0.000 053 174 92 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.000 053 174 92(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
0.000 053 174 92(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: 0.000 053 174 92.

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) 0.000 053 174 92 × 2 = 0 + 0.000 106 349 84;
  • 2) 0.000 106 349 84 × 2 = 0 + 0.000 212 699 68;
  • 3) 0.000 212 699 68 × 2 = 0 + 0.000 425 399 36;
  • 4) 0.000 425 399 36 × 2 = 0 + 0.000 850 798 72;
  • 5) 0.000 850 798 72 × 2 = 0 + 0.001 701 597 44;
  • 6) 0.001 701 597 44 × 2 = 0 + 0.003 403 194 88;
  • 7) 0.003 403 194 88 × 2 = 0 + 0.006 806 389 76;
  • 8) 0.006 806 389 76 × 2 = 0 + 0.013 612 779 52;
  • 9) 0.013 612 779 52 × 2 = 0 + 0.027 225 559 04;
  • 10) 0.027 225 559 04 × 2 = 0 + 0.054 451 118 08;
  • 11) 0.054 451 118 08 × 2 = 0 + 0.108 902 236 16;
  • 12) 0.108 902 236 16 × 2 = 0 + 0.217 804 472 32;
  • 13) 0.217 804 472 32 × 2 = 0 + 0.435 608 944 64;
  • 14) 0.435 608 944 64 × 2 = 0 + 0.871 217 889 28;
  • 15) 0.871 217 889 28 × 2 = 1 + 0.742 435 778 56;
  • 16) 0.742 435 778 56 × 2 = 1 + 0.484 871 557 12;
  • 17) 0.484 871 557 12 × 2 = 0 + 0.969 743 114 24;
  • 18) 0.969 743 114 24 × 2 = 1 + 0.939 486 228 48;
  • 19) 0.939 486 228 48 × 2 = 1 + 0.878 972 456 96;
  • 20) 0.878 972 456 96 × 2 = 1 + 0.757 944 913 92;
  • 21) 0.757 944 913 92 × 2 = 1 + 0.515 889 827 84;
  • 22) 0.515 889 827 84 × 2 = 1 + 0.031 779 655 68;
  • 23) 0.031 779 655 68 × 2 = 0 + 0.063 559 311 36;
  • 24) 0.063 559 311 36 × 2 = 0 + 0.127 118 622 72;
  • 25) 0.127 118 622 72 × 2 = 0 + 0.254 237 245 44;
  • 26) 0.254 237 245 44 × 2 = 0 + 0.508 474 490 88;
  • 27) 0.508 474 490 88 × 2 = 1 + 0.016 948 981 76;
  • 28) 0.016 948 981 76 × 2 = 0 + 0.033 897 963 52;
  • 29) 0.033 897 963 52 × 2 = 0 + 0.067 795 927 04;
  • 30) 0.067 795 927 04 × 2 = 0 + 0.135 591 854 08;
  • 31) 0.135 591 854 08 × 2 = 0 + 0.271 183 708 16;
  • 32) 0.271 183 708 16 × 2 = 0 + 0.542 367 416 32;
  • 33) 0.542 367 416 32 × 2 = 1 + 0.084 734 832 64;
  • 34) 0.084 734 832 64 × 2 = 0 + 0.169 469 665 28;
  • 35) 0.169 469 665 28 × 2 = 0 + 0.338 939 330 56;
  • 36) 0.338 939 330 56 × 2 = 0 + 0.677 878 661 12;
  • 37) 0.677 878 661 12 × 2 = 1 + 0.355 757 322 24;
  • 38) 0.355 757 322 24 × 2 = 0 + 0.711 514 644 48;
  • 39) 0.711 514 644 48 × 2 = 1 + 0.423 029 288 96;
  • 40) 0.423 029 288 96 × 2 = 0 + 0.846 058 577 92;
  • 41) 0.846 058 577 92 × 2 = 1 + 0.692 117 155 84;
  • 42) 0.692 117 155 84 × 2 = 1 + 0.384 234 311 68;
  • 43) 0.384 234 311 68 × 2 = 0 + 0.768 468 623 36;
  • 44) 0.768 468 623 36 × 2 = 1 + 0.536 937 246 72;
  • 45) 0.536 937 246 72 × 2 = 1 + 0.073 874 493 44;
  • 46) 0.073 874 493 44 × 2 = 0 + 0.147 748 986 88;
  • 47) 0.147 748 986 88 × 2 = 0 + 0.295 497 973 76;
  • 48) 0.295 497 973 76 × 2 = 0 + 0.590 995 947 52;
  • 49) 0.590 995 947 52 × 2 = 1 + 0.181 991 895 04;
  • 50) 0.181 991 895 04 × 2 = 0 + 0.363 983 790 08;
  • 51) 0.363 983 790 08 × 2 = 0 + 0.727 967 580 16;
  • 52) 0.727 967 580 16 × 2 = 1 + 0.455 935 160 32;
  • 53) 0.455 935 160 32 × 2 = 0 + 0.911 870 320 64;
  • 54) 0.911 870 320 64 × 2 = 1 + 0.823 740 641 28;
  • 55) 0.823 740 641 28 × 2 = 1 + 0.647 481 282 56;
  • 56) 0.647 481 282 56 × 2 = 1 + 0.294 962 565 12;
  • 57) 0.294 962 565 12 × 2 = 0 + 0.589 925 130 24;
  • 58) 0.589 925 130 24 × 2 = 1 + 0.179 850 260 48;
  • 59) 0.179 850 260 48 × 2 = 0 + 0.359 700 520 96;
  • 60) 0.359 700 520 96 × 2 = 0 + 0.719 401 041 92;
  • 61) 0.719 401 041 92 × 2 = 1 + 0.438 802 083 84;
  • 62) 0.438 802 083 84 × 2 = 0 + 0.877 604 167 68;
  • 63) 0.877 604 167 68 × 2 = 1 + 0.755 208 335 36;
  • 64) 0.755 208 335 36 × 2 = 1 + 0.510 416 670 72;
  • 65) 0.510 416 670 72 × 2 = 1 + 0.020 833 341 44;
  • 66) 0.020 833 341 44 × 2 = 0 + 0.041 666 682 88;
  • 67) 0.041 666 682 88 × 2 = 0 + 0.083 333 365 76;

