262 192.005 860 090 313 944 965 600 966 41 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 262 192.005 860 090 313 944 965 600 966 41(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
262 192.005 860 090 313 944 965 600 966 41(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: 262 192.
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;
  • 262 192 ÷ 2 = 131 096 + 0;
  • 131 096 ÷ 2 = 65 548 + 0;
  • 65 548 ÷ 2 = 32 774 + 0;
  • 32 774 ÷ 2 = 16 387 + 0;
  • 16 387 ÷ 2 = 8 193 + 1;
  • 8 193 ÷ 2 = 4 096 + 1;
  • 4 096 ÷ 2 = 2 048 + 0;
  • 2 048 ÷ 2 = 1 024 + 0;
  • 1 024 ÷ 2 = 512 + 0;
  • 512 ÷ 2 = 256 + 0;
  • 256 ÷ 2 = 128 + 0;
  • 128 ÷ 2 = 64 + 0;
  • 64 ÷ 2 = 32 + 0;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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.

262 192(10) =


100 0000 0000 0011 0000(2)


3. Convert to binary (base 2) the fractional part: 0.005 860 090 313 944 965 600 966 41.

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) 0.005 860 090 313 944 965 600 966 41 × 2 = 0 + 0.011 720 180 627 889 931 201 932 82;
  • 2) 0.011 720 180 627 889 931 201 932 82 × 2 = 0 + 0.023 440 361 255 779 862 403 865 64;
  • 3) 0.023 440 361 255 779 862 403 865 64 × 2 = 0 + 0.046 880 722 511 559 724 807 731 28;
  • 4) 0.046 880 722 511 559 724 807 731 28 × 2 = 0 + 0.093 761 445 023 119 449 615 462 56;
  • 5) 0.093 761 445 023 119 449 615 462 56 × 2 = 0 + 0.187 522 890 046 238 899 230 925 12;
  • 6) 0.187 522 890 046 238 899 230 925 12 × 2 = 0 + 0.375 045 780 092 477 798 461 850 24;
  • 7) 0.375 045 780 092 477 798 461 850 24 × 2 = 0 + 0.750 091 560 184 955 596 923 700 48;
  • 8) 0.750 091 560 184 955 596 923 700 48 × 2 = 1 + 0.500 183 120 369 911 193 847 400 96;
  • 9) 0.500 183 120 369 911 193 847 400 96 × 2 = 1 + 0.000 366 240 739 822 387 694 801 92;
  • 10) 0.000 366 240 739 822 387 694 801 92 × 2 = 0 + 0.000 732 481 479 644 775 389 603 84;
  • 11) 0.000 732 481 479 644 775 389 603 84 × 2 = 0 + 0.001 464 962 959 289 550 779 207 68;
  • 12) 0.001 464 962 959 289 550 779 207 68 × 2 = 0 + 0.002 929 925 918 579 101 558 415 36;
  • 13) 0.002 929 925 918 579 101 558 415 36 × 2 = 0 + 0.005 859 851 837 158 203 116 830 72;
  • 14) 0.005 859 851 837 158 203 116 830 72 × 2 = 0 + 0.011 719 703 674 316 406 233 661 44;
  • 15) 0.011 719 703 674 316 406 233 661 44 × 2 = 0 + 0.023 439 407 348 632 812 467 322 88;
  • 16) 0.023 439 407 348 632 812 467 322 88 × 2 = 0 + 0.046 878 814 697 265 624 934 645 76;
  • 17) 0.046 878 814 697 265 624 934 645 76 × 2 = 0 + 0.093 757 629 394 531 249 869 291 52;
  • 18) 0.093 757 629 394 531 249 869 291 52 × 2 = 0 + 0.187 515 258 789 062 499 738 583 04;
  • 19) 0.187 515 258 789 062 499 738 583 04 × 2 = 0 + 0.375 030 517 578 124 999 477 166 08;
  • 20) 0.375 030 517 578 124 999 477 166 08 × 2 = 0 + 0.750 061 035 156 249 998 954 332 16;
  • 21) 0.750 061 035 156 249 998 954 332 16 × 2 = 1 + 0.500 122 070 312 499 997 908 664 32;
  • 22) 0.500 122 070 312 499 997 908 664 32 × 2 = 1 + 0.000 244 140 624 999 995 817 328 64;
  • 23) 0.000 244 140 624 999 995 817 328 64 × 2 = 0 + 0.000 488 281 249 999 991 634 657 28;
  • 24) 0.000 488 281 249 999 991 634 657 28 × 2 = 0 + 0.000 976 562 499 999 983 269 314 56;
  • 25) 0.000 976 562 499 999 983 269 314 56 × 2 = 0 + 0.001 953 124 999 999 966 538 629 12;
  • 26) 0.001 953 124 999 999 966 538 629 12 × 2 = 0 + 0.003 906 249 999 999 933 077 258 24;
  • 27) 0.003 906 249 999 999 933 077 258 24 × 2 = 0 + 0.007 812 499 999 999 866 154 516 48;
  • 28) 0.007 812 499 999 999 866 154 516 48 × 2 = 0 + 0.015 624 999 999 999 732 309 032 96;
  • 29) 0.015 624 999 999 999 732 309 032 96 × 2 = 0 + 0.031 249 999 999 999 464 618 065 92;
  • 30) 0.031 249 999 999 999 464 618 065 92 × 2 = 0 + 0.062 499 999 999 998 929 236 131 84;
  • 31) 0.062 499 999 999 998 929 236 131 84 × 2 = 0 + 0.124 999 999 999 997 858 472 263 68;
  • 32) 0.124 999 999 999 997 858 472 263 68 × 2 = 0 + 0.249 999 999 999 995 716 944 527 36;
  • 33) 0.249 999 999 999 995 716 944 527 36 × 2 = 0 + 0.499 999 999 999 991 433 889 054 72;
  • 34) 0.499 999 999 999 991 433 889 054 72 × 2 = 0 + 0.999 999 999 999 982 867 778 109 44;
  • 35) 0.999 999 999 999 982 867 778 109 44 × 2 = 1 + 0.999 999 999 999 965 735 556 218 88;
  • 36) 0.999 999 999 999 965 735 556 218 88 × 2 = 1 + 0.999 999 999 999 931 471 112 437 76;
  • 37) 0.999 999 999 999 931 471 112 437 76 × 2 = 1 + 0.999 999 999 999 862 942 224 875 52;
  • 38) 0.999 999 999 999 862 942 224 875 52 × 2 = 1 + 0.999 999 999 999 725 884 449 751 04;
  • 39) 0.999 999 999 999 725 884 449 751 04 × 2 = 1 + 0.999 999 999 999 451 768 899 502 08;
  • 40) 0.999 999 999 999 451 768 899 502 08 × 2 = 1 + 0.999 999 999 998 903 537 799 004 16;
  • 41) 0.999 999 999 998 903 537 799 004 16 × 2 = 1 + 0.999 999 999 997 807 075 598 008 32;
  • 42) 0.999 999 999 997 807 075 598 008 32 × 2 = 1 + 0.999 999 999 995 614 151 196 016 64;
  • 43) 0.999 999 999 995 614 151 196 016 64 × 2 = 1 + 0.999 999 999 991 228 302 392 033 28;
  • 44) 0.999 999 999 991 228 302 392 033 28 × 2 = 1 + 0.999 999 999 982 456 604 784 066 56;
  • 45) 0.999 999 999 982 456 604 784 066 56 × 2 = 1 + 0.999 999 999 964 913 209 568 133 12;
  • 46) 0.999 999 999 964 913 209 568 133 12 × 2 = 1 + 0.999 999 999 929 826 419 136 266 24;
  • 47) 0.999 999 999 929 826 419 136 266 24 × 2 = 1 + 0.999 999 999 859 652 838 272 532 48;
  • 48) 0.999 999 999 859 652 838 272 532 48 × 2 = 1 + 0.999 999 999 719 305 676 545 064 96;
  • 49) 0.999 999 999 719 305 676 545 064 96 × 2 = 1 + 0.999 999 999 438 611 353 090 129 92;
  • 50) 0.999 999 999 438 611 353 090 129 92 × 2 = 1 + 0.999 999 998 877 222 706 180 259 84;
  • 51) 0.999 999 998 877 222 706 180 259 84 × 2 = 1 + 0.999 999 997 754 445 412 360 519 68;
  • 52) 0.999 999 997 754 445 412 360 519 68 × 2 = 1 + 0.999 999 995 508 890 824 721 039 36;
  • 53) 0.999 999 995 508 890 824 721 039 36 × 2 = 1 + 0.999 999 991 017 781 649 442 078 72;

