0.974 013 318 541 656 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 318 541 656(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
0.974 013 318 541 656(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: 0.974 013 318 541 656.

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) 0.974 013 318 541 656 × 2 = 1 + 0.948 026 637 083 312;
  • 2) 0.948 026 637 083 312 × 2 = 1 + 0.896 053 274 166 624;
  • 3) 0.896 053 274 166 624 × 2 = 1 + 0.792 106 548 333 248;
  • 4) 0.792 106 548 333 248 × 2 = 1 + 0.584 213 096 666 496;
  • 5) 0.584 213 096 666 496 × 2 = 1 + 0.168 426 193 332 992;
  • 6) 0.168 426 193 332 992 × 2 = 0 + 0.336 852 386 665 984;
  • 7) 0.336 852 386 665 984 × 2 = 0 + 0.673 704 773 331 968;
  • 8) 0.673 704 773 331 968 × 2 = 1 + 0.347 409 546 663 936;
  • 9) 0.347 409 546 663 936 × 2 = 0 + 0.694 819 093 327 872;
  • 10) 0.694 819 093 327 872 × 2 = 1 + 0.389 638 186 655 744;
  • 11) 0.389 638 186 655 744 × 2 = 0 + 0.779 276 373 311 488;
  • 12) 0.779 276 373 311 488 × 2 = 1 + 0.558 552 746 622 976;
  • 13) 0.558 552 746 622 976 × 2 = 1 + 0.117 105 493 245 952;
  • 14) 0.117 105 493 245 952 × 2 = 0 + 0.234 210 986 491 904;
  • 15) 0.234 210 986 491 904 × 2 = 0 + 0.468 421 972 983 808;
  • 16) 0.468 421 972 983 808 × 2 = 0 + 0.936 843 945 967 616;
  • 17) 0.936 843 945 967 616 × 2 = 1 + 0.873 687 891 935 232;
  • 18) 0.873 687 891 935 232 × 2 = 1 + 0.747 375 783 870 464;
  • 19) 0.747 375 783 870 464 × 2 = 1 + 0.494 751 567 740 928;
  • 20) 0.494 751 567 740 928 × 2 = 0 + 0.989 503 135 481 856;
  • 21) 0.989 503 135 481 856 × 2 = 1 + 0.979 006 270 963 712;
  • 22) 0.979 006 270 963 712 × 2 = 1 + 0.958 012 541 927 424;
  • 23) 0.958 012 541 927 424 × 2 = 1 + 0.916 025 083 854 848;
  • 24) 0.916 025 083 854 848 × 2 = 1 + 0.832 050 167 709 696;
  • 25) 0.832 050 167 709 696 × 2 = 1 + 0.664 100 335 419 392;
  • 26) 0.664 100 335 419 392 × 2 = 1 + 0.328 200 670 838 784;
  • 27) 0.328 200 670 838 784 × 2 = 0 + 0.656 401 341 677 568;
  • 28) 0.656 401 341 677 568 × 2 = 1 + 0.312 802 683 355 136;
  • 29) 0.312 802 683 355 136 × 2 = 0 + 0.625 605 366 710 272;
  • 30) 0.625 605 366 710 272 × 2 = 1 + 0.251 210 733 420 544;
  • 31) 0.251 210 733 420 544 × 2 = 0 + 0.502 421 466 841 088;
  • 32) 0.502 421 466 841 088 × 2 = 1 + 0.004 842 933 682 176;
  • 33) 0.004 842 933 682 176 × 2 = 0 + 0.009 685 867 364 352;
  • 34) 0.009 685 867 364 352 × 2 = 0 + 0.019 371 734 728 704;
  • 35) 0.019 371 734 728 704 × 2 = 0 + 0.038 743 469 457 408;
  • 36) 0.038 743 469 457 408 × 2 = 0 + 0.077 486 938 914 816;
  • 37) 0.077 486 938 914 816 × 2 = 0 + 0.154 973 877 829 632;
  • 38) 0.154 973 877 829 632 × 2 = 0 + 0.309 947 755 659 264;
  • 39) 0.309 947 755 659 264 × 2 = 0 + 0.619 895 511 318 528;
  • 40) 0.619 895 511 318 528 × 2 = 1 + 0.239 791 022 637 056;
  • 41) 0.239 791 022 637 056 × 2 = 0 + 0.479 582 045 274 112;
  • 42) 0.479 582 045 274 112 × 2 = 0 + 0.959 164 090 548 224;
  • 43) 0.959 164 090 548 224 × 2 = 1 + 0.918 328 181 096 448;
  • 44) 0.918 328 181 096 448 × 2 = 1 + 0.836 656 362 192 896;
  • 45) 0.836 656 362 192 896 × 2 = 1 + 0.673 312 724 385 792;
  • 46) 0.673 312 724 385 792 × 2 = 1 + 0.346 625 448 771 584;
  • 47) 0.346 625 448 771 584 × 2 = 0 + 0.693 250 897 543 168;
  • 48) 0.693 250 897 543 168 × 2 = 1 + 0.386 501 795 086 336;
  • 49) 0.386 501 795 086 336 × 2 = 0 + 0.773 003 590 172 672;
  • 50) 0.773 003 590 172 672 × 2 = 1 + 0.546 007 180 345 344;
  • 51) 0.546 007 180 345 344 × 2 = 1 + 0.092 014 360 690 688;
  • 52) 0.092 014 360 690 688 × 2 = 0 + 0.184 028 721 381 376;
  • 53) 0.184 028 721 381 376 × 2 = 0 + 0.368 057 442 762 752;

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:


0.974 013 318 541 656(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0011 1101 0110 0(2)

5. Positive number before normalization:

0.974 013 318 541 656(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0011 1101 0110 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:


0.974 013 318 541 656(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0011 1101 0110 0(2) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0011 1101 0110 0(2) × 20 =


1.1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0111 1010 1100(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 0111 1010 1100


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 0111 1010 1100 =


1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0111 1010 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 1110


Mantissa (52 bits) =
1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0111 1010 1100


Decimal number 0.974 013 318 541 656 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 0111 1010 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