-0.000 282 021 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 021 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
-0.000 282 021 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:

|-0.000 282 021 2| = 0.000 282 021 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: 0.000 282 021 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) 0.000 282 021 2 × 2 = 0 + 0.000 564 042 4;
  • 2) 0.000 564 042 4 × 2 = 0 + 0.001 128 084 8;
  • 3) 0.001 128 084 8 × 2 = 0 + 0.002 256 169 6;
  • 4) 0.002 256 169 6 × 2 = 0 + 0.004 512 339 2;
  • 5) 0.004 512 339 2 × 2 = 0 + 0.009 024 678 4;
  • 6) 0.009 024 678 4 × 2 = 0 + 0.018 049 356 8;
  • 7) 0.018 049 356 8 × 2 = 0 + 0.036 098 713 6;
  • 8) 0.036 098 713 6 × 2 = 0 + 0.072 197 427 2;
  • 9) 0.072 197 427 2 × 2 = 0 + 0.144 394 854 4;
  • 10) 0.144 394 854 4 × 2 = 0 + 0.288 789 708 8;
  • 11) 0.288 789 708 8 × 2 = 0 + 0.577 579 417 6;
  • 12) 0.577 579 417 6 × 2 = 1 + 0.155 158 835 2;
  • 13) 0.155 158 835 2 × 2 = 0 + 0.310 317 670 4;
  • 14) 0.310 317 670 4 × 2 = 0 + 0.620 635 340 8;
  • 15) 0.620 635 340 8 × 2 = 1 + 0.241 270 681 6;
  • 16) 0.241 270 681 6 × 2 = 0 + 0.482 541 363 2;
  • 17) 0.482 541 363 2 × 2 = 0 + 0.965 082 726 4;
  • 18) 0.965 082 726 4 × 2 = 1 + 0.930 165 452 8;
  • 19) 0.930 165 452 8 × 2 = 1 + 0.860 330 905 6;
  • 20) 0.860 330 905 6 × 2 = 1 + 0.720 661 811 2;
  • 21) 0.720 661 811 2 × 2 = 1 + 0.441 323 622 4;
  • 22) 0.441 323 622 4 × 2 = 0 + 0.882 647 244 8;
  • 23) 0.882 647 244 8 × 2 = 1 + 0.765 294 489 6;
  • 24) 0.765 294 489 6 × 2 = 1 + 0.530 588 979 2;
  • 25) 0.530 588 979 2 × 2 = 1 + 0.061 177 958 4;
  • 26) 0.061 177 958 4 × 2 = 0 + 0.122 355 916 8;
  • 27) 0.122 355 916 8 × 2 = 0 + 0.244 711 833 6;
  • 28) 0.244 711 833 6 × 2 = 0 + 0.489 423 667 2;
  • 29) 0.489 423 667 2 × 2 = 0 + 0.978 847 334 4;
  • 30) 0.978 847 334 4 × 2 = 1 + 0.957 694 668 8;
  • 31) 0.957 694 668 8 × 2 = 1 + 0.915 389 337 6;
  • 32) 0.915 389 337 6 × 2 = 1 + 0.830 778 675 2;
  • 33) 0.830 778 675 2 × 2 = 1 + 0.661 557 350 4;
  • 34) 0.661 557 350 4 × 2 = 1 + 0.323 114 700 8;
  • 35) 0.323 114 700 8 × 2 = 0 + 0.646 229 401 6;
  • 36) 0.646 229 401 6 × 2 = 1 + 0.292 458 803 2;
  • 37) 0.292 458 803 2 × 2 = 0 + 0.584 917 606 4;
  • 38) 0.584 917 606 4 × 2 = 1 + 0.169 835 212 8;
  • 39) 0.169 835 212 8 × 2 = 0 + 0.339 670 425 6;
  • 40) 0.339 670 425 6 × 2 = 0 + 0.679 340 851 2;
  • 41) 0.679 340 851 2 × 2 = 1 + 0.358 681 702 4;
  • 42) 0.358 681 702 4 × 2 = 0 + 0.717 363 404 8;
  • 43) 0.717 363 404 8 × 2 = 1 + 0.434 726 809 6;
  • 44) 0.434 726 809 6 × 2 = 0 + 0.869 453 619 2;
  • 45) 0.869 453 619 2 × 2 = 1 + 0.738 907 238 4;
  • 46) 0.738 907 238 4 × 2 = 1 + 0.477 814 476 8;
  • 47) 0.477 814 476 8 × 2 = 0 + 0.955 628 953 6;
  • 48) 0.955 628 953 6 × 2 = 1 + 0.911 257 907 2;
  • 49) 0.911 257 907 2 × 2 = 1 + 0.822 515 814 4;
  • 50) 0.822 515 814 4 × 2 = 1 + 0.645 031 628 8;
  • 51) 0.645 031 628 8 × 2 = 1 + 0.290 063 257 6;
  • 52) 0.290 063 257 6 × 2 = 0 + 0.580 126 515 2;
  • 53) 0.580 126 515 2 × 2 = 1 + 0.160 253 030 4;
  • 54) 0.160 253 030 4 × 2 = 0 + 0.320 506 060 8;
  • 55) 0.320 506 060 8 × 2 = 0 + 0.641 012 121 6;
  • 56) 0.641 012 121 6 × 2 = 1 + 0.282 024 243 2;
  • 57) 0.282 024 243 2 × 2 = 0 + 0.564 048 486 4;
  • 58) 0.564 048 486 4 × 2 = 1 + 0.128 096 972 8;
  • 59) 0.128 096 972 8 × 2 = 0 + 0.256 193 945 6;
  • 60) 0.256 193 945 6 × 2 = 0 + 0.512 387 891 2;
  • 61) 0.512 387 891 2 × 2 = 1 + 0.024 775 782 4;
  • 62) 0.024 775 782 4 × 2 = 0 + 0.049 551 564 8;
  • 63) 0.049 551 564 8 × 2 = 0 + 0.099 103 129 6;
  • 64) 0.099 103 129 6 × 2 = 0 + 0.198 206 259 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:


0.000 282 021 2(10) =


0.0000 0000 0001 0010 0111 1011 1000 0111 1101 0100 1010 1101 1110 1001 0100 1000(2)

6. Positive number before normalization:

0.000 282 021 2(10) =


0.0000 0000 0001 0010 0111 1011 1000 0111 1101 0100 1010 1101 1110 1001 0100 1000(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:


0.000 282 021 2(10) =


0.0000 0000 0001 0010 0111 1011 1000 0111 1101 0100 1010 1101 1110 1001 0100 1000(2) =


0.0000 0000 0001 0010 0111 1011 1000 0111 1101 0100 1010 1101 1110 1001 0100 1000(2) × 20 =


1.0010 0111 1011 1000 0111 1101 0100 1010 1101 1110 1001 0100 1000(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 1000 0111 1101 0100 1010 1101 1110 1001 0100 1000


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 1000 0111 1101 0100 1010 1101 1110 1001 0100 1000 =


0010 0111 1011 1000 0111 1101 0100 1010 1101 1110 1001 0100 1000


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 1000 0111 1101 0100 1010 1101 1110 1001 0100 1000


Decimal number -0.000 282 021 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 1000 0111 1101 0100 1010 1101 1110 1001 0100 1000


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