0.974 013 318 541 706 5 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 318 541 706 5(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
0.974 013 318 541 706 5(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: 0.974 013 318 541 706 5.

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) 0.974 013 318 541 706 5 × 2 = 1 + 0.948 026 637 083 413;
  • 2) 0.948 026 637 083 413 × 2 = 1 + 0.896 053 274 166 826;
  • 3) 0.896 053 274 166 826 × 2 = 1 + 0.792 106 548 333 652;
  • 4) 0.792 106 548 333 652 × 2 = 1 + 0.584 213 096 667 304;
  • 5) 0.584 213 096 667 304 × 2 = 1 + 0.168 426 193 334 608;
  • 6) 0.168 426 193 334 608 × 2 = 0 + 0.336 852 386 669 216;
  • 7) 0.336 852 386 669 216 × 2 = 0 + 0.673 704 773 338 432;
  • 8) 0.673 704 773 338 432 × 2 = 1 + 0.347 409 546 676 864;
  • 9) 0.347 409 546 676 864 × 2 = 0 + 0.694 819 093 353 728;
  • 10) 0.694 819 093 353 728 × 2 = 1 + 0.389 638 186 707 456;
  • 11) 0.389 638 186 707 456 × 2 = 0 + 0.779 276 373 414 912;
  • 12) 0.779 276 373 414 912 × 2 = 1 + 0.558 552 746 829 824;
  • 13) 0.558 552 746 829 824 × 2 = 1 + 0.117 105 493 659 648;
  • 14) 0.117 105 493 659 648 × 2 = 0 + 0.234 210 987 319 296;
  • 15) 0.234 210 987 319 296 × 2 = 0 + 0.468 421 974 638 592;
  • 16) 0.468 421 974 638 592 × 2 = 0 + 0.936 843 949 277 184;
  • 17) 0.936 843 949 277 184 × 2 = 1 + 0.873 687 898 554 368;
  • 18) 0.873 687 898 554 368 × 2 = 1 + 0.747 375 797 108 736;
  • 19) 0.747 375 797 108 736 × 2 = 1 + 0.494 751 594 217 472;
  • 20) 0.494 751 594 217 472 × 2 = 0 + 0.989 503 188 434 944;
  • 21) 0.989 503 188 434 944 × 2 = 1 + 0.979 006 376 869 888;
  • 22) 0.979 006 376 869 888 × 2 = 1 + 0.958 012 753 739 776;
  • 23) 0.958 012 753 739 776 × 2 = 1 + 0.916 025 507 479 552;
  • 24) 0.916 025 507 479 552 × 2 = 1 + 0.832 051 014 959 104;
  • 25) 0.832 051 014 959 104 × 2 = 1 + 0.664 102 029 918 208;
  • 26) 0.664 102 029 918 208 × 2 = 1 + 0.328 204 059 836 416;
  • 27) 0.328 204 059 836 416 × 2 = 0 + 0.656 408 119 672 832;
  • 28) 0.656 408 119 672 832 × 2 = 1 + 0.312 816 239 345 664;
  • 29) 0.312 816 239 345 664 × 2 = 0 + 0.625 632 478 691 328;
  • 30) 0.625 632 478 691 328 × 2 = 1 + 0.251 264 957 382 656;
  • 31) 0.251 264 957 382 656 × 2 = 0 + 0.502 529 914 765 312;
  • 32) 0.502 529 914 765 312 × 2 = 1 + 0.005 059 829 530 624;
  • 33) 0.005 059 829 530 624 × 2 = 0 + 0.010 119 659 061 248;
  • 34) 0.010 119 659 061 248 × 2 = 0 + 0.020 239 318 122 496;
  • 35) 0.020 239 318 122 496 × 2 = 0 + 0.040 478 636 244 992;
  • 36) 0.040 478 636 244 992 × 2 = 0 + 0.080 957 272 489 984;
  • 37) 0.080 957 272 489 984 × 2 = 0 + 0.161 914 544 979 968;
  • 38) 0.161 914 544 979 968 × 2 = 0 + 0.323 829 089 959 936;
  • 39) 0.323 829 089 959 936 × 2 = 0 + 0.647 658 179 919 872;
  • 40) 0.647 658 179 919 872 × 2 = 1 + 0.295 316 359 839 744;
  • 41) 0.295 316 359 839 744 × 2 = 0 + 0.590 632 719 679 488;
  • 42) 0.590 632 719 679 488 × 2 = 1 + 0.181 265 439 358 976;
  • 43) 0.181 265 439 358 976 × 2 = 0 + 0.362 530 878 717 952;
  • 44) 0.362 530 878 717 952 × 2 = 0 + 0.725 061 757 435 904;
  • 45) 0.725 061 757 435 904 × 2 = 1 + 0.450 123 514 871 808;
  • 46) 0.450 123 514 871 808 × 2 = 0 + 0.900 247 029 743 616;
  • 47) 0.900 247 029 743 616 × 2 = 1 + 0.800 494 059 487 232;
  • 48) 0.800 494 059 487 232 × 2 = 1 + 0.600 988 118 974 464;
  • 49) 0.600 988 118 974 464 × 2 = 1 + 0.201 976 237 948 928;
  • 50) 0.201 976 237 948 928 × 2 = 0 + 0.403 952 475 897 856;
  • 51) 0.403 952 475 897 856 × 2 = 0 + 0.807 904 951 795 712;
  • 52) 0.807 904 951 795 712 × 2 = 1 + 0.615 809 903 591 424;
  • 53) 0.615 809 903 591 424 × 2 = 1 + 0.231 619 807 182 848;

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:


0.974 013 318 541 706 5(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0100 1011 1001 1(2)

5. Positive number before normalization:

0.974 013 318 541 706 5(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0100 1011 1001 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:


0.974 013 318 541 706 5(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0100 1011 1001 1(2) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0100 1011 1001 1(2) × 20 =


1.1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 1001 0111 0011(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 1001 0111 0011


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 1001 0111 0011 =


1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 1001 0111 0011


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 1001 0111 0011


Decimal number 0.974 013 318 541 706 5 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 1001 0111 0011


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