-0.000 282 005 916 18 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 916 18(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
-0.000 282 005 916 18(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:

|-0.000 282 005 916 18| = 0.000 282 005 916 18


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: 0.000 282 005 916 18.

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) 0.000 282 005 916 18 × 2 = 0 + 0.000 564 011 832 36;
  • 2) 0.000 564 011 832 36 × 2 = 0 + 0.001 128 023 664 72;
  • 3) 0.001 128 023 664 72 × 2 = 0 + 0.002 256 047 329 44;
  • 4) 0.002 256 047 329 44 × 2 = 0 + 0.004 512 094 658 88;
  • 5) 0.004 512 094 658 88 × 2 = 0 + 0.009 024 189 317 76;
  • 6) 0.009 024 189 317 76 × 2 = 0 + 0.018 048 378 635 52;
  • 7) 0.018 048 378 635 52 × 2 = 0 + 0.036 096 757 271 04;
  • 8) 0.036 096 757 271 04 × 2 = 0 + 0.072 193 514 542 08;
  • 9) 0.072 193 514 542 08 × 2 = 0 + 0.144 387 029 084 16;
  • 10) 0.144 387 029 084 16 × 2 = 0 + 0.288 774 058 168 32;
  • 11) 0.288 774 058 168 32 × 2 = 0 + 0.577 548 116 336 64;
  • 12) 0.577 548 116 336 64 × 2 = 1 + 0.155 096 232 673 28;
  • 13) 0.155 096 232 673 28 × 2 = 0 + 0.310 192 465 346 56;
  • 14) 0.310 192 465 346 56 × 2 = 0 + 0.620 384 930 693 12;
  • 15) 0.620 384 930 693 12 × 2 = 1 + 0.240 769 861 386 24;
  • 16) 0.240 769 861 386 24 × 2 = 0 + 0.481 539 722 772 48;
  • 17) 0.481 539 722 772 48 × 2 = 0 + 0.963 079 445 544 96;
  • 18) 0.963 079 445 544 96 × 2 = 1 + 0.926 158 891 089 92;
  • 19) 0.926 158 891 089 92 × 2 = 1 + 0.852 317 782 179 84;
  • 20) 0.852 317 782 179 84 × 2 = 1 + 0.704 635 564 359 68;
  • 21) 0.704 635 564 359 68 × 2 = 1 + 0.409 271 128 719 36;
  • 22) 0.409 271 128 719 36 × 2 = 0 + 0.818 542 257 438 72;
  • 23) 0.818 542 257 438 72 × 2 = 1 + 0.637 084 514 877 44;
  • 24) 0.637 084 514 877 44 × 2 = 1 + 0.274 169 029 754 88;
  • 25) 0.274 169 029 754 88 × 2 = 0 + 0.548 338 059 509 76;
  • 26) 0.548 338 059 509 76 × 2 = 1 + 0.096 676 119 019 52;
  • 27) 0.096 676 119 019 52 × 2 = 0 + 0.193 352 238 039 04;
  • 28) 0.193 352 238 039 04 × 2 = 0 + 0.386 704 476 078 08;
  • 29) 0.386 704 476 078 08 × 2 = 0 + 0.773 408 952 156 16;
  • 30) 0.773 408 952 156 16 × 2 = 1 + 0.546 817 904 312 32;
  • 31) 0.546 817 904 312 32 × 2 = 1 + 0.093 635 808 624 64;
  • 32) 0.093 635 808 624 64 × 2 = 0 + 0.187 271 617 249 28;
  • 33) 0.187 271 617 249 28 × 2 = 0 + 0.374 543 234 498 56;
  • 34) 0.374 543 234 498 56 × 2 = 0 + 0.749 086 468 997 12;
  • 35) 0.749 086 468 997 12 × 2 = 1 + 0.498 172 937 994 24;
  • 36) 0.498 172 937 994 24 × 2 = 0 + 0.996 345 875 988 48;
  • 37) 0.996 345 875 988 48 × 2 = 1 + 0.992 691 751 976 96;
  • 38) 0.992 691 751 976 96 × 2 = 1 + 0.985 383 503 953 92;
  • 39) 0.985 383 503 953 92 × 2 = 1 + 0.970 767 007 907 84;
  • 40) 0.970 767 007 907 84 × 2 = 1 + 0.941 534 015 815 68;
  • 41) 0.941 534 015 815 68 × 2 = 1 + 0.883 068 031 631 36;
  • 42) 0.883 068 031 631 36 × 2 = 1 + 0.766 136 063 262 72;
  • 43) 0.766 136 063 262 72 × 2 = 1 + 0.532 272 126 525 44;
  • 44) 0.532 272 126 525 44 × 2 = 1 + 0.064 544 253 050 88;
  • 45) 0.064 544 253 050 88 × 2 = 0 + 0.129 088 506 101 76;
  • 46) 0.129 088 506 101 76 × 2 = 0 + 0.258 177 012 203 52;
  • 47) 0.258 177 012 203 52 × 2 = 0 + 0.516 354 024 407 04;
  • 48) 0.516 354 024 407 04 × 2 = 1 + 0.032 708 048 814 08;
  • 49) 0.032 708 048 814 08 × 2 = 0 + 0.065 416 097 628 16;
  • 50) 0.065 416 097 628 16 × 2 = 0 + 0.130 832 195 256 32;
  • 51) 0.130 832 195 256 32 × 2 = 0 + 0.261 664 390 512 64;
  • 52) 0.261 664 390 512 64 × 2 = 0 + 0.523 328 781 025 28;
  • 53) 0.523 328 781 025 28 × 2 = 1 + 0.046 657 562 050 56;
  • 54) 0.046 657 562 050 56 × 2 = 0 + 0.093 315 124 101 12;
  • 55) 0.093 315 124 101 12 × 2 = 0 + 0.186 630 248 202 24;
  • 56) 0.186 630 248 202 24 × 2 = 0 + 0.373 260 496 404 48;
  • 57) 0.373 260 496 404 48 × 2 = 0 + 0.746 520 992 808 96;
  • 58) 0.746 520 992 808 96 × 2 = 1 + 0.493 041 985 617 92;
  • 59) 0.493 041 985 617 92 × 2 = 0 + 0.986 083 971 235 84;
  • 60) 0.986 083 971 235 84 × 2 = 1 + 0.972 167 942 471 68;
  • 61) 0.972 167 942 471 68 × 2 = 1 + 0.944 335 884 943 36;
  • 62) 0.944 335 884 943 36 × 2 = 1 + 0.888 671 769 886 72;
  • 63) 0.888 671 769 886 72 × 2 = 1 + 0.777 343 539 773 44;
  • 64) 0.777 343 539 773 44 × 2 = 1 + 0.554 687 079 546 88;

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:


0.000 282 005 916 18(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1111 1111 0001 0000 1000 0101 1111(2)

6. Positive number before normalization:

0.000 282 005 916 18(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1111 1111 0001 0000 1000 0101 1111(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:


0.000 282 005 916 18(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1111 1111 0001 0000 1000 0101 1111(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1111 1111 0001 0000 1000 0101 1111(2) × 20 =


1.0010 0111 1011 0100 0110 0010 1111 1111 0001 0000 1000 0101 1111(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 0010 1111 1111 0001 0000 1000 0101 1111


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 0010 1111 1111 0001 0000 1000 0101 1111 =


0010 0111 1011 0100 0110 0010 1111 1111 0001 0000 1000 0101 1111


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 0010 1111 1111 0001 0000 1000 0101 1111


Decimal number -0.000 282 005 916 18 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0010 1111 1111 0001 0000 1000 0101 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