47.540 588 363 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 47.540 588 363(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
47.540 588 363(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: 47.
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;
  • 47 ÷ 2 = 23 + 1;
  • 23 ÷ 2 = 11 + 1;
  • 11 ÷ 2 = 5 + 1;
  • 5 ÷ 2 = 2 + 1;
  • 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.

47(10) =


10 1111(2)


3. Convert to binary (base 2) the fractional part: 0.540 588 363.

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) 0.540 588 363 × 2 = 1 + 0.081 176 726;
  • 2) 0.081 176 726 × 2 = 0 + 0.162 353 452;
  • 3) 0.162 353 452 × 2 = 0 + 0.324 706 904;
  • 4) 0.324 706 904 × 2 = 0 + 0.649 413 808;
  • 5) 0.649 413 808 × 2 = 1 + 0.298 827 616;
  • 6) 0.298 827 616 × 2 = 0 + 0.597 655 232;
  • 7) 0.597 655 232 × 2 = 1 + 0.195 310 464;
  • 8) 0.195 310 464 × 2 = 0 + 0.390 620 928;
  • 9) 0.390 620 928 × 2 = 0 + 0.781 241 856;
  • 10) 0.781 241 856 × 2 = 1 + 0.562 483 712;
  • 11) 0.562 483 712 × 2 = 1 + 0.124 967 424;
  • 12) 0.124 967 424 × 2 = 0 + 0.249 934 848;
  • 13) 0.249 934 848 × 2 = 0 + 0.499 869 696;
  • 14) 0.499 869 696 × 2 = 0 + 0.999 739 392;
  • 15) 0.999 739 392 × 2 = 1 + 0.999 478 784;
  • 16) 0.999 478 784 × 2 = 1 + 0.998 957 568;
  • 17) 0.998 957 568 × 2 = 1 + 0.997 915 136;
  • 18) 0.997 915 136 × 2 = 1 + 0.995 830 272;
  • 19) 0.995 830 272 × 2 = 1 + 0.991 660 544;
  • 20) 0.991 660 544 × 2 = 1 + 0.983 321 088;
  • 21) 0.983 321 088 × 2 = 1 + 0.966 642 176;
  • 22) 0.966 642 176 × 2 = 1 + 0.933 284 352;
  • 23) 0.933 284 352 × 2 = 1 + 0.866 568 704;
  • 24) 0.866 568 704 × 2 = 1 + 0.733 137 408;
  • 25) 0.733 137 408 × 2 = 1 + 0.466 274 816;
  • 26) 0.466 274 816 × 2 = 0 + 0.932 549 632;
  • 27) 0.932 549 632 × 2 = 1 + 0.865 099 264;
  • 28) 0.865 099 264 × 2 = 1 + 0.730 198 528;
  • 29) 0.730 198 528 × 2 = 1 + 0.460 397 056;
  • 30) 0.460 397 056 × 2 = 0 + 0.920 794 112;
  • 31) 0.920 794 112 × 2 = 1 + 0.841 588 224;
  • 32) 0.841 588 224 × 2 = 1 + 0.683 176 448;
  • 33) 0.683 176 448 × 2 = 1 + 0.366 352 896;
  • 34) 0.366 352 896 × 2 = 0 + 0.732 705 792;
  • 35) 0.732 705 792 × 2 = 1 + 0.465 411 584;
  • 36) 0.465 411 584 × 2 = 0 + 0.930 823 168;
  • 37) 0.930 823 168 × 2 = 1 + 0.861 646 336;
  • 38) 0.861 646 336 × 2 = 1 + 0.723 292 672;
  • 39) 0.723 292 672 × 2 = 1 + 0.446 585 344;
  • 40) 0.446 585 344 × 2 = 0 + 0.893 170 688;
  • 41) 0.893 170 688 × 2 = 1 + 0.786 341 376;
  • 42) 0.786 341 376 × 2 = 1 + 0.572 682 752;
  • 43) 0.572 682 752 × 2 = 1 + 0.145 365 504;
  • 44) 0.145 365 504 × 2 = 0 + 0.290 731 008;
  • 45) 0.290 731 008 × 2 = 0 + 0.581 462 016;
  • 46) 0.581 462 016 × 2 = 1 + 0.162 924 032;
  • 47) 0.162 924 032 × 2 = 0 + 0.325 848 064;
  • 48) 0.325 848 064 × 2 = 0 + 0.651 696 128;
  • 49) 0.651 696 128 × 2 = 1 + 0.303 392 256;
  • 50) 0.303 392 256 × 2 = 0 + 0.606 784 512;
  • 51) 0.606 784 512 × 2 = 1 + 0.213 569 024;
  • 52) 0.213 569 024 × 2 = 0 + 0.427 138 048;
  • 53) 0.427 138 048 × 2 = 0 + 0.854 276 096;

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:


0.540 588 363(10) =


0.1000 1010 0110 0011 1111 1111 1011 1011 1010 1110 1110 0100 1010 0(2)

5. Positive number before normalization:

47.540 588 363(10) =


10 1111.1000 1010 0110 0011 1111 1111 1011 1011 1010 1110 1110 0100 1010 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 5 positions to the left, so that only one non zero digit remains to the left of it:


47.540 588 363(10) =


10 1111.1000 1010 0110 0011 1111 1111 1011 1011 1010 1110 1110 0100 1010 0(2) =


10 1111.1000 1010 0110 0011 1111 1111 1011 1011 1010 1110 1110 0100 1010 0(2) × 20 =


1.0111 1100 0101 0011 0001 1111 1111 1101 1101 1101 0111 0111 0010 0101 00(2) × 25


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): 5


Mantissa (not normalized):
1.0111 1100 0101 0011 0001 1111 1111 1101 1101 1101 0111 0111 0010 0101 00


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


5 + 2(11-1) - 1 =


(5 + 1 023)(10) =


1 028(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;
  • 1 028 ÷ 2 = 514 + 0;
  • 514 ÷ 2 = 257 + 0;
  • 257 ÷ 2 = 128 + 1;
  • 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) =


1028(10) =


100 0000 0100(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. 0111 1100 0101 0011 0001 1111 1111 1101 1101 1101 0111 0111 0010 01 0100 =


0111 1100 0101 0011 0001 1111 1111 1101 1101 1101 0111 0111 0010


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 0100


Mantissa (52 bits) =
0111 1100 0101 0011 0001 1111 1111 1101 1101 1101 0111 0111 0010


Decimal number 47.540 588 363 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0100 - 0111 1100 0101 0011 0001 1111 1111 1101 1101 1101 0111 0111 0010

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