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:


0.000 053 174 92(10) =


0.0000 0000 0000 0011 0111 1100 0010 0000 1000 1010 1101 1000 1001 0111 0100 1011 100(2)

5. Positive number before normalization:

0.000 053 174 92(10) =


0.0000 0000 0000 0011 0111 1100 0010 0000 1000 1010 1101 1000 1001 0111 0100 1011 100(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 15 positions to the right, so that only one non zero digit remains to the left of it:


0.000 053 174 92(10) =


0.0000 0000 0000 0011 0111 1100 0010 0000 1000 1010 1101 1000 1001 0111 0100 1011 100(2) =


0.0000 0000 0000 0011 0111 1100 0010 0000 1000 1010 1101 1000 1001 0111 0100 1011 100(2) × 20 =


1.1011 1110 0001 0000 0100 0101 0110 1100 0100 1011 1010 0101 1100(2) × 2-15


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): -15


Mantissa (not normalized):
1.1011 1110 0001 0000 0100 0101 0110 1100 0100 1011 1010 0101 1100


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-15 + 2(11-1) - 1 =


(-15 + 1 023)(10) =


1 008(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;
  • 1 008 ÷ 2 = 504 + 0;
  • 504 ÷ 2 = 252 + 0;
  • 252 ÷ 2 = 126 + 0;
  • 126 ÷ 2 = 63 + 0;
  • 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) =


1008(10) =


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


Mantissa (normalized) =


1. 1011 1110 0001 0000 0100 0101 0110 1100 0100 1011 1010 0101 1100 =


1011 1110 0001 0000 0100 0101 0110 1100 0100 1011 1010 0101 1100


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 0000


Mantissa (52 bits) =
1011 1110 0001 0000 0100 0101 0110 1100 0100 1011 1010 0101 1100


Decimal number 0.000 053 174 92 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 0000 - 1011 1110 0001 0000 0100 0101 0110 1100 0100 1011 1010 0101 1100

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