0.974 013 318 541 786 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 318 541 786(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
0.974 013 318 541 786(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: 0.974 013 318 541 786.

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) 0.974 013 318 541 786 × 2 = 1 + 0.948 026 637 083 572;
  • 2) 0.948 026 637 083 572 × 2 = 1 + 0.896 053 274 167 144;
  • 3) 0.896 053 274 167 144 × 2 = 1 + 0.792 106 548 334 288;
  • 4) 0.792 106 548 334 288 × 2 = 1 + 0.584 213 096 668 576;
  • 5) 0.584 213 096 668 576 × 2 = 1 + 0.168 426 193 337 152;
  • 6) 0.168 426 193 337 152 × 2 = 0 + 0.336 852 386 674 304;
  • 7) 0.336 852 386 674 304 × 2 = 0 + 0.673 704 773 348 608;
  • 8) 0.673 704 773 348 608 × 2 = 1 + 0.347 409 546 697 216;
  • 9) 0.347 409 546 697 216 × 2 = 0 + 0.694 819 093 394 432;
  • 10) 0.694 819 093 394 432 × 2 = 1 + 0.389 638 186 788 864;
  • 11) 0.389 638 186 788 864 × 2 = 0 + 0.779 276 373 577 728;
  • 12) 0.779 276 373 577 728 × 2 = 1 + 0.558 552 747 155 456;
  • 13) 0.558 552 747 155 456 × 2 = 1 + 0.117 105 494 310 912;
  • 14) 0.117 105 494 310 912 × 2 = 0 + 0.234 210 988 621 824;
  • 15) 0.234 210 988 621 824 × 2 = 0 + 0.468 421 977 243 648;
  • 16) 0.468 421 977 243 648 × 2 = 0 + 0.936 843 954 487 296;
  • 17) 0.936 843 954 487 296 × 2 = 1 + 0.873 687 908 974 592;
  • 18) 0.873 687 908 974 592 × 2 = 1 + 0.747 375 817 949 184;
  • 19) 0.747 375 817 949 184 × 2 = 1 + 0.494 751 635 898 368;
  • 20) 0.494 751 635 898 368 × 2 = 0 + 0.989 503 271 796 736;
  • 21) 0.989 503 271 796 736 × 2 = 1 + 0.979 006 543 593 472;
  • 22) 0.979 006 543 593 472 × 2 = 1 + 0.958 013 087 186 944;
  • 23) 0.958 013 087 186 944 × 2 = 1 + 0.916 026 174 373 888;
  • 24) 0.916 026 174 373 888 × 2 = 1 + 0.832 052 348 747 776;
  • 25) 0.832 052 348 747 776 × 2 = 1 + 0.664 104 697 495 552;
  • 26) 0.664 104 697 495 552 × 2 = 1 + 0.328 209 394 991 104;
  • 27) 0.328 209 394 991 104 × 2 = 0 + 0.656 418 789 982 208;
  • 28) 0.656 418 789 982 208 × 2 = 1 + 0.312 837 579 964 416;
  • 29) 0.312 837 579 964 416 × 2 = 0 + 0.625 675 159 928 832;
  • 30) 0.625 675 159 928 832 × 2 = 1 + 0.251 350 319 857 664;
  • 31) 0.251 350 319 857 664 × 2 = 0 + 0.502 700 639 715 328;
  • 32) 0.502 700 639 715 328 × 2 = 1 + 0.005 401 279 430 656;
  • 33) 0.005 401 279 430 656 × 2 = 0 + 0.010 802 558 861 312;
  • 34) 0.010 802 558 861 312 × 2 = 0 + 0.021 605 117 722 624;
  • 35) 0.021 605 117 722 624 × 2 = 0 + 0.043 210 235 445 248;
  • 36) 0.043 210 235 445 248 × 2 = 0 + 0.086 420 470 890 496;
  • 37) 0.086 420 470 890 496 × 2 = 0 + 0.172 840 941 780 992;
  • 38) 0.172 840 941 780 992 × 2 = 0 + 0.345 681 883 561 984;
  • 39) 0.345 681 883 561 984 × 2 = 0 + 0.691 363 767 123 968;
  • 40) 0.691 363 767 123 968 × 2 = 1 + 0.382 727 534 247 936;
  • 41) 0.382 727 534 247 936 × 2 = 0 + 0.765 455 068 495 872;
  • 42) 0.765 455 068 495 872 × 2 = 1 + 0.530 910 136 991 744;
  • 43) 0.530 910 136 991 744 × 2 = 1 + 0.061 820 273 983 488;
  • 44) 0.061 820 273 983 488 × 2 = 0 + 0.123 640 547 966 976;
  • 45) 0.123 640 547 966 976 × 2 = 0 + 0.247 281 095 933 952;
  • 46) 0.247 281 095 933 952 × 2 = 0 + 0.494 562 191 867 904;
  • 47) 0.494 562 191 867 904 × 2 = 0 + 0.989 124 383 735 808;
  • 48) 0.989 124 383 735 808 × 2 = 1 + 0.978 248 767 471 616;
  • 49) 0.978 248 767 471 616 × 2 = 1 + 0.956 497 534 943 232;
  • 50) 0.956 497 534 943 232 × 2 = 1 + 0.912 995 069 886 464;
  • 51) 0.912 995 069 886 464 × 2 = 1 + 0.825 990 139 772 928;
  • 52) 0.825 990 139 772 928 × 2 = 1 + 0.651 980 279 545 856;
  • 53) 0.651 980 279 545 856 × 2 = 1 + 0.303 960 559 091 712;

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:


0.974 013 318 541 786(10) =


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

5. Positive number before normalization:

0.974 013 318 541 786(10) =


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


0.974 013 318 541 786(10) =


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


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


1.1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 1100 0011 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 1100 0011 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 1100 0011 1111 =


1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 1100 0011 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 1100 0011 1111


Decimal number 0.974 013 318 541 786 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 1100 0011 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