-0.000 282 006 314 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 314(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
-0.000 282 006 314(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. Start with the positive version of the number:

|-0.000 282 006 314| = 0.000 282 006 314


2. 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;

3. 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)


4. Convert to binary (base 2) the fractional part: 0.000 282 006 314.

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) 0.000 282 006 314 × 2 = 0 + 0.000 564 012 628;
  • 2) 0.000 564 012 628 × 2 = 0 + 0.001 128 025 256;
  • 3) 0.001 128 025 256 × 2 = 0 + 0.002 256 050 512;
  • 4) 0.002 256 050 512 × 2 = 0 + 0.004 512 101 024;
  • 5) 0.004 512 101 024 × 2 = 0 + 0.009 024 202 048;
  • 6) 0.009 024 202 048 × 2 = 0 + 0.018 048 404 096;
  • 7) 0.018 048 404 096 × 2 = 0 + 0.036 096 808 192;
  • 8) 0.036 096 808 192 × 2 = 0 + 0.072 193 616 384;
  • 9) 0.072 193 616 384 × 2 = 0 + 0.144 387 232 768;
  • 10) 0.144 387 232 768 × 2 = 0 + 0.288 774 465 536;
  • 11) 0.288 774 465 536 × 2 = 0 + 0.577 548 931 072;
  • 12) 0.577 548 931 072 × 2 = 1 + 0.155 097 862 144;
  • 13) 0.155 097 862 144 × 2 = 0 + 0.310 195 724 288;
  • 14) 0.310 195 724 288 × 2 = 0 + 0.620 391 448 576;
  • 15) 0.620 391 448 576 × 2 = 1 + 0.240 782 897 152;
  • 16) 0.240 782 897 152 × 2 = 0 + 0.481 565 794 304;
  • 17) 0.481 565 794 304 × 2 = 0 + 0.963 131 588 608;
  • 18) 0.963 131 588 608 × 2 = 1 + 0.926 263 177 216;
  • 19) 0.926 263 177 216 × 2 = 1 + 0.852 526 354 432;
  • 20) 0.852 526 354 432 × 2 = 1 + 0.705 052 708 864;
  • 21) 0.705 052 708 864 × 2 = 1 + 0.410 105 417 728;
  • 22) 0.410 105 417 728 × 2 = 0 + 0.820 210 835 456;
  • 23) 0.820 210 835 456 × 2 = 1 + 0.640 421 670 912;
  • 24) 0.640 421 670 912 × 2 = 1 + 0.280 843 341 824;
  • 25) 0.280 843 341 824 × 2 = 0 + 0.561 686 683 648;
  • 26) 0.561 686 683 648 × 2 = 1 + 0.123 373 367 296;
  • 27) 0.123 373 367 296 × 2 = 0 + 0.246 746 734 592;
  • 28) 0.246 746 734 592 × 2 = 0 + 0.493 493 469 184;
  • 29) 0.493 493 469 184 × 2 = 0 + 0.986 986 938 368;
  • 30) 0.986 986 938 368 × 2 = 1 + 0.973 973 876 736;
  • 31) 0.973 973 876 736 × 2 = 1 + 0.947 947 753 472;
  • 32) 0.947 947 753 472 × 2 = 1 + 0.895 895 506 944;
  • 33) 0.895 895 506 944 × 2 = 1 + 0.791 791 013 888;
  • 34) 0.791 791 013 888 × 2 = 1 + 0.583 582 027 776;
  • 35) 0.583 582 027 776 × 2 = 1 + 0.167 164 055 552;
  • 36) 0.167 164 055 552 × 2 = 0 + 0.334 328 111 104;
  • 37) 0.334 328 111 104 × 2 = 0 + 0.668 656 222 208;
  • 38) 0.668 656 222 208 × 2 = 1 + 0.337 312 444 416;
  • 39) 0.337 312 444 416 × 2 = 0 + 0.674 624 888 832;
  • 40) 0.674 624 888 832 × 2 = 1 + 0.349 249 777 664;
  • 41) 0.349 249 777 664 × 2 = 0 + 0.698 499 555 328;
  • 42) 0.698 499 555 328 × 2 = 1 + 0.396 999 110 656;
  • 43) 0.396 999 110 656 × 2 = 0 + 0.793 998 221 312;
  • 44) 0.793 998 221 312 × 2 = 1 + 0.587 996 442 624;
  • 45) 0.587 996 442 624 × 2 = 1 + 0.175 992 885 248;
  • 46) 0.175 992 885 248 × 2 = 0 + 0.351 985 770 496;
  • 47) 0.351 985 770 496 × 2 = 0 + 0.703 971 540 992;
  • 48) 0.703 971 540 992 × 2 = 1 + 0.407 943 081 984;
  • 49) 0.407 943 081 984 × 2 = 0 + 0.815 886 163 968;
  • 50) 0.815 886 163 968 × 2 = 1 + 0.631 772 327 936;
  • 51) 0.631 772 327 936 × 2 = 1 + 0.263 544 655 872;
  • 52) 0.263 544 655 872 × 2 = 0 + 0.527 089 311 744;
  • 53) 0.527 089 311 744 × 2 = 1 + 0.054 178 623 488;
  • 54) 0.054 178 623 488 × 2 = 0 + 0.108 357 246 976;
  • 55) 0.108 357 246 976 × 2 = 0 + 0.216 714 493 952;
  • 56) 0.216 714 493 952 × 2 = 0 + 0.433 428 987 904;
  • 57) 0.433 428 987 904 × 2 = 0 + 0.866 857 975 808;
  • 58) 0.866 857 975 808 × 2 = 1 + 0.733 715 951 616;
  • 59) 0.733 715 951 616 × 2 = 1 + 0.467 431 903 232;
  • 60) 0.467 431 903 232 × 2 = 0 + 0.934 863 806 464;
  • 61) 0.934 863 806 464 × 2 = 1 + 0.869 727 612 928;
  • 62) 0.869 727 612 928 × 2 = 1 + 0.739 455 225 856;
  • 63) 0.739 455 225 856 × 2 = 1 + 0.478 910 451 712;
  • 64) 0.478 910 451 712 × 2 = 0 + 0.957 820 903 424;

