-0.000 282 010 45 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 010 45(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
-0.000 282 010 45(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:

|-0.000 282 010 45| = 0.000 282 010 45


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: 0.000 282 010 45.

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) 0.000 282 010 45 × 2 = 0 + 0.000 564 020 9;
  • 2) 0.000 564 020 9 × 2 = 0 + 0.001 128 041 8;
  • 3) 0.001 128 041 8 × 2 = 0 + 0.002 256 083 6;
  • 4) 0.002 256 083 6 × 2 = 0 + 0.004 512 167 2;
  • 5) 0.004 512 167 2 × 2 = 0 + 0.009 024 334 4;
  • 6) 0.009 024 334 4 × 2 = 0 + 0.018 048 668 8;
  • 7) 0.018 048 668 8 × 2 = 0 + 0.036 097 337 6;
  • 8) 0.036 097 337 6 × 2 = 0 + 0.072 194 675 2;
  • 9) 0.072 194 675 2 × 2 = 0 + 0.144 389 350 4;
  • 10) 0.144 389 350 4 × 2 = 0 + 0.288 778 700 8;
  • 11) 0.288 778 700 8 × 2 = 0 + 0.577 557 401 6;
  • 12) 0.577 557 401 6 × 2 = 1 + 0.155 114 803 2;
  • 13) 0.155 114 803 2 × 2 = 0 + 0.310 229 606 4;
  • 14) 0.310 229 606 4 × 2 = 0 + 0.620 459 212 8;
  • 15) 0.620 459 212 8 × 2 = 1 + 0.240 918 425 6;
  • 16) 0.240 918 425 6 × 2 = 0 + 0.481 836 851 2;
  • 17) 0.481 836 851 2 × 2 = 0 + 0.963 673 702 4;
  • 18) 0.963 673 702 4 × 2 = 1 + 0.927 347 404 8;
  • 19) 0.927 347 404 8 × 2 = 1 + 0.854 694 809 6;
  • 20) 0.854 694 809 6 × 2 = 1 + 0.709 389 619 2;
  • 21) 0.709 389 619 2 × 2 = 1 + 0.418 779 238 4;
  • 22) 0.418 779 238 4 × 2 = 0 + 0.837 558 476 8;
  • 23) 0.837 558 476 8 × 2 = 1 + 0.675 116 953 6;
  • 24) 0.675 116 953 6 × 2 = 1 + 0.350 233 907 2;
  • 25) 0.350 233 907 2 × 2 = 0 + 0.700 467 814 4;
  • 26) 0.700 467 814 4 × 2 = 1 + 0.400 935 628 8;
  • 27) 0.400 935 628 8 × 2 = 0 + 0.801 871 257 6;
  • 28) 0.801 871 257 6 × 2 = 1 + 0.603 742 515 2;
  • 29) 0.603 742 515 2 × 2 = 1 + 0.207 485 030 4;
  • 30) 0.207 485 030 4 × 2 = 0 + 0.414 970 060 8;
  • 31) 0.414 970 060 8 × 2 = 0 + 0.829 940 121 6;
  • 32) 0.829 940 121 6 × 2 = 1 + 0.659 880 243 2;
  • 33) 0.659 880 243 2 × 2 = 1 + 0.319 760 486 4;
  • 34) 0.319 760 486 4 × 2 = 0 + 0.639 520 972 8;
  • 35) 0.639 520 972 8 × 2 = 1 + 0.279 041 945 6;
  • 36) 0.279 041 945 6 × 2 = 0 + 0.558 083 891 2;
  • 37) 0.558 083 891 2 × 2 = 1 + 0.116 167 782 4;
  • 38) 0.116 167 782 4 × 2 = 0 + 0.232 335 564 8;
  • 39) 0.232 335 564 8 × 2 = 0 + 0.464 671 129 6;
  • 40) 0.464 671 129 6 × 2 = 0 + 0.929 342 259 2;
  • 41) 0.929 342 259 2 × 2 = 1 + 0.858 684 518 4;
  • 42) 0.858 684 518 4 × 2 = 1 + 0.717 369 036 8;
  • 43) 0.717 369 036 8 × 2 = 1 + 0.434 738 073 6;
  • 44) 0.434 738 073 6 × 2 = 0 + 0.869 476 147 2;
  • 45) 0.869 476 147 2 × 2 = 1 + 0.738 952 294 4;
  • 46) 0.738 952 294 4 × 2 = 1 + 0.477 904 588 8;
  • 47) 0.477 904 588 8 × 2 = 0 + 0.955 809 177 6;
  • 48) 0.955 809 177 6 × 2 = 1 + 0.911 618 355 2;
  • 49) 0.911 618 355 2 × 2 = 1 + 0.823 236 710 4;
  • 50) 0.823 236 710 4 × 2 = 1 + 0.646 473 420 8;
  • 51) 0.646 473 420 8 × 2 = 1 + 0.292 946 841 6;
  • 52) 0.292 946 841 6 × 2 = 0 + 0.585 893 683 2;
  • 53) 0.585 893 683 2 × 2 = 1 + 0.171 787 366 4;
  • 54) 0.171 787 366 4 × 2 = 0 + 0.343 574 732 8;
  • 55) 0.343 574 732 8 × 2 = 0 + 0.687 149 465 6;
  • 56) 0.687 149 465 6 × 2 = 1 + 0.374 298 931 2;
  • 57) 0.374 298 931 2 × 2 = 0 + 0.748 597 862 4;
  • 58) 0.748 597 862 4 × 2 = 1 + 0.497 195 724 8;
  • 59) 0.497 195 724 8 × 2 = 0 + 0.994 391 449 6;
  • 60) 0.994 391 449 6 × 2 = 1 + 0.988 782 899 2;
  • 61) 0.988 782 899 2 × 2 = 1 + 0.977 565 798 4;
  • 62) 0.977 565 798 4 × 2 = 1 + 0.955 131 596 8;
  • 63) 0.955 131 596 8 × 2 = 1 + 0.910 263 193 6;
  • 64) 0.910 263 193 6 × 2 = 1 + 0.820 526 387 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:


0.000 282 010 45(10) =


0.0000 0000 0001 0010 0111 1011 0101 1001 1010 1000 1110 1101 1110 1001 0101 1111(2)

6. Positive number before normalization:

0.000 282 010 45(10) =


0.0000 0000 0001 0010 0111 1011 0101 1001 1010 1000 1110 1101 1110 1001 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:


0.000 282 010 45(10) =


0.0000 0000 0001 0010 0111 1011 0101 1001 1010 1000 1110 1101 1110 1001 0101 1111(2) =


0.0000 0000 0001 0010 0111 1011 0101 1001 1010 1000 1110 1101 1110 1001 0101 1111(2) × 20 =


1.0010 0111 1011 0101 1001 1010 1000 1110 1101 1110 1001 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 0101 1001 1010 1000 1110 1101 1110 1001 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 0101 1001 1010 1000 1110 1101 1110 1001 0101 1111 =


0010 0111 1011 0101 1001 1010 1000 1110 1101 1110 1001 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 0101 1001 1010 1000 1110 1101 1110 1001 0101 1111


Decimal number -0.000 282 010 45 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0101 1001 1010 1000 1110 1101 1110 1001 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