0.974 013 318 541 727 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 318 541 727 2(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
0.974 013 318 541 727 2(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: 0.974 013 318 541 727 2.

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) 0.974 013 318 541 727 2 × 2 = 1 + 0.948 026 637 083 454 4;
  • 2) 0.948 026 637 083 454 4 × 2 = 1 + 0.896 053 274 166 908 8;
  • 3) 0.896 053 274 166 908 8 × 2 = 1 + 0.792 106 548 333 817 6;
  • 4) 0.792 106 548 333 817 6 × 2 = 1 + 0.584 213 096 667 635 2;
  • 5) 0.584 213 096 667 635 2 × 2 = 1 + 0.168 426 193 335 270 4;
  • 6) 0.168 426 193 335 270 4 × 2 = 0 + 0.336 852 386 670 540 8;
  • 7) 0.336 852 386 670 540 8 × 2 = 0 + 0.673 704 773 341 081 6;
  • 8) 0.673 704 773 341 081 6 × 2 = 1 + 0.347 409 546 682 163 2;
  • 9) 0.347 409 546 682 163 2 × 2 = 0 + 0.694 819 093 364 326 4;
  • 10) 0.694 819 093 364 326 4 × 2 = 1 + 0.389 638 186 728 652 8;
  • 11) 0.389 638 186 728 652 8 × 2 = 0 + 0.779 276 373 457 305 6;
  • 12) 0.779 276 373 457 305 6 × 2 = 1 + 0.558 552 746 914 611 2;
  • 13) 0.558 552 746 914 611 2 × 2 = 1 + 0.117 105 493 829 222 4;
  • 14) 0.117 105 493 829 222 4 × 2 = 0 + 0.234 210 987 658 444 8;
  • 15) 0.234 210 987 658 444 8 × 2 = 0 + 0.468 421 975 316 889 6;
  • 16) 0.468 421 975 316 889 6 × 2 = 0 + 0.936 843 950 633 779 2;
  • 17) 0.936 843 950 633 779 2 × 2 = 1 + 0.873 687 901 267 558 4;
  • 18) 0.873 687 901 267 558 4 × 2 = 1 + 0.747 375 802 535 116 8;
  • 19) 0.747 375 802 535 116 8 × 2 = 1 + 0.494 751 605 070 233 6;
  • 20) 0.494 751 605 070 233 6 × 2 = 0 + 0.989 503 210 140 467 2;
  • 21) 0.989 503 210 140 467 2 × 2 = 1 + 0.979 006 420 280 934 4;
  • 22) 0.979 006 420 280 934 4 × 2 = 1 + 0.958 012 840 561 868 8;
  • 23) 0.958 012 840 561 868 8 × 2 = 1 + 0.916 025 681 123 737 6;
  • 24) 0.916 025 681 123 737 6 × 2 = 1 + 0.832 051 362 247 475 2;
  • 25) 0.832 051 362 247 475 2 × 2 = 1 + 0.664 102 724 494 950 4;
  • 26) 0.664 102 724 494 950 4 × 2 = 1 + 0.328 205 448 989 900 8;
  • 27) 0.328 205 448 989 900 8 × 2 = 0 + 0.656 410 897 979 801 6;
  • 28) 0.656 410 897 979 801 6 × 2 = 1 + 0.312 821 795 959 603 2;
  • 29) 0.312 821 795 959 603 2 × 2 = 0 + 0.625 643 591 919 206 4;
  • 30) 0.625 643 591 919 206 4 × 2 = 1 + 0.251 287 183 838 412 8;
  • 31) 0.251 287 183 838 412 8 × 2 = 0 + 0.502 574 367 676 825 6;
  • 32) 0.502 574 367 676 825 6 × 2 = 1 + 0.005 148 735 353 651 2;
  • 33) 0.005 148 735 353 651 2 × 2 = 0 + 0.010 297 470 707 302 4;
  • 34) 0.010 297 470 707 302 4 × 2 = 0 + 0.020 594 941 414 604 8;
  • 35) 0.020 594 941 414 604 8 × 2 = 0 + 0.041 189 882 829 209 6;
  • 36) 0.041 189 882 829 209 6 × 2 = 0 + 0.082 379 765 658 419 2;
  • 37) 0.082 379 765 658 419 2 × 2 = 0 + 0.164 759 531 316 838 4;
  • 38) 0.164 759 531 316 838 4 × 2 = 0 + 0.329 519 062 633 676 8;
  • 39) 0.329 519 062 633 676 8 × 2 = 0 + 0.659 038 125 267 353 6;
  • 40) 0.659 038 125 267 353 6 × 2 = 1 + 0.318 076 250 534 707 2;
  • 41) 0.318 076 250 534 707 2 × 2 = 0 + 0.636 152 501 069 414 4;
  • 42) 0.636 152 501 069 414 4 × 2 = 1 + 0.272 305 002 138 828 8;
  • 43) 0.272 305 002 138 828 8 × 2 = 0 + 0.544 610 004 277 657 6;
  • 44) 0.544 610 004 277 657 6 × 2 = 1 + 0.089 220 008 555 315 2;
  • 45) 0.089 220 008 555 315 2 × 2 = 0 + 0.178 440 017 110 630 4;
  • 46) 0.178 440 017 110 630 4 × 2 = 0 + 0.356 880 034 221 260 8;
  • 47) 0.356 880 034 221 260 8 × 2 = 0 + 0.713 760 068 442 521 6;
  • 48) 0.713 760 068 442 521 6 × 2 = 1 + 0.427 520 136 885 043 2;
  • 49) 0.427 520 136 885 043 2 × 2 = 0 + 0.855 040 273 770 086 4;
  • 50) 0.855 040 273 770 086 4 × 2 = 1 + 0.710 080 547 540 172 8;
  • 51) 0.710 080 547 540 172 8 × 2 = 1 + 0.420 161 095 080 345 6;
  • 52) 0.420 161 095 080 345 6 × 2 = 0 + 0.840 322 190 160 691 2;
  • 53) 0.840 322 190 160 691 2 × 2 = 1 + 0.680 644 380 321 382 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:


0.974 013 318 541 727 2(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0101 0001 0110 1(2)

5. Positive number before normalization:

0.974 013 318 541 727 2(10) =


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


0.974 013 318 541 727 2(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0101 0001 0110 1(2) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0101 0001 0110 1(2) × 20 =


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


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 0010 1101 =


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


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 0010 1101


Decimal number 0.974 013 318 541 727 2 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 0010 1101


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