-0.000 282 007 7 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 007 7(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
-0.000 282 007 7(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:

|-0.000 282 007 7| = 0.000 282 007 7


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: 0.000 282 007 7.

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) 0.000 282 007 7 × 2 = 0 + 0.000 564 015 4;
  • 2) 0.000 564 015 4 × 2 = 0 + 0.001 128 030 8;
  • 3) 0.001 128 030 8 × 2 = 0 + 0.002 256 061 6;
  • 4) 0.002 256 061 6 × 2 = 0 + 0.004 512 123 2;
  • 5) 0.004 512 123 2 × 2 = 0 + 0.009 024 246 4;
  • 6) 0.009 024 246 4 × 2 = 0 + 0.018 048 492 8;
  • 7) 0.018 048 492 8 × 2 = 0 + 0.036 096 985 6;
  • 8) 0.036 096 985 6 × 2 = 0 + 0.072 193 971 2;
  • 9) 0.072 193 971 2 × 2 = 0 + 0.144 387 942 4;
  • 10) 0.144 387 942 4 × 2 = 0 + 0.288 775 884 8;
  • 11) 0.288 775 884 8 × 2 = 0 + 0.577 551 769 6;
  • 12) 0.577 551 769 6 × 2 = 1 + 0.155 103 539 2;
  • 13) 0.155 103 539 2 × 2 = 0 + 0.310 207 078 4;
  • 14) 0.310 207 078 4 × 2 = 0 + 0.620 414 156 8;
  • 15) 0.620 414 156 8 × 2 = 1 + 0.240 828 313 6;
  • 16) 0.240 828 313 6 × 2 = 0 + 0.481 656 627 2;
  • 17) 0.481 656 627 2 × 2 = 0 + 0.963 313 254 4;
  • 18) 0.963 313 254 4 × 2 = 1 + 0.926 626 508 8;
  • 19) 0.926 626 508 8 × 2 = 1 + 0.853 253 017 6;
  • 20) 0.853 253 017 6 × 2 = 1 + 0.706 506 035 2;
  • 21) 0.706 506 035 2 × 2 = 1 + 0.413 012 070 4;
  • 22) 0.413 012 070 4 × 2 = 0 + 0.826 024 140 8;
  • 23) 0.826 024 140 8 × 2 = 1 + 0.652 048 281 6;
  • 24) 0.652 048 281 6 × 2 = 1 + 0.304 096 563 2;
  • 25) 0.304 096 563 2 × 2 = 0 + 0.608 193 126 4;
  • 26) 0.608 193 126 4 × 2 = 1 + 0.216 386 252 8;
  • 27) 0.216 386 252 8 × 2 = 0 + 0.432 772 505 6;
  • 28) 0.432 772 505 6 × 2 = 0 + 0.865 545 011 2;
  • 29) 0.865 545 011 2 × 2 = 1 + 0.731 090 022 4;
  • 30) 0.731 090 022 4 × 2 = 1 + 0.462 180 044 8;
  • 31) 0.462 180 044 8 × 2 = 0 + 0.924 360 089 6;
  • 32) 0.924 360 089 6 × 2 = 1 + 0.848 720 179 2;
  • 33) 0.848 720 179 2 × 2 = 1 + 0.697 440 358 4;
  • 34) 0.697 440 358 4 × 2 = 1 + 0.394 880 716 8;
  • 35) 0.394 880 716 8 × 2 = 0 + 0.789 761 433 6;
  • 36) 0.789 761 433 6 × 2 = 1 + 0.579 522 867 2;
  • 37) 0.579 522 867 2 × 2 = 1 + 0.159 045 734 4;
  • 38) 0.159 045 734 4 × 2 = 0 + 0.318 091 468 8;
  • 39) 0.318 091 468 8 × 2 = 0 + 0.636 182 937 6;
  • 40) 0.636 182 937 6 × 2 = 1 + 0.272 365 875 2;
  • 41) 0.272 365 875 2 × 2 = 0 + 0.544 731 750 4;
  • 42) 0.544 731 750 4 × 2 = 1 + 0.089 463 500 8;
  • 43) 0.089 463 500 8 × 2 = 0 + 0.178 927 001 6;
  • 44) 0.178 927 001 6 × 2 = 0 + 0.357 854 003 2;
  • 45) 0.357 854 003 2 × 2 = 0 + 0.715 708 006 4;
  • 46) 0.715 708 006 4 × 2 = 1 + 0.431 416 012 8;
  • 47) 0.431 416 012 8 × 2 = 0 + 0.862 832 025 6;
  • 48) 0.862 832 025 6 × 2 = 1 + 0.725 664 051 2;
  • 49) 0.725 664 051 2 × 2 = 1 + 0.451 328 102 4;
  • 50) 0.451 328 102 4 × 2 = 0 + 0.902 656 204 8;
  • 51) 0.902 656 204 8 × 2 = 1 + 0.805 312 409 6;
  • 52) 0.805 312 409 6 × 2 = 1 + 0.610 624 819 2;
  • 53) 0.610 624 819 2 × 2 = 1 + 0.221 249 638 4;
  • 54) 0.221 249 638 4 × 2 = 0 + 0.442 499 276 8;
  • 55) 0.442 499 276 8 × 2 = 0 + 0.884 998 553 6;
  • 56) 0.884 998 553 6 × 2 = 1 + 0.769 997 107 2;
  • 57) 0.769 997 107 2 × 2 = 1 + 0.539 994 214 4;
  • 58) 0.539 994 214 4 × 2 = 1 + 0.079 988 428 8;
  • 59) 0.079 988 428 8 × 2 = 0 + 0.159 976 857 6;
  • 60) 0.159 976 857 6 × 2 = 0 + 0.319 953 715 2;
  • 61) 0.319 953 715 2 × 2 = 0 + 0.639 907 430 4;
  • 62) 0.639 907 430 4 × 2 = 1 + 0.279 814 860 8;
  • 63) 0.279 814 860 8 × 2 = 0 + 0.559 629 721 6;
  • 64) 0.559 629 721 6 × 2 = 1 + 0.119 259 443 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:


0.000 282 007 7(10) =


0.0000 0000 0001 0010 0111 1011 0100 1101 1101 1001 0100 0101 1011 1001 1100 0101(2)

6. Positive number before normalization:

0.000 282 007 7(10) =


0.0000 0000 0001 0010 0111 1011 0100 1101 1101 1001 0100 0101 1011 1001 1100 0101(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:


0.000 282 007 7(10) =


0.0000 0000 0001 0010 0111 1011 0100 1101 1101 1001 0100 0101 1011 1001 1100 0101(2) =


0.0000 0000 0001 0010 0111 1011 0100 1101 1101 1001 0100 0101 1011 1001 1100 0101(2) × 20 =


1.0010 0111 1011 0100 1101 1101 1001 0100 0101 1011 1001 1100 0101(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 1101 1101 1001 0100 0101 1011 1001 1100 0101


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 1101 1101 1001 0100 0101 1011 1001 1100 0101 =


0010 0111 1011 0100 1101 1101 1001 0100 0101 1011 1001 1100 0101


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 1101 1101 1001 0100 0101 1011 1001 1100 0101


Decimal number -0.000 282 007 7 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 1101 1101 1001 0100 0101 1011 1001 1100 0101


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