0.974 013 333 6 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 333 6(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
0.974 013 333 6(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: 0.974 013 333 6.

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) 0.974 013 333 6 × 2 = 1 + 0.948 026 667 2;
  • 2) 0.948 026 667 2 × 2 = 1 + 0.896 053 334 4;
  • 3) 0.896 053 334 4 × 2 = 1 + 0.792 106 668 8;
  • 4) 0.792 106 668 8 × 2 = 1 + 0.584 213 337 6;
  • 5) 0.584 213 337 6 × 2 = 1 + 0.168 426 675 2;
  • 6) 0.168 426 675 2 × 2 = 0 + 0.336 853 350 4;
  • 7) 0.336 853 350 4 × 2 = 0 + 0.673 706 700 8;
  • 8) 0.673 706 700 8 × 2 = 1 + 0.347 413 401 6;
  • 9) 0.347 413 401 6 × 2 = 0 + 0.694 826 803 2;
  • 10) 0.694 826 803 2 × 2 = 1 + 0.389 653 606 4;
  • 11) 0.389 653 606 4 × 2 = 0 + 0.779 307 212 8;
  • 12) 0.779 307 212 8 × 2 = 1 + 0.558 614 425 6;
  • 13) 0.558 614 425 6 × 2 = 1 + 0.117 228 851 2;
  • 14) 0.117 228 851 2 × 2 = 0 + 0.234 457 702 4;
  • 15) 0.234 457 702 4 × 2 = 0 + 0.468 915 404 8;
  • 16) 0.468 915 404 8 × 2 = 0 + 0.937 830 809 6;
  • 17) 0.937 830 809 6 × 2 = 1 + 0.875 661 619 2;
  • 18) 0.875 661 619 2 × 2 = 1 + 0.751 323 238 4;
  • 19) 0.751 323 238 4 × 2 = 1 + 0.502 646 476 8;
  • 20) 0.502 646 476 8 × 2 = 1 + 0.005 292 953 6;
  • 21) 0.005 292 953 6 × 2 = 0 + 0.010 585 907 2;
  • 22) 0.010 585 907 2 × 2 = 0 + 0.021 171 814 4;
  • 23) 0.021 171 814 4 × 2 = 0 + 0.042 343 628 8;
  • 24) 0.042 343 628 8 × 2 = 0 + 0.084 687 257 6;
  • 25) 0.084 687 257 6 × 2 = 0 + 0.169 374 515 2;
  • 26) 0.169 374 515 2 × 2 = 0 + 0.338 749 030 4;
  • 27) 0.338 749 030 4 × 2 = 0 + 0.677 498 060 8;
  • 28) 0.677 498 060 8 × 2 = 1 + 0.354 996 121 6;
  • 29) 0.354 996 121 6 × 2 = 0 + 0.709 992 243 2;
  • 30) 0.709 992 243 2 × 2 = 1 + 0.419 984 486 4;
  • 31) 0.419 984 486 4 × 2 = 0 + 0.839 968 972 8;
  • 32) 0.839 968 972 8 × 2 = 1 + 0.679 937 945 6;
  • 33) 0.679 937 945 6 × 2 = 1 + 0.359 875 891 2;
  • 34) 0.359 875 891 2 × 2 = 0 + 0.719 751 782 4;
  • 35) 0.719 751 782 4 × 2 = 1 + 0.439 503 564 8;
  • 36) 0.439 503 564 8 × 2 = 0 + 0.879 007 129 6;
  • 37) 0.879 007 129 6 × 2 = 1 + 0.758 014 259 2;
  • 38) 0.758 014 259 2 × 2 = 1 + 0.516 028 518 4;
  • 39) 0.516 028 518 4 × 2 = 1 + 0.032 057 036 8;
  • 40) 0.032 057 036 8 × 2 = 0 + 0.064 114 073 6;
  • 41) 0.064 114 073 6 × 2 = 0 + 0.128 228 147 2;
  • 42) 0.128 228 147 2 × 2 = 0 + 0.256 456 294 4;
  • 43) 0.256 456 294 4 × 2 = 0 + 0.512 912 588 8;
  • 44) 0.512 912 588 8 × 2 = 1 + 0.025 825 177 6;
  • 45) 0.025 825 177 6 × 2 = 0 + 0.051 650 355 2;
  • 46) 0.051 650 355 2 × 2 = 0 + 0.103 300 710 4;
  • 47) 0.103 300 710 4 × 2 = 0 + 0.206 601 420 8;
  • 48) 0.206 601 420 8 × 2 = 0 + 0.413 202 841 6;
  • 49) 0.413 202 841 6 × 2 = 0 + 0.826 405 683 2;
  • 50) 0.826 405 683 2 × 2 = 1 + 0.652 811 366 4;
  • 51) 0.652 811 366 4 × 2 = 1 + 0.305 622 732 8;
  • 52) 0.305 622 732 8 × 2 = 0 + 0.611 245 465 6;
  • 53) 0.611 245 465 6 × 2 = 1 + 0.222 490 931 2;

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:


0.974 013 333 6(10) =

0.1111 1001 0101 1000 1111 0000 0001 0101 1010 1110 0001 0000 0110 1(2)

5. Positive number before normalization:

0.974 013 333 6(10) =

0.1111 1001 0101 1000 1111 0000 0001 0101 1010 1110 0001 0000 0110 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 1 positions to the right, so that only one non zero digit remains to the left of it:


0.974 013 333 6(10) =

0.1111 1001 0101 1000 1111 0000 0001 0101 1010 1110 0001 0000 0110 1(2) =

0.1111 1001 0101 1000 1111 0000 0001 0101 1010 1110 0001 0000 0110 1(2) × 20 =

1.1111 0010 1011 0001 1110 0000 0010 1011 0101 1100 0010 0000 1101(2) × 2-1


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):
1.1111 0010 1011 0001 1110 0000 0010 1011 0101 1100 0010 0000 1101


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) =

1 022(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;
  • 1 022 ÷ 2 = 511 + 0;
  • 511 ÷ 2 = 255 + 1;
  • 255 ÷ 2 = 127 + 1;
  • 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) =

1022(10) =

011 1111 1110(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. 1111 0010 1011 0001 1110 0000 0010 1011 0101 1100 0010 0000 1101 =

1111 0010 1011 0001 1110 0000 0010 1011 0101 1100 0010 0000 1101


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 1110

Mantissa (52 bits) =
1111 0010 1011 0001 1110 0000 0010 1011 0101 1100 0010 0000 1101


Decimal number 0.974 013 333 6 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1110 - 1111 0010 1011 0001 1110 0000 0010 1011 0101 1100 0010 0000 1101

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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