0.974 013 318 541 486 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 318 541 486(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
0.974 013 318 541 486(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: 0.974 013 318 541 486.

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) 0.974 013 318 541 486 × 2 = 1 + 0.948 026 637 082 972;
  • 2) 0.948 026 637 082 972 × 2 = 1 + 0.896 053 274 165 944;
  • 3) 0.896 053 274 165 944 × 2 = 1 + 0.792 106 548 331 888;
  • 4) 0.792 106 548 331 888 × 2 = 1 + 0.584 213 096 663 776;
  • 5) 0.584 213 096 663 776 × 2 = 1 + 0.168 426 193 327 552;
  • 6) 0.168 426 193 327 552 × 2 = 0 + 0.336 852 386 655 104;
  • 7) 0.336 852 386 655 104 × 2 = 0 + 0.673 704 773 310 208;
  • 8) 0.673 704 773 310 208 × 2 = 1 + 0.347 409 546 620 416;
  • 9) 0.347 409 546 620 416 × 2 = 0 + 0.694 819 093 240 832;
  • 10) 0.694 819 093 240 832 × 2 = 1 + 0.389 638 186 481 664;
  • 11) 0.389 638 186 481 664 × 2 = 0 + 0.779 276 372 963 328;
  • 12) 0.779 276 372 963 328 × 2 = 1 + 0.558 552 745 926 656;
  • 13) 0.558 552 745 926 656 × 2 = 1 + 0.117 105 491 853 312;
  • 14) 0.117 105 491 853 312 × 2 = 0 + 0.234 210 983 706 624;
  • 15) 0.234 210 983 706 624 × 2 = 0 + 0.468 421 967 413 248;
  • 16) 0.468 421 967 413 248 × 2 = 0 + 0.936 843 934 826 496;
  • 17) 0.936 843 934 826 496 × 2 = 1 + 0.873 687 869 652 992;
  • 18) 0.873 687 869 652 992 × 2 = 1 + 0.747 375 739 305 984;
  • 19) 0.747 375 739 305 984 × 2 = 1 + 0.494 751 478 611 968;
  • 20) 0.494 751 478 611 968 × 2 = 0 + 0.989 502 957 223 936;
  • 21) 0.989 502 957 223 936 × 2 = 1 + 0.979 005 914 447 872;
  • 22) 0.979 005 914 447 872 × 2 = 1 + 0.958 011 828 895 744;
  • 23) 0.958 011 828 895 744 × 2 = 1 + 0.916 023 657 791 488;
  • 24) 0.916 023 657 791 488 × 2 = 1 + 0.832 047 315 582 976;
  • 25) 0.832 047 315 582 976 × 2 = 1 + 0.664 094 631 165 952;
  • 26) 0.664 094 631 165 952 × 2 = 1 + 0.328 189 262 331 904;
  • 27) 0.328 189 262 331 904 × 2 = 0 + 0.656 378 524 663 808;
  • 28) 0.656 378 524 663 808 × 2 = 1 + 0.312 757 049 327 616;
  • 29) 0.312 757 049 327 616 × 2 = 0 + 0.625 514 098 655 232;
  • 30) 0.625 514 098 655 232 × 2 = 1 + 0.251 028 197 310 464;
  • 31) 0.251 028 197 310 464 × 2 = 0 + 0.502 056 394 620 928;
  • 32) 0.502 056 394 620 928 × 2 = 1 + 0.004 112 789 241 856;
  • 33) 0.004 112 789 241 856 × 2 = 0 + 0.008 225 578 483 712;
  • 34) 0.008 225 578 483 712 × 2 = 0 + 0.016 451 156 967 424;
  • 35) 0.016 451 156 967 424 × 2 = 0 + 0.032 902 313 934 848;
  • 36) 0.032 902 313 934 848 × 2 = 0 + 0.065 804 627 869 696;
  • 37) 0.065 804 627 869 696 × 2 = 0 + 0.131 609 255 739 392;
  • 38) 0.131 609 255 739 392 × 2 = 0 + 0.263 218 511 478 784;
  • 39) 0.263 218 511 478 784 × 2 = 0 + 0.526 437 022 957 568;
  • 40) 0.526 437 022 957 568 × 2 = 1 + 0.052 874 045 915 136;
  • 41) 0.052 874 045 915 136 × 2 = 0 + 0.105 748 091 830 272;
  • 42) 0.105 748 091 830 272 × 2 = 0 + 0.211 496 183 660 544;
  • 43) 0.211 496 183 660 544 × 2 = 0 + 0.422 992 367 321 088;
  • 44) 0.422 992 367 321 088 × 2 = 0 + 0.845 984 734 642 176;
  • 45) 0.845 984 734 642 176 × 2 = 1 + 0.691 969 469 284 352;
  • 46) 0.691 969 469 284 352 × 2 = 1 + 0.383 938 938 568 704;
  • 47) 0.383 938 938 568 704 × 2 = 0 + 0.767 877 877 137 408;
  • 48) 0.767 877 877 137 408 × 2 = 1 + 0.535 755 754 274 816;
  • 49) 0.535 755 754 274 816 × 2 = 1 + 0.071 511 508 549 632;
  • 50) 0.071 511 508 549 632 × 2 = 0 + 0.143 023 017 099 264;
  • 51) 0.143 023 017 099 264 × 2 = 0 + 0.286 046 034 198 528;
  • 52) 0.286 046 034 198 528 × 2 = 0 + 0.572 092 068 397 056;
  • 53) 0.572 092 068 397 056 × 2 = 1 + 0.144 184 136 794 112;

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:


0.974 013 318 541 486(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0000 1101 1000 1(2)

5. Positive number before normalization:

0.974 013 318 541 486(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0000 1101 1000 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:


0.974 013 318 541 486(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0000 1101 1000 1(2) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0000 1101 1000 1(2) × 20 =


1.1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0001 1011 0001(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 1101 1111 1010 1010 0000 0010 0001 1011 0001


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 1101 1111 1010 1010 0000 0010 0001 1011 0001 =


1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0001 1011 0001


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 1101 1111 1010 1010 0000 0010 0001 1011 0001


Decimal number 0.974 013 318 541 486 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1110 - 1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0001 1011 0001


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