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).


5. 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:


0.000 282 006 314(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1110 0101 0101 1001 0110 1000 0110 1110(2)

6. Positive number before normalization:

0.000 282 006 314(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1110 0101 0101 1001 0110 1000 0110 1110(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 12 positions to the right, so that only one non zero digit remains to the left of it:


0.000 282 006 314(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1110 0101 0101 1001 0110 1000 0110 1110(2) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1110 0101 0101 1001 0110 1000 0110 1110(2) × 20 =


1.0010 0111 1011 0100 0111 1110 0101 0101 1001 0110 1000 0110 1110(2) × 2-12


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): -12


Mantissa (not normalized):
1.0010 0111 1011 0100 0111 1110 0101 0101 1001 0110 1000 0110 1110


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-12 + 2(11-1) - 1 =


(-12 + 1 023)(10) =


1 011(10)


10. 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;
  • 1 011 ÷ 2 = 505 + 1;
  • 505 ÷ 2 = 252 + 1;
  • 252 ÷ 2 = 126 + 0;
  • 126 ÷ 2 = 63 + 0;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

11. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1011(10) =


011 1111 0011(2)


12. 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. 0010 0111 1011 0100 0111 1110 0101 0101 1001 0110 1000 0110 1110 =


0010 0111 1011 0100 0111 1110 0101 0101 1001 0110 1000 0110 1110


13. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
1 (a negative number)


Exponent (11 bits) =
011 1111 0011


Mantissa (52 bits) =
0010 0111 1011 0100 0111 1110 0101 0101 1001 0110 1000 0110 1110


Decimal number -0.000 282 006 314 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0111 1110 0101 0101 1001 0110 1000 0110 1110


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