-0.000 282 028 3 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 028 3(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
-0.000 282 028 3(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:

|-0.000 282 028 3| = 0.000 282 028 3


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: 0.000 282 028 3.

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) 0.000 282 028 3 × 2 = 0 + 0.000 564 056 6;
  • 2) 0.000 564 056 6 × 2 = 0 + 0.001 128 113 2;
  • 3) 0.001 128 113 2 × 2 = 0 + 0.002 256 226 4;
  • 4) 0.002 256 226 4 × 2 = 0 + 0.004 512 452 8;
  • 5) 0.004 512 452 8 × 2 = 0 + 0.009 024 905 6;
  • 6) 0.009 024 905 6 × 2 = 0 + 0.018 049 811 2;
  • 7) 0.018 049 811 2 × 2 = 0 + 0.036 099 622 4;
  • 8) 0.036 099 622 4 × 2 = 0 + 0.072 199 244 8;
  • 9) 0.072 199 244 8 × 2 = 0 + 0.144 398 489 6;
  • 10) 0.144 398 489 6 × 2 = 0 + 0.288 796 979 2;
  • 11) 0.288 796 979 2 × 2 = 0 + 0.577 593 958 4;
  • 12) 0.577 593 958 4 × 2 = 1 + 0.155 187 916 8;
  • 13) 0.155 187 916 8 × 2 = 0 + 0.310 375 833 6;
  • 14) 0.310 375 833 6 × 2 = 0 + 0.620 751 667 2;
  • 15) 0.620 751 667 2 × 2 = 1 + 0.241 503 334 4;
  • 16) 0.241 503 334 4 × 2 = 0 + 0.483 006 668 8;
  • 17) 0.483 006 668 8 × 2 = 0 + 0.966 013 337 6;
  • 18) 0.966 013 337 6 × 2 = 1 + 0.932 026 675 2;
  • 19) 0.932 026 675 2 × 2 = 1 + 0.864 053 350 4;
  • 20) 0.864 053 350 4 × 2 = 1 + 0.728 106 700 8;
  • 21) 0.728 106 700 8 × 2 = 1 + 0.456 213 401 6;
  • 22) 0.456 213 401 6 × 2 = 0 + 0.912 426 803 2;
  • 23) 0.912 426 803 2 × 2 = 1 + 0.824 853 606 4;
  • 24) 0.824 853 606 4 × 2 = 1 + 0.649 707 212 8;
  • 25) 0.649 707 212 8 × 2 = 1 + 0.299 414 425 6;
  • 26) 0.299 414 425 6 × 2 = 0 + 0.598 828 851 2;
  • 27) 0.598 828 851 2 × 2 = 1 + 0.197 657 702 4;
  • 28) 0.197 657 702 4 × 2 = 0 + 0.395 315 404 8;
  • 29) 0.395 315 404 8 × 2 = 0 + 0.790 630 809 6;
  • 30) 0.790 630 809 6 × 2 = 1 + 0.581 261 619 2;
  • 31) 0.581 261 619 2 × 2 = 1 + 0.162 523 238 4;
  • 32) 0.162 523 238 4 × 2 = 0 + 0.325 046 476 8;
  • 33) 0.325 046 476 8 × 2 = 0 + 0.650 092 953 6;
  • 34) 0.650 092 953 6 × 2 = 1 + 0.300 185 907 2;
  • 35) 0.300 185 907 2 × 2 = 0 + 0.600 371 814 4;
  • 36) 0.600 371 814 4 × 2 = 1 + 0.200 743 628 8;
  • 37) 0.200 743 628 8 × 2 = 0 + 0.401 487 257 6;
  • 38) 0.401 487 257 6 × 2 = 0 + 0.802 974 515 2;
  • 39) 0.802 974 515 2 × 2 = 1 + 0.605 949 030 4;
  • 40) 0.605 949 030 4 × 2 = 1 + 0.211 898 060 8;
  • 41) 0.211 898 060 8 × 2 = 0 + 0.423 796 121 6;
  • 42) 0.423 796 121 6 × 2 = 0 + 0.847 592 243 2;
  • 43) 0.847 592 243 2 × 2 = 1 + 0.695 184 486 4;
  • 44) 0.695 184 486 4 × 2 = 1 + 0.390 368 972 8;
  • 45) 0.390 368 972 8 × 2 = 0 + 0.780 737 945 6;
  • 46) 0.780 737 945 6 × 2 = 1 + 0.561 475 891 2;
  • 47) 0.561 475 891 2 × 2 = 1 + 0.122 951 782 4;
  • 48) 0.122 951 782 4 × 2 = 0 + 0.245 903 564 8;
  • 49) 0.245 903 564 8 × 2 = 0 + 0.491 807 129 6;
  • 50) 0.491 807 129 6 × 2 = 0 + 0.983 614 259 2;
  • 51) 0.983 614 259 2 × 2 = 1 + 0.967 228 518 4;
  • 52) 0.967 228 518 4 × 2 = 1 + 0.934 457 036 8;
  • 53) 0.934 457 036 8 × 2 = 1 + 0.868 914 073 6;
  • 54) 0.868 914 073 6 × 2 = 1 + 0.737 828 147 2;
  • 55) 0.737 828 147 2 × 2 = 1 + 0.475 656 294 4;
  • 56) 0.475 656 294 4 × 2 = 0 + 0.951 312 588 8;
  • 57) 0.951 312 588 8 × 2 = 1 + 0.902 625 177 6;
  • 58) 0.902 625 177 6 × 2 = 1 + 0.805 250 355 2;
  • 59) 0.805 250 355 2 × 2 = 1 + 0.610 500 710 4;
  • 60) 0.610 500 710 4 × 2 = 1 + 0.221 001 420 8;
  • 61) 0.221 001 420 8 × 2 = 0 + 0.442 002 841 6;
  • 62) 0.442 002 841 6 × 2 = 0 + 0.884 005 683 2;
  • 63) 0.884 005 683 2 × 2 = 1 + 0.768 011 366 4;
  • 64) 0.768 011 366 4 × 2 = 1 + 0.536 022 732 8;

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:


0.000 282 028 3(10) =


0.0000 0000 0001 0010 0111 1011 1010 0110 0101 0011 0011 0110 0011 1110 1111 0011(2)

6. Positive number before normalization:

0.000 282 028 3(10) =


0.0000 0000 0001 0010 0111 1011 1010 0110 0101 0011 0011 0110 0011 1110 1111 0011(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:


0.000 282 028 3(10) =


0.0000 0000 0001 0010 0111 1011 1010 0110 0101 0011 0011 0110 0011 1110 1111 0011(2) =


0.0000 0000 0001 0010 0111 1011 1010 0110 0101 0011 0011 0110 0011 1110 1111 0011(2) × 20 =


1.0010 0111 1011 1010 0110 0101 0011 0011 0110 0011 1110 1111 0011(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 1010 0110 0101 0011 0011 0110 0011 1110 1111 0011


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 1010 0110 0101 0011 0011 0110 0011 1110 1111 0011 =


0010 0111 1011 1010 0110 0101 0011 0011 0110 0011 1110 1111 0011


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 1010 0110 0101 0011 0011 0110 0011 1110 1111 0011


Decimal number -0.000 282 028 3 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 1010 0110 0101 0011 0011 0110 0011 1110 1111 0011


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