0.974 013 318 541 803 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 318 541 803(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
0.974 013 318 541 803(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: 0.974 013 318 541 803.

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) 0.974 013 318 541 803 × 2 = 1 + 0.948 026 637 083 606;
  • 2) 0.948 026 637 083 606 × 2 = 1 + 0.896 053 274 167 212;
  • 3) 0.896 053 274 167 212 × 2 = 1 + 0.792 106 548 334 424;
  • 4) 0.792 106 548 334 424 × 2 = 1 + 0.584 213 096 668 848;
  • 5) 0.584 213 096 668 848 × 2 = 1 + 0.168 426 193 337 696;
  • 6) 0.168 426 193 337 696 × 2 = 0 + 0.336 852 386 675 392;
  • 7) 0.336 852 386 675 392 × 2 = 0 + 0.673 704 773 350 784;
  • 8) 0.673 704 773 350 784 × 2 = 1 + 0.347 409 546 701 568;
  • 9) 0.347 409 546 701 568 × 2 = 0 + 0.694 819 093 403 136;
  • 10) 0.694 819 093 403 136 × 2 = 1 + 0.389 638 186 806 272;
  • 11) 0.389 638 186 806 272 × 2 = 0 + 0.779 276 373 612 544;
  • 12) 0.779 276 373 612 544 × 2 = 1 + 0.558 552 747 225 088;
  • 13) 0.558 552 747 225 088 × 2 = 1 + 0.117 105 494 450 176;
  • 14) 0.117 105 494 450 176 × 2 = 0 + 0.234 210 988 900 352;
  • 15) 0.234 210 988 900 352 × 2 = 0 + 0.468 421 977 800 704;
  • 16) 0.468 421 977 800 704 × 2 = 0 + 0.936 843 955 601 408;
  • 17) 0.936 843 955 601 408 × 2 = 1 + 0.873 687 911 202 816;
  • 18) 0.873 687 911 202 816 × 2 = 1 + 0.747 375 822 405 632;
  • 19) 0.747 375 822 405 632 × 2 = 1 + 0.494 751 644 811 264;
  • 20) 0.494 751 644 811 264 × 2 = 0 + 0.989 503 289 622 528;
  • 21) 0.989 503 289 622 528 × 2 = 1 + 0.979 006 579 245 056;
  • 22) 0.979 006 579 245 056 × 2 = 1 + 0.958 013 158 490 112;
  • 23) 0.958 013 158 490 112 × 2 = 1 + 0.916 026 316 980 224;
  • 24) 0.916 026 316 980 224 × 2 = 1 + 0.832 052 633 960 448;
  • 25) 0.832 052 633 960 448 × 2 = 1 + 0.664 105 267 920 896;
  • 26) 0.664 105 267 920 896 × 2 = 1 + 0.328 210 535 841 792;
  • 27) 0.328 210 535 841 792 × 2 = 0 + 0.656 421 071 683 584;
  • 28) 0.656 421 071 683 584 × 2 = 1 + 0.312 842 143 367 168;
  • 29) 0.312 842 143 367 168 × 2 = 0 + 0.625 684 286 734 336;
  • 30) 0.625 684 286 734 336 × 2 = 1 + 0.251 368 573 468 672;
  • 31) 0.251 368 573 468 672 × 2 = 0 + 0.502 737 146 937 344;
  • 32) 0.502 737 146 937 344 × 2 = 1 + 0.005 474 293 874 688;
  • 33) 0.005 474 293 874 688 × 2 = 0 + 0.010 948 587 749 376;
  • 34) 0.010 948 587 749 376 × 2 = 0 + 0.021 897 175 498 752;
  • 35) 0.021 897 175 498 752 × 2 = 0 + 0.043 794 350 997 504;
  • 36) 0.043 794 350 997 504 × 2 = 0 + 0.087 588 701 995 008;
  • 37) 0.087 588 701 995 008 × 2 = 0 + 0.175 177 403 990 016;
  • 38) 0.175 177 403 990 016 × 2 = 0 + 0.350 354 807 980 032;
  • 39) 0.350 354 807 980 032 × 2 = 0 + 0.700 709 615 960 064;
  • 40) 0.700 709 615 960 064 × 2 = 1 + 0.401 419 231 920 128;
  • 41) 0.401 419 231 920 128 × 2 = 0 + 0.802 838 463 840 256;
  • 42) 0.802 838 463 840 256 × 2 = 1 + 0.605 676 927 680 512;
  • 43) 0.605 676 927 680 512 × 2 = 1 + 0.211 353 855 361 024;
  • 44) 0.211 353 855 361 024 × 2 = 0 + 0.422 707 710 722 048;
  • 45) 0.422 707 710 722 048 × 2 = 0 + 0.845 415 421 444 096;
  • 46) 0.845 415 421 444 096 × 2 = 1 + 0.690 830 842 888 192;
  • 47) 0.690 830 842 888 192 × 2 = 1 + 0.381 661 685 776 384;
  • 48) 0.381 661 685 776 384 × 2 = 0 + 0.763 323 371 552 768;
  • 49) 0.763 323 371 552 768 × 2 = 1 + 0.526 646 743 105 536;
  • 50) 0.526 646 743 105 536 × 2 = 1 + 0.053 293 486 211 072;
  • 51) 0.053 293 486 211 072 × 2 = 0 + 0.106 586 972 422 144;
  • 52) 0.106 586 972 422 144 × 2 = 0 + 0.213 173 944 844 288;
  • 53) 0.213 173 944 844 288 × 2 = 0 + 0.426 347 889 688 576;

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:


0.974 013 318 541 803(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0110 0110 1100 0(2)

5. Positive number before normalization:

0.974 013 318 541 803(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0110 0110 1100 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:


0.974 013 318 541 803(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0110 0110 1100 0(2) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0110 0110 1100 0(2) × 20 =


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


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 1101 1000 =


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


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 1101 1000


Decimal number 0.974 013 318 541 803 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 1101 1000


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