0.974 013 318 541 571 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 318 541 571(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
0.974 013 318 541 571(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: 0.974 013 318 541 571.

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) 0.974 013 318 541 571 × 2 = 1 + 0.948 026 637 083 142;
  • 2) 0.948 026 637 083 142 × 2 = 1 + 0.896 053 274 166 284;
  • 3) 0.896 053 274 166 284 × 2 = 1 + 0.792 106 548 332 568;
  • 4) 0.792 106 548 332 568 × 2 = 1 + 0.584 213 096 665 136;
  • 5) 0.584 213 096 665 136 × 2 = 1 + 0.168 426 193 330 272;
  • 6) 0.168 426 193 330 272 × 2 = 0 + 0.336 852 386 660 544;
  • 7) 0.336 852 386 660 544 × 2 = 0 + 0.673 704 773 321 088;
  • 8) 0.673 704 773 321 088 × 2 = 1 + 0.347 409 546 642 176;
  • 9) 0.347 409 546 642 176 × 2 = 0 + 0.694 819 093 284 352;
  • 10) 0.694 819 093 284 352 × 2 = 1 + 0.389 638 186 568 704;
  • 11) 0.389 638 186 568 704 × 2 = 0 + 0.779 276 373 137 408;
  • 12) 0.779 276 373 137 408 × 2 = 1 + 0.558 552 746 274 816;
  • 13) 0.558 552 746 274 816 × 2 = 1 + 0.117 105 492 549 632;
  • 14) 0.117 105 492 549 632 × 2 = 0 + 0.234 210 985 099 264;
  • 15) 0.234 210 985 099 264 × 2 = 0 + 0.468 421 970 198 528;
  • 16) 0.468 421 970 198 528 × 2 = 0 + 0.936 843 940 397 056;
  • 17) 0.936 843 940 397 056 × 2 = 1 + 0.873 687 880 794 112;
  • 18) 0.873 687 880 794 112 × 2 = 1 + 0.747 375 761 588 224;
  • 19) 0.747 375 761 588 224 × 2 = 1 + 0.494 751 523 176 448;
  • 20) 0.494 751 523 176 448 × 2 = 0 + 0.989 503 046 352 896;
  • 21) 0.989 503 046 352 896 × 2 = 1 + 0.979 006 092 705 792;
  • 22) 0.979 006 092 705 792 × 2 = 1 + 0.958 012 185 411 584;
  • 23) 0.958 012 185 411 584 × 2 = 1 + 0.916 024 370 823 168;
  • 24) 0.916 024 370 823 168 × 2 = 1 + 0.832 048 741 646 336;
  • 25) 0.832 048 741 646 336 × 2 = 1 + 0.664 097 483 292 672;
  • 26) 0.664 097 483 292 672 × 2 = 1 + 0.328 194 966 585 344;
  • 27) 0.328 194 966 585 344 × 2 = 0 + 0.656 389 933 170 688;
  • 28) 0.656 389 933 170 688 × 2 = 1 + 0.312 779 866 341 376;
  • 29) 0.312 779 866 341 376 × 2 = 0 + 0.625 559 732 682 752;
  • 30) 0.625 559 732 682 752 × 2 = 1 + 0.251 119 465 365 504;
  • 31) 0.251 119 465 365 504 × 2 = 0 + 0.502 238 930 731 008;
  • 32) 0.502 238 930 731 008 × 2 = 1 + 0.004 477 861 462 016;
  • 33) 0.004 477 861 462 016 × 2 = 0 + 0.008 955 722 924 032;
  • 34) 0.008 955 722 924 032 × 2 = 0 + 0.017 911 445 848 064;
  • 35) 0.017 911 445 848 064 × 2 = 0 + 0.035 822 891 696 128;
  • 36) 0.035 822 891 696 128 × 2 = 0 + 0.071 645 783 392 256;
  • 37) 0.071 645 783 392 256 × 2 = 0 + 0.143 291 566 784 512;
  • 38) 0.143 291 566 784 512 × 2 = 0 + 0.286 583 133 569 024;
  • 39) 0.286 583 133 569 024 × 2 = 0 + 0.573 166 267 138 048;
  • 40) 0.573 166 267 138 048 × 2 = 1 + 0.146 332 534 276 096;
  • 41) 0.146 332 534 276 096 × 2 = 0 + 0.292 665 068 552 192;
  • 42) 0.292 665 068 552 192 × 2 = 0 + 0.585 330 137 104 384;
  • 43) 0.585 330 137 104 384 × 2 = 1 + 0.170 660 274 208 768;
  • 44) 0.170 660 274 208 768 × 2 = 0 + 0.341 320 548 417 536;
  • 45) 0.341 320 548 417 536 × 2 = 0 + 0.682 641 096 835 072;
  • 46) 0.682 641 096 835 072 × 2 = 1 + 0.365 282 193 670 144;
  • 47) 0.365 282 193 670 144 × 2 = 0 + 0.730 564 387 340 288;
  • 48) 0.730 564 387 340 288 × 2 = 1 + 0.461 128 774 680 576;
  • 49) 0.461 128 774 680 576 × 2 = 0 + 0.922 257 549 361 152;
  • 50) 0.922 257 549 361 152 × 2 = 1 + 0.844 515 098 722 304;
  • 51) 0.844 515 098 722 304 × 2 = 1 + 0.689 030 197 444 608;
  • 52) 0.689 030 197 444 608 × 2 = 1 + 0.378 060 394 889 216;
  • 53) 0.378 060 394 889 216 × 2 = 0 + 0.756 120 789 778 432;

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:


0.974 013 318 541 571(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0010 0101 0111 0(2)

5. Positive number before normalization:

0.974 013 318 541 571(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0010 0101 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:


0.974 013 318 541 571(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0010 0101 0111 0(2) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0010 0101 0111 0(2) × 20 =


1.1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0100 1010 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 0100 1010 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 0100 1010 1110 =


1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0100 1010 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 0100 1010 1110


Decimal number 0.974 013 318 541 571 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 0100 1010 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