-0.000 281 990 8 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 281 990 8(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
-0.000 281 990 8(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:

|-0.000 281 990 8| = 0.000 281 990 8


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: 0.000 281 990 8.

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) 0.000 281 990 8 × 2 = 0 + 0.000 563 981 6;
  • 2) 0.000 563 981 6 × 2 = 0 + 0.001 127 963 2;
  • 3) 0.001 127 963 2 × 2 = 0 + 0.002 255 926 4;
  • 4) 0.002 255 926 4 × 2 = 0 + 0.004 511 852 8;
  • 5) 0.004 511 852 8 × 2 = 0 + 0.009 023 705 6;
  • 6) 0.009 023 705 6 × 2 = 0 + 0.018 047 411 2;
  • 7) 0.018 047 411 2 × 2 = 0 + 0.036 094 822 4;
  • 8) 0.036 094 822 4 × 2 = 0 + 0.072 189 644 8;
  • 9) 0.072 189 644 8 × 2 = 0 + 0.144 379 289 6;
  • 10) 0.144 379 289 6 × 2 = 0 + 0.288 758 579 2;
  • 11) 0.288 758 579 2 × 2 = 0 + 0.577 517 158 4;
  • 12) 0.577 517 158 4 × 2 = 1 + 0.155 034 316 8;
  • 13) 0.155 034 316 8 × 2 = 0 + 0.310 068 633 6;
  • 14) 0.310 068 633 6 × 2 = 0 + 0.620 137 267 2;
  • 15) 0.620 137 267 2 × 2 = 1 + 0.240 274 534 4;
  • 16) 0.240 274 534 4 × 2 = 0 + 0.480 549 068 8;
  • 17) 0.480 549 068 8 × 2 = 0 + 0.961 098 137 6;
  • 18) 0.961 098 137 6 × 2 = 1 + 0.922 196 275 2;
  • 19) 0.922 196 275 2 × 2 = 1 + 0.844 392 550 4;
  • 20) 0.844 392 550 4 × 2 = 1 + 0.688 785 100 8;
  • 21) