0.974 013 329 7 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 329 7(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
0.974 013 329 7(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: 0.974 013 329 7.

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) 0.974 013 329 7 × 2 = 1 + 0.948 026 659 4;
  • 2) 0.948 026 659 4 × 2 = 1 + 0.896 053 318 8;
  • 3) 0.896 053 318 8 × 2 = 1 + 0.792 106 637 6;
  • 4) 0.792 106 637 6 × 2 = 1 + 0.584 213 275 2;
  • 5) 0.584 213 275 2 × 2 = 1 + 0.168 426 550 4;
  • 6) 0.168 426 550 4 × 2 = 0 + 0.336 853 100 8;
  • 7) 0.336 853 100 8 × 2 = 0 + 0.673 706 201 6;
  • 8) 0.673 706 201 6 × 2 = 1 + 0.347 412 403 2;
  • 9) 0.347 412 403 2 × 2 = 0 + 0.694 824 806 4;
  • 10) 0.694 824 806 4 × 2 = 1 + 0.389 649 612 8;
  • 11) 0.389 649 612 8 × 2 = 0 + 0.779 299 225 6;
  • 12) 0.779 299 225 6 × 2 = 1 + 0.558 598 451 2;
  • 13) 0.558 598 451 2 × 2 = 1 + 0.117 196 902 4;
  • 14) 0.117 196 902 4 × 2 = 0 + 0.234 393 804 8;
  • 15) 0.234 393 804 8 × 2 = 0 + 0.468 787 609 6;
  • 16) 0.468 787 609 6 × 2 = 0 + 0.937 575 219 2;
  • 17) 0.937 575 219 2 × 2 = 1 + 0.875 150 438 4;
  • 18) 0.875 150 438 4 × 2 = 1 + 0.750 300 876 8;
  • 19) 0.750 300 876 8 × 2 = 1 + 0.500 601 753 6;
  • 20) 0.500 601 753 6 × 2 = 1 + 0.001 203 507 2;
  • 21) 0.001 203 507 2 × 2 = 0 + 0.002 407 014 4;
  • 22) 0.002 407 014 4 × 2 = 0 + 0.004 814 028 8;
  • 23) 0.004 814 028 8 × 2 = 0 + 0.009 628 057 6;
  • 24) 0.009 628 057 6 × 2 = 0 + 0.019 256 115 2;
  • 25) 0.019 256 115 2 × 2 = 0 + 0.038 512 230 4;
  • 26) 0.038 512 230 4 × 2 = 0 + 0.077 024 460 8;
  • 27) 0.077 024 460 8 × 2 = 0 + 0.154 048 921 6;
  • 28) 0.154 048 921 6 × 2 = 0 + 0.308 097 843 2;
  • 29) 0.308 097 843 2 × 2 = 0 + 0.616 195 686 4;
  • 30) 0.616 195 686 4 × 2 = 1 + 0.232 391 372 8;
  • 31) 0.232 391 372 8 × 2 = 0 + 0.464 782 745 6;
  • 32) 0.464 782 745 6 × 2 = 0 + 0.929 565 491 2;
  • 33) 0.929 565 491 2 × 2 = 1 + 0.859 130 982 4;
  • 34) 0.859 130 982 4 × 2 = 1 + 0.718 261 964 8;
  • 35) 0.718 261 964 8 × 2 = 1 + 0.436 523 929 6;
  • 36) 0.436 523 929 6 × 2 = 0 + 0.873 047 859 2;
  • 37) 0.873 047 859 2 × 2 = 1 + 0.746 095 718 4;
  • 38) 0.746 095 718 4 × 2 = 1 + 0.492 191 436 8;
  • 39) 0.492 191 436 8 × 2 = 0 + 0.984 382 873 6;
  • 40) 0.984 382 873 6 × 2 = 1 + 0.968 765 747 2;
  • 41) 0.968 765 747 2 × 2 = 1 + 0.937 531 494 4;
  • 42) 0.937 531 494 4 × 2 = 1 + 0.875 062 988 8;
  • 43) 0.875 062 988 8 × 2 = 1 + 0.750 125 977 6;
  • 44) 0.750 125 977 6 × 2 = 1 + 0.500 251 955 2;
  • 45) 0.500 251 955 2 × 2 = 1 + 0.000 503 910 4;
  • 46) 0.000 503 910 4 × 2 = 0 + 0.001 007 820 8;
  • 47) 0.001 007 820 8 × 2 = 0 + 0.002 015 641 6;
  • 48) 0.002 015 641 6 × 2 = 0 + 0.004 031 283 2;
  • 49) 0.004 031 283 2 × 2 = 0 + 0.008 062 566 4;
  • 50) 0.008 062 566 4 × 2 = 0 + 0.016 125 132 8;
  • 51) 0.016 125 132 8 × 2 = 0 + 0.032 250 265 6;
  • 52) 0.032 250 265 6 × 2 = 0 + 0.064 500 531 2;
  • 53) 0.064 500 531 2 × 2 = 0 + 0.129 001 062 4;

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:


0.974 013 329 7(10) =


0.1111 1001 0101 1000 1111 0000 0000 0100 1110 1101 1111 1000 0000 0(2)

5. Positive number before normalization:

0.974 013 329 7(10) =


0.1111 1001 0101 1000 1111 0000 0000 0100 1110 1101 1111 1000 0000 0(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:


0.974 013 329 7(10) =


0.1111 1001 0101 1000 1111 0000 0000 0100 1110 1101 1111 1000 0000 0(2) =


0.1111 1001 0101 1000 1111 0000 0000 0100 1110 1101 1111 1000 0000 0(2) × 20 =


1.1111 0010 1011 0001 1110 0000 0000 1001 1101 1011 1111 0000 0000(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 0000 1001 1101 1011 1111 0000 0000


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 0000 1001 1101 1011 1111 0000 0000 =


1111 0010 1011 0001 1110 0000 0000 1001 1101 1011 1111 0000 0000


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 0000 1001 1101 1011 1111 0000 0000


Decimal number 0.974 013 329 7 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1110 - 1111 0010 1011 0001 1110 0000 0000 1001 1101 1011 1111 0000 0000


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