2 = 1 + 0.612 565 012 48;
  • 38) 0.612 565 012 48 × 2 = 1 + 0.225 130 024 96;
  • 39) 0.225 130 024 96 × 2 = 0 + 0.450 260 049 92;
  • 40) 0.450 260 049 92 × 2 = 0 + 0.900 520 099 84;
  • 41) 0.900 520 099 84 × 2 = 1 + 0.801 040 199 68;
  • 42) 0.801 040 199 68 × 2 = 1 + 0.602 080 399 36;
  • 43) 0.602 080 399 36 × 2 = 1 + 0.204 160 798 72;
  • 44) 0.204 160 798 72 × 2 = 0 + 0.408 321 597 44;
  • 45) 0.408 321 597 44 × 2 = 0 + 0.816 643 194 88;
  • 46) 0.816 643 194 88 × 2 = 1 + 0.633 286 389 76;
  • 47) 0.633 286 389 76 × 2 = 1 + 0.266 572 779 52;
  • 48) 0.266 572 779 52 × 2 = 0 + 0.533 145 559 04;
  • 49) 0.533 145 559 04 × 2 = 1 + 0.066 291 118 08;
  • 50) 0.066 291 118 08 × 2 = 0 + 0.132 582 236 16;
  • 51) 0.132 582 236 16 × 2 = 0 + 0.265 164 472 32;
  • 52) 0.265 164 472 32 × 2 = 0 + 0.530 328 944 64;
  • 53) 0.530 328 944 64 × 2 = 1 + 0.060 657 889 28;

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:


0.799 651 568 84(10) =


0.1100 1100 1011 0101 1111 0111 0001 1000 0101 1100 1110 0110 1000 1(2)

5. Positive number before normalization:

14 897.799 651 568 84(10) =


11 1010 0011 0001.1100 1100 1011 0101 1111 0111 0001 1000 0101 1100 1110 0110 1000 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 13 positions to the left, so that only one non zero digit remains to the left of it:


14 897.799 651 568 84(10) =


11 1010 0011 0001.1100 1100 1011 0101 1111 0111 0001 1000 0101 1100 1110 0110 1000 1(2) =


11 1010 0011 0001.1100 1100 1011 0101 1111 0111 0001 1000 0101 1100 1110 0110 1000 1(2) × 20 =


1.1101 0001 1000 1110 0110 0101 1010 1111 1011 1000 1100 0010 1110 0111 0011 0100 01(2) × 213


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): 13


Mantissa (not normalized):
1.1101 0001 1000 1110 0110 0101 1010 1111 1011 1000 1100 0010 1110 0111 0011 0100 01


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


13 + 2(11-1) - 1 =


(13 + 1 023)(10) =


1 036(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;
  • 1 036 ÷ 2 = 518 + 0;
  • 518 ÷ 2 = 259 + 0;
  • 259 ÷ 2 = 129 + 1;
  • 129 ÷ 2 = 64 + 1;
  • 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) =


1036(10) =


100 0000 1100(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. 1101 0001 1000 1110 0110 0101 1010 1111 1011 1000 1100 0010 1110 01 1100 1101 0001 =


1101 0001 1000 1110 0110 0101 1010 1111 1011 1000 1100 0010 1110


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 1100


Mantissa (52 bits) =
1101 0001 1000 1110 0110 0101 1010 1111 1011 1000 1100 0010 1110


Decimal number 14 897.799 651 568 84 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1100 - 1101 0001 1000 1110 0110 0101 1010 1111 1011 1000 1100 0010 1110


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