0.974 013 318 541 691 5 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 318 541 691 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
0.974 013 318 541 691 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: 0.974 013 318 541 691 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) 0.974 013 318 541 691 5 × 2 = 1 + 0.948 026 637 083 383;
  • 2) 0.948 026 637 083 383 × 2 = 1 + 0.896 053 274 166 766;
  • 3) 0.896 053 274 166 766 × 2 = 1 + 0.792 106 548 333 532;
  • 4) 0.792 106 548 333 532 × 2 = 1 + 0.584 213 096 667 064;
  • 5) 0.584 213 096 667 064 × 2 = 1 + 0.168 426 193 334 128;
  • 6) 0.168 426 193 334 128 × 2 = 0 + 0.336 852 386 668 256;
  • 7) 0.336 852 386 668 256 × 2 = 0 + 0.673 704 773 336 512;
  • 8) 0.673 704 773 336 512 × 2 = 1 + 0.347 409 546 673 024;
  • 9) 0.347 409 546 673 024 × 2 = 0 + 0.694 819 093 346 048;
  • 10) 0.694 819 093 346 048 × 2 = 1 + 0.389 638 186 692 096;
  • 11) 0.389 638 186 692 096 × 2 = 0 + 0.779 276 373 384 192;
  • 12) 0.779 276 373 384 192 × 2 = 1 + 0.558 552 746 768 384;
  • 13) 0.558 552 746 768 384 × 2 = 1 + 0.117 105 493 536 768;
  • 14) 0.117 105 493 536 768 × 2 = 0 + 0.234 210 987 073 536;
  • 15) 0.234 210 987 073 536 × 2 = 0 + 0.468 421 974 147 072;
  • 16) 0.468 421 974 147 072 × 2 = 0 + 0.936 843 948 294 144;
  • 17) 0.936 843 948 294 144 × 2 = 1 + 0.873 687 896 588 288;
  • 18) 0.873 687 896 588 288 × 2 = 1 + 0.747 375 793 176 576;
  • 19) 0.747 375 793 176 576 × 2 = 1 + 0.494 751 586 353 152;
  • 20) 0.494 751 586 353 152 × 2 = 0 + 0.989 503 172 706 304;
  • 21) 0.989 503 172 706 304 × 2 = 1 + 0.979 006 345 412 608;
  • 22) 0.979 006 345 412 608 × 2 = 1 + 0.958 012 690 825 216;
  • 23) 0.958 012 690 825 216 × 2 = 1 + 0.916 025 381 650 432;
  • 24) 0.916 025 381 650 432 × 2 = 1 + 0.832 050 763 300 864;
  • 25) 0.832 050 763 300 864 × 2 = 1 + 0.664 101 526 601 728;
  • 26) 0.664 101 526 601 728 × 2 = 1 + 0.328 203 053 203 456;
  • 27) 0.328 203 053 203 456 × 2 = 0 + 0.656 406 106 406 912;
  • 28) 0.656 406 106 406 912 × 2 = 1 + 0.312 812 212 813 824;
  • 29) 0.312 812 212 813 824 × 2 = 0 + 0.625 624 425 627 648;
  • 30) 0.625 624 425 627 648 × 2 = 1 + 0.251 248 851 255 296;
  • 31) 0.251 248 851 255 296 × 2 = 0 + 0.502 497 702 510 592;
  • 32) 0.502 497 702 510 592 × 2 = 1 + 0.004 995 405 021 184;
  • 33) 0.004 995 405 021 184 × 2 = 0 + 0.009 990 810 042 368;
  • 34) 0.009 990 810 042 368 × 2 = 0 + 0.019 981 620 084 736;
  • 35) 0.019 981 620 084 736 × 2 = 0 + 0.039 963 240 169 472;
  • 36) 0.039 963 240 169 472 × 2 = 0 + 0.079 926 480 338 944;
  • 37) 0.079 926 480 338 944 × 2 = 0 + 0.159 852 960 677 888;
  • 38) 0.159 852 960 677 888 × 2 = 0 + 0.319 705 921 355 776;
  • 39) 0.319 705 921 355 776 × 2 = 0 + 0.639 411 842 711 552;
  • 40) 0.639 411 842 711 552 × 2 = 1 + 0.278 823 685 423 104;
  • 41) 0.278 823 685 423 104 × 2 = 0 + 0.557 647 370 846 208;
  • 42) 0.557 647 370 846 208 × 2 = 1 + 0.115 294 741 692 416;
  • 43) 0.115 294 741 692 416 × 2 = 0 + 0.230 589 483 384 832;
  • 44) 0.230 589 483 384 832 × 2 = 0 + 0.461 178 966 769 664;
  • 45) 0.461 178 966 769 664 × 2 = 0 + 0.922 357 933 539 328;
  • 46) 0.922 357 933 539 328 × 2 = 1 + 0.844 715 867 078 656;
  • 47) 0.844 715 867 078 656 × 2 = 1 + 0.689 431 734 157 312;
  • 48) 0.689 431 734 157 312 × 2 = 1 + 0.378 863 468 314 624;
  • 49) 0.378 863 468 314 624 × 2 = 0 + 0.757 726 936 629 248;
  • 50) 0.757 726 936 629 248 × 2 = 1 + 0.515 453 873 258 496;
  • 51) 0.515 453 873 258 496 × 2 = 1 + 0.030 907 746 516 992;
  • 52) 0.030 907 746 516 992 × 2 = 0 + 0.061 815 493 033 984;
  • 53) 0.061 815 493 033 984 × 2 = 0 + 0.123 630 986 067 968;

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:


0.974 013 318 541 691 5(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0100 0111 0110 0(2)

5. Positive number before normalization:

0.974 013 318 541 691 5(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0100 0111 0110 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:


0.974 013 318 541 691 5(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0100 0111 0110 0(2) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0100 0111 0110 0(2) × 20 =


1.1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 1000 1110 1100(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 1000 1110 1100


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 1000 1110 1100 =


1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 1000 1110 1100


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 1000 1110 1100


Decimal number 0.974 013 318 541 691 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 1000 1110 1100


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