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

Convert decimal 0.974 013 318 541 754(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
0.974 013 318 541 754(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: 0.974 013 318 541 754.

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) 0.974 013 318 541 754 × 2 = 1 + 0.948 026 637 083 508;
  • 2) 0.948 026 637 083 508 × 2 = 1 + 0.896 053 274 167 016;
  • 3) 0.896 053 274 167 016 × 2 = 1 + 0.792 106 548 334 032;
  • 4) 0.792 106 548 334 032 × 2 = 1 + 0.584 213 096 668 064;
  • 5) 0.584 213 096 668 064 × 2 = 1 + 0.168 426 193 336 128;
  • 6) 0.168 426 193 336 128 × 2 = 0 + 0.336 852 386 672 256;
  • 7) 0.336 852 386 672 256 × 2 = 0 + 0.673 704 773 344 512;
  • 8) 0.673 704 773 344 512 × 2 = 1 + 0.347 409 546 689 024;
  • 9) 0.347 409 546 689 024 × 2 = 0 + 0.694 819 093 378 048;
  • 10) 0.694 819 093 378 048 × 2 = 1 + 0.389 638 186 756 096;
  • 11) 0.389 638 186 756 096 × 2 = 0 + 0.779 276 373 512 192;
  • 12) 0.779 276 373 512 192 × 2 = 1 + 0.558 552 747 024 384;
  • 13) 0.558 552 747 024 384 × 2 = 1 + 0.117 105 494 048 768;
  • 14) 0.117 105 494 048 768 × 2 = 0 + 0.234 210 988 097 536;
  • 15) 0.234 210 988 097 536 × 2 = 0 + 0.468 421 976 195 072;
  • 16) 0.468 421 976 195 072 × 2 = 0 + 0.936 843 952 390 144;
  • 17) 0.936 843 952 390 144 × 2 = 1 + 0.873 687 904 780 288;
  • 18) 0.873 687 904 780 288 × 2 = 1 + 0.747 375 809 560 576;
  • 19) 0.747 375 809 560 576 × 2 = 1 + 0.494 751 619 121 152;
  • 20) 0.494 751 619 121 152 × 2 = 0 + 0.989 503 238 242 304;
  • 21) 0.989 503 238 242 304 × 2 = 1 + 0.979 006 476 484 608;
  • 22) 0.979 006 476 484 608 × 2 = 1 + 0.958 012 952 969 216;
  • 23) 0.958 012 952 969 216 × 2 = 1 + 0.916 025 905 938 432;
  • 24) 0.916 025 905 938 432 × 2 = 1 + 0.832 051 811 876 864;
  • 25) 0.832 051 811 876 864 × 2 = 1 + 0.664 103 623 753 728;
  • 26) 0.664 103 623 753 728 × 2 = 1 + 0.328 207 247 507 456;
  • 27) 0.328 207 247 507 456 × 2 = 0 + 0.656 414 495 014 912;
  • 28) 0.656 414 495 014 912 × 2 = 1 + 0.312 828 990 029 824;
  • 29) 0.312 828 990 029 824 × 2 = 0 + 0.625 657 980 059 648;
  • 30) 0.625 657 980 059 648 × 2 = 1 + 0.251 315 960 119 296;
  • 31) 0.251 315 960 119 296 × 2 = 0 + 0.502 631 920 238 592;
  • 32) 0.502 631 920 238 592 × 2 = 1 + 0.005 263 840 477 184;
  • 33) 0.005 263 840 477 184 × 2 = 0 + 0.010 527 680 954 368;
  • 34) 0.010 527 680 954 368 × 2 = 0 + 0.021 055 361 908 736;
  • 35) 0.021 055 361 908 736 × 2 = 0 + 0.042 110 723 817 472;
  • 36) 0.042 110 723 817 472 × 2 = 0 + 0.084 221 447 634 944;
  • 37) 0.084 221 447 634 944 × 2 = 0 + 0.168 442 895 269 888;
  • 38) 0.168 442 895 269 888 × 2 = 0 + 0.336 885 790 539 776;
  • 39) 0.336 885 790 539 776 × 2 = 0 + 0.673 771 581 079 552;
  • 40) 0.673 771 581 079 552 × 2 = 1 + 0.347 543 162 159 104;
  • 41) 0.347 543 162 159 104 × 2 = 0 + 0.695 086 324 318 208;
  • 42) 0.695 086 324 318 208 × 2 = 1 + 0.390 172 648 636 416;
  • 43) 0.390 172 648 636 416 × 2 = 0 + 0.780 345 297 272 832;
  • 44) 0.780 345 297 272 832 × 2 = 1 + 0.560 690 594 545 664;
  • 45) 0.560 690 594 545 664 × 2 = 1 + 0.121 381 189 091 328;
  • 46) 0.121 381 189 091 328 × 2 = 0 + 0.242 762 378 182 656;
  • 47) 0.242 762 378 182 656 × 2 = 0 + 0.485 524 756 365 312;
  • 48) 0.485 524 756 365 312 × 2 = 0 + 0.971 049 512 730 624;
  • 49) 0.971 049 512 730 624 × 2 = 1 + 0.942 099 025 461 248;
  • 50) 0.942 099 025 461 248 × 2 = 1 + 0.884 198 050 922 496;
  • 51) 0.884 198 050 922 496 × 2 = 1 + 0.768 396 101 844 992;
  • 52) 0.768 396 101 844 992 × 2 = 1 + 0.536 792 203 689 984;
  • 53) 0.536 792 203 689 984 × 2 = 1 + 0.073 584 407 379 968;

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:


0.974 013 318 541 754(10) =


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

5. Positive number before normalization:

0.974 013 318 541 754(10) =


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


0.974 013 318 541 754(10) =


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


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


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


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 1011 0001 1111 =


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


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 1011 0001 1111


Decimal number 0.974 013 318 541 754 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 1011 0001 1111


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