0.974 013 318 541 728 7 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 318 541 728 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
0.974 013 318 541 728 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: 0.974 013 318 541 728 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) 0.974 013 318 541 728 7 × 2 = 1 + 0.948 026 637 083 457 4;
  • 2) 0.948 026 637 083 457 4 × 2 = 1 + 0.896 053 274 166 914 8;
  • 3) 0.896 053 274 166 914 8 × 2 = 1 + 0.792 106 548 333 829 6;
  • 4) 0.792 106 548 333 829 6 × 2 = 1 + 0.584 213 096 667 659 2;
  • 5) 0.584 213 096 667 659 2 × 2 = 1 + 0.168 426 193 335 318 4;
  • 6) 0.168 426 193 335 318 4 × 2 = 0 + 0.336 852 386 670 636 8;
  • 7) 0.336 852 386 670 636 8 × 2 = 0 + 0.673 704 773 341 273 6;
  • 8) 0.673 704 773 341 273 6 × 2 = 1 + 0.347 409 546 682 547 2;
  • 9) 0.347 409 546 682 547 2 × 2 = 0 + 0.694 819 093 365 094 4;
  • 10) 0.694 819 093 365 094 4 × 2 = 1 + 0.389 638 186 730 188 8;
  • 11) 0.389 638 186 730 188 8 × 2 = 0 + 0.779 276 373 460 377 6;
  • 12) 0.779 276 373 460 377 6 × 2 = 1 + 0.558 552 746 920 755 2;
  • 13) 0.558 552 746 920 755 2 × 2 = 1 + 0.117 105 493 841 510 4;
  • 14) 0.117 105 493 841 510 4 × 2 = 0 + 0.234 210 987 683 020 8;
  • 15) 0.234 210 987 683 020 8 × 2 = 0 + 0.468 421 975 366 041 6;
  • 16) 0.468 421 975 366 041 6 × 2 = 0 + 0.936 843 950 732 083 2;
  • 17) 0.936 843 950 732 083 2 × 2 = 1 + 0.873 687 901 464 166 4;
  • 18) 0.873 687 901 464 166 4 × 2 = 1 + 0.747 375 802 928 332 8;
  • 19) 0.747 375 802 928 332 8 × 2 = 1 + 0.494 751 605 856 665 6;
  • 20) 0.494 751 605 856 665 6 × 2 = 0 + 0.989 503 211 713 331 2;
  • 21) 0.989 503 211 713 331 2 × 2 = 1 + 0.979 006 423 426 662 4;
  • 22) 0.979 006 423 426 662 4 × 2 = 1 + 0.958 012 846 853 324 8;
  • 23) 0.958 012 846 853 324 8 × 2 = 1 + 0.916 025 693 706 649 6;
  • 24) 0.916 025 693 706 649 6 × 2 = 1 + 0.832 051 387 413 299 2;
  • 25) 0.832 051 387 413 299 2 × 2 = 1 + 0.664 102 774 826 598 4;
  • 26) 0.664 102 774 826 598 4 × 2 = 1 + 0.328 205 549 653 196 8;
  • 27) 0.328 205 549 653 196 8 × 2 = 0 + 0.656 411 099 306 393 6;
  • 28) 0.656 411 099 306 393 6 × 2 = 1 + 0.312 822 198 612 787 2;
  • 29) 0.312 822 198 612 787 2 × 2 = 0 + 0.625 644 397 225 574 4;
  • 30) 0.625 644 397 225 574 4 × 2 = 1 + 0.251 288 794 451 148 8;
  • 31) 0.251 288 794 451 148 8 × 2 = 0 + 0.502 577 588 902 297 6;
  • 32) 0.502 577 588 902 297 6 × 2 = 1 + 0.005 155 177 804 595 2;
  • 33) 0.005 155 177 804 595 2 × 2 = 0 + 0.010 310 355 609 190 4;
  • 34) 0.010 310 355 609 190 4 × 2 = 0 + 0.020 620 711 218 380 8;
  • 35) 0.020 620 711 218 380 8 × 2 = 0 + 0.041 241 422 436 761 6;
  • 36) 0.041 241 422 436 761 6 × 2 = 0 + 0.082 482 844 873 523 2;
  • 37) 0.082 482 844 873 523 2 × 2 = 0 + 0.164 965 689 747 046 4;
  • 38) 0.164 965 689 747 046 4 × 2 = 0 + 0.329 931 379 494 092 8;
  • 39) 0.329 931 379 494 092 8 × 2 = 0 + 0.659 862 758 988 185 6;
  • 40) 0.659 862 758 988 185 6 × 2 = 1 + 0.319 725 517 976 371 2;
  • 41) 0.319 725 517 976 371 2 × 2 = 0 + 0.639 451 035 952 742 4;
  • 42) 0.639 451 035 952 742 4 × 2 = 1 + 0.278 902 071 905 484 8;
  • 43) 0.278 902 071 905 484 8 × 2 = 0 + 0.557 804 143 810 969 6;
  • 44) 0.557 804 143 810 969 6 × 2 = 1 + 0.115 608 287 621 939 2;
  • 45) 0.115 608 287 621 939 2 × 2 = 0 + 0.231 216 575 243 878 4;
  • 46) 0.231 216 575 243 878 4 × 2 = 0 + 0.462 433 150 487 756 8;
  • 47) 0.462 433 150 487 756 8 × 2 = 0 + 0.924 866 300 975 513 6;
  • 48) 0.924 866 300 975 513 6 × 2 = 1 + 0.849 732 601 951 027 2;
  • 49) 0.849 732 601 951 027 2 × 2 = 1 + 0.699 465 203 902 054 4;
  • 50) 0.699 465 203 902 054 4 × 2 = 1 + 0.398 930 407 804 108 8;
  • 51) 0.398 930 407 804 108 8 × 2 = 0 + 0.797 860 815 608 217 6;
  • 52) 0.797 860 815 608 217 6 × 2 = 1 + 0.595 721 631 216 435 2;
  • 53) 0.595 721 631 216 435 2 × 2 = 1 + 0.191 443 262 432 870 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:


0.974 013 318 541 728 7(10) =


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

5. Positive number before normalization:

0.974 013 318 541 728 7(10) =


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


0.974 013 318 541 728 7(10) =


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


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


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


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 1010 0011 1011 =


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


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 1010 0011 1011


Decimal number 0.974 013 318 541 728 7 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 1010 0011 1011


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