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:


0.005 860 090 313 944 965 600 966 41(10) =


0.0000 0001 1000 0000 0000 1100 0000 0000 0011 1111 1111 1111 1111 1(2)

5. Positive number before normalization:

262 192.005 860 090 313 944 965 600 966 41(10) =


100 0000 0000 0011 0000.0000 0001 1000 0000 0000 1100 0000 0000 0011 1111 1111 1111 1111 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 18 positions to the left, so that only one non zero digit remains to the left of it:


262 192.005 860 090 313 944 965 600 966 41(10) =


100 0000 0000 0011 0000.0000 0001 1000 0000 0000 1100 0000 0000 0011 1111 1111 1111 1111 1(2) =


100 0000 0000 0011 0000.0000 0001 1000 0000 0000 1100 0000 0000 0011 1111 1111 1111 1111 1(2) × 20 =


1.0000 0000 0000 1100 0000 0000 0110 0000 0000 0011 0000 0000 0000 1111 1111 1111 1111 111(2) × 218


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): 18


Mantissa (not normalized):
1.0000 0000 0000 1100 0000 0000 0110 0000 0000 0011 0000 0000 0000 1111 1111 1111 1111 111


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


18 + 2(11-1) - 1 =


(18 + 1 023)(10) =


1 041(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;
  • 1 041 ÷ 2 = 520 + 1;
  • 520 ÷ 2 = 260 + 0;
  • 260 ÷ 2 = 130 + 0;
  • 130 ÷ 2 = 65 + 0;
  • 65 ÷ 2 = 32 + 1;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 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) =


1041(10) =


100 0001 0001(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, by removing the excess bits, from the right (if any of the excess bits is set on 1, we are losing precision...).


Mantissa (normalized) =


1. 0000 0000 0000 1100 0000 0000 0110 0000 0000 0011 0000 0000 0000 111 1111 1111 1111 1111 =


0000 0000 0000 1100 0000 0000 0110 0000 0000 0011 0000 0000 0000


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) =
100 0001 0001


Mantissa (52 bits) =
0000 0000 0000 1100 0000 0000 0110 0000 0000 0011 0000 0000 0000


Decimal number 262 192.005 860 090 313 944 965 600 966 41 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0001 0001 - 0000 0000 0000 1100 0000 0000 0110 0000 0000 0011 0000 0000 0000

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