-0.000 282 005 886 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 886 2(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
-0.000 282 005 886 2(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:

|-0.000 282 005 886 2| = 0.000 282 005 886 2


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: 0.000 282 005 886 2.

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) 0.000 282 005 886 2 × 2 = 0 + 0.000 564 011 772 4;
  • 2) 0.000 564 011 772 4 × 2 = 0 + 0.001 128 023 544 8;
  • 3) 0.001 128 023 544 8 × 2 = 0 + 0.002 256 047 089 6;
  • 4) 0.002 256 047 089 6 × 2 = 0 + 0.004 512 094 179 2;
  • 5) 0.004 512 094 179 2 × 2 = 0 + 0.009 024 188 358 4;
  • 6) 0.009 024 188 358 4 × 2 = 0 + 0.018 048 376 716 8;
  • 7) 0.018 048 376 716 8 × 2 = 0 + 0.036 096 753 433 6;
  • 8) 0.036 096 753 433 6 × 2 = 0 + 0.072 193 506 867 2;
  • 9) 0.072 193 506 867 2 × 2 = 0 + 0.144 387 013 734 4;
  • 10) 0.144 387 013 734 4 × 2 = 0 + 0.288 774 027 468 8;
  • 11) 0.288 774 027 468 8 × 2 = 0 + 0.577 548 054 937 6;
  • 12) 0.577 548 054 937 6 × 2 = 1 + 0.155 096 109 875 2;
  • 13) 0.155 096 109 875 2 × 2 = 0 + 0.310 192 219 750 4;
  • 14) 0.310 192 219 750 4 × 2 = 0 + 0.620 384 439 500 8;
  • 15) 0.620 384 439 500 8 × 2 = 1 + 0.240 768 879 001 6;
  • 16) 0.240 768 879 001 6 × 2 = 0 + 0.481 537 758 003 2;
  • 17) 0.481 537 758 003 2 × 2 = 0 + 0.963 075 516 006 4;
  • 18) 0.963 075 516 006 4 × 2 = 1 + 0.926 151 032 012 8;
  • 19) 0.926 151 032 012 8 × 2 = 1 + 0.852 302 064 025 6;
  • 20) 0.852 302 064 025 6 × 2 = 1 + 0.704 604 128 051 2;
  • 21) 0.704 604 128 051 2 × 2 = 1 + 0.409 208 256 102 4;
  • 22) 0.409 208 256 102 4 × 2 = 0 + 0.818 416 512 204 8;
  • 23) 0.818 416 512 204 8 × 2 = 1 + 0.636 833 024 409 6;
  • 24) 0.636 833 024 409 6 × 2 = 1 + 0.273 666 048 819 2;
  • 25) 0.273 666 048 819 2 × 2 = 0 + 0.547 332 097 638 4;
  • 26) 0.547 332 097 638 4 × 2 = 1 + 0.094 664 195 276 8;
  • 27) 0.094 664 195 276 8 × 2 = 0 + 0.189 328 390 553 6;
  • 28) 0.189 328 390 553 6 × 2 = 0 + 0.378 656 781 107 2;
  • 29) 0.378 656 781 107 2 × 2 = 0 + 0.757 313 562 214 4;
  • 30) 0.757 313 562 214 4 × 2 = 1 + 0.514 627 124 428 8;
  • 31) 0.514 627 124 428 8 × 2 = 1 + 0.029 254 248 857 6;
  • 32) 0.029 254 248 857 6 × 2 = 0 + 0.058 508 497 715 2;
  • 33) 0.058 508 497 715 2 × 2 = 0 + 0.117 016 995 430 4;
  • 34) 0.117 016 995 430 4 × 2 = 0 + 0.234 033 990 860 8;
  • 35) 0.234 033 990 860 8 × 2 = 0 + 0.468 067 981 721 6;
  • 36) 0.468 067 981 721 6 × 2 = 0 + 0.936 135 963 443 2;
  • 37) 0.936 135 963 443 2 × 2 = 1 + 0.872 271 926 886 4;
  • 38) 0.872 271 926 886 4 × 2 = 1 + 0.744 543 853 772 8;
  • 39) 0.744 543 853 772 8 × 2 = 1 + 0.489 087 707 545 6;
  • 40) 0.489 087 707 545 6 × 2 = 0 + 0.978 175 415 091 2;
  • 41) 0.978 175 415 091 2 × 2 = 1 + 0.956 350 830 182 4;
  • 42) 0.956 350 830 182 4 × 2 = 1 + 0.912 701 660 364 8;
  • 43) 0.912 701 660 364 8 × 2 = 1 + 0.825 403 320 729 6;
  • 44) 0.825 403 320 729 6 × 2 = 1 + 0.650 806 641 459 2;
  • 45) 0.650 806 641 459 2 × 2 = 1 + 0.301 613 282 918 4;
  • 46) 0.301 613 282 918 4 × 2 = 0 + 0.603 226 565 836 8;
  • 47) 0.603 226 565 836 8 × 2 = 1 + 0.206 453 131 673 6;
  • 48) 0.206 453 131 673 6 × 2 = 0 + 0.412 906 263 347 2;
  • 49) 0.412 906 263 347 2 × 2 = 0 + 0.825 812 526 694 4;
  • 50) 0.825 812 526 694 4 × 2 = 1 + 0.651 625 053 388 8;
  • 51) 0.651 625 053 388 8 × 2 = 1 + 0.303 250 106 777 6;
  • 52) 0.303 250 106 777 6 × 2 = 0 + 0.606 500 213 555 2;
  • 53) 0.606 500 213 555 2 × 2 = 1 + 0.213 000 427 110 4;
  • 54) 0.213 000 427 110 4 × 2 = 0 + 0.426 000 854 220 8;
  • 55) 0.426 000 854 220 8 × 2 = 0 + 0.852 001 708 441 6;
  • 56) 0.852 001 708 441 6 × 2 = 1 + 0.704 003 416 883 2;
  • 57) 0.704 003 416 883 2 × 2 = 1 + 0.408 006 833 766 4;
  • 58) 0.408 006 833 766 4 × 2 = 0 + 0.816 013 667 532 8;
  • 59) 0.816 013 667 532 8 × 2 = 1 + 0.632 027 335 065 6;
  • 60) 0.632 027 335 065 6 × 2 = 1 + 0.264 054 670 131 2;
  • 61) 0.264 054 670 131 2 × 2 = 0 + 0.528 109 340 262 4;
  • 62) 0.528 109 340 262 4 × 2 = 1 + 0.056 218 680 524 8;
  • 63) 0.056 218 680 524 8 × 2 = 0 + 0.112 437 361 049 6;
  • 64) 0.112 437 361 049 6 × 2 = 0 + 0.224 874 722 099 2;

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:


0.000 282 005 886 2(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 1110 1111 1010 0110 1001 1011 0100(2)

6. Positive number before normalization:

0.000 282 005 886 2(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 1110 1111 1010 0110 1001 1011 0100(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:


0.000 282 005 886 2(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 1110 1111 1010 0110 1001 1011 0100(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 1110 1111 1010 0110 1001 1011 0100(2) × 20 =


1.0010 0111 1011 0100 0110 0000 1110 1111 1010 0110 1001 1011 0100(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 0110 0000 1110 1111 1010 0110 1001 1011 0100


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 0110 0000 1110 1111 1010 0110 1001 1011 0100 =


0010 0111 1011 0100 0110 0000 1110 1111 1010 0110 1001 1011 0100


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 0110 0000 1110 1111 1010 0110 1001 1011 0100


Decimal number -0.000 282 005 886 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0000 1110 1111 1010 0110 1001 1011 0100


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