0.974 013 318 541 507 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 318 541 507(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
0.974 013 318 541 507(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: 0.974 013 318 541 507.

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) 0.974 013 318 541 507 × 2 = 1 + 0.948 026 637 083 014;
  • 2) 0.948 026 637 083 014 × 2 = 1 + 0.896 053 274 166 028;
  • 3) 0.896 053 274 166 028 × 2 = 1 + 0.792 106 548 332 056;
  • 4) 0.792 106 548 332 056 × 2 = 1 + 0.584 213 096 664 112;
  • 5) 0.584 213 096 664 112 × 2 = 1 + 0.168 426 193 328 224;
  • 6) 0.168 426 193 328 224 × 2 = 0 + 0.336 852 386 656 448;
  • 7) 0.336 852 386 656 448 × 2 = 0 + 0.673 704 773 312 896;
  • 8) 0.673 704 773 312 896 × 2 = 1 + 0.347 409 546 625 792;
  • 9) 0.347 409 546 625 792 × 2 = 0 + 0.694 819 093 251 584;
  • 10) 0.694 819 093 251 584 × 2 = 1 + 0.389 638 186 503 168;
  • 11) 0.389 638 186 503 168 × 2 = 0 + 0.779 276 373 006 336;
  • 12) 0.779 276 373 006 336 × 2 = 1 + 0.558 552 746 012 672;
  • 13) 0.558 552 746 012 672 × 2 = 1 + 0.117 105 492 025 344;
  • 14) 0.117 105 492 025 344 × 2 = 0 + 0.234 210 984 050 688;
  • 15) 0.234 210 984 050 688 × 2 = 0 + 0.468 421 968 101 376;
  • 16) 0.468 421 968 101 376 × 2 = 0 + 0.936 843 936 202 752;
  • 17) 0.936 843 936 202 752 × 2 = 1 + 0.873 687 872 405 504;
  • 18) 0.873 687 872 405 504 × 2 = 1 + 0.747 375 744 811 008;
  • 19) 0.747 375 744 811 008 × 2 = 1 + 0.494 751 489 622 016;
  • 20) 0.494 751 489 622 016 × 2 = 0 + 0.989 502 979 244 032;
  • 21) 0.989 502 979 244 032 × 2 = 1 + 0.979 005 958 488 064;
  • 22) 0.979 005 958 488 064 × 2 = 1 + 0.958 011 916 976 128;
  • 23) 0.958 011 916 976 128 × 2 = 1 + 0.916 023 833 952 256;
  • 24) 0.916 023 833 952 256 × 2 = 1 + 0.832 047 667 904 512;
  • 25) 0.832 047 667 904 512 × 2 = 1 + 0.664 095 335 809 024;
  • 26) 0.664 095 335 809 024 × 2 = 1 + 0.328 190 671 618 048;
  • 27) 0.328 190 671 618 048 × 2 = 0 + 0.656 381 343 236 096;
  • 28) 0.656 381 343 236 096 × 2 = 1 + 0.312 762 686 472 192;
  • 29) 0.312 762 686 472 192 × 2 = 0 + 0.625 525 372 944 384;
  • 30) 0.625 525 372 944 384 × 2 = 1 + 0.251 050 745 888 768;
  • 31) 0.251 050 745 888 768 × 2 = 0 + 0.502 101 491 777 536;
  • 32) 0.502 101 491 777 536 × 2 = 1 + 0.004 202 983 555 072;
  • 33) 0.004 202 983 555 072 × 2 = 0 + 0.008 405 967 110 144;
  • 34) 0.008 405 967 110 144 × 2 = 0 + 0.016 811 934 220 288;
  • 35) 0.016 811 934 220 288 × 2 = 0 + 0.033 623 868 440 576;
  • 36) 0.033 623 868 440 576 × 2 = 0 + 0.067 247 736 881 152;
  • 37) 0.067 247 736 881 152 × 2 = 0 + 0.134 495 473 762 304;
  • 38) 0.134 495 473 762 304 × 2 = 0 + 0.268 990 947 524 608;
  • 39) 0.268 990 947 524 608 × 2 = 0 + 0.537 981 895 049 216;
  • 40) 0.537 981 895 049 216 × 2 = 1 + 0.075 963 790 098 432;
  • 41) 0.075 963 790 098 432 × 2 = 0 + 0.151 927 580 196 864;
  • 42) 0.151 927 580 196 864 × 2 = 0 + 0.303 855 160 393 728;
  • 43) 0.303 855 160 393 728 × 2 = 0 + 0.607 710 320 787 456;
  • 44) 0.607 710 320 787 456 × 2 = 1 + 0.215 420 641 574 912;
  • 45) 0.215 420 641 574 912 × 2 = 0 + 0.430 841 283 149 824;
  • 46) 0.430 841 283 149 824 × 2 = 0 + 0.861 682 566 299 648;
  • 47) 0.861 682 566 299 648 × 2 = 1 + 0.723 365 132 599 296;
  • 48) 0.723 365 132 599 296 × 2 = 1 + 0.446 730 265 198 592;
  • 49) 0.446 730 265 198 592 × 2 = 0 + 0.893 460 530 397 184;
  • 50) 0.893 460 530 397 184 × 2 = 1 + 0.786 921 060 794 368;
  • 51) 0.786 921 060 794 368 × 2 = 1 + 0.573 842 121 588 736;
  • 52) 0.573 842 121 588 736 × 2 = 1 + 0.147 684 243 177 472;
  • 53) 0.147 684 243 177 472 × 2 = 0 + 0.295 368 486 354 944;

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:


0.974 013 318 541 507(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0001 0011 0111 0(2)

5. Positive number before normalization:

0.974 013 318 541 507(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0001 0011 0111 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:


0.974 013 318 541 507(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0001 0011 0111 0(2) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0001 0011 0111 0(2) × 20 =


1.1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0010 0110 1110(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 0010 0110 1110


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 0010 0110 1110 =


1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0010 0110 1110


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 0010 0110 1110


Decimal number 0.974 013 318 541 507 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 0010 0110 1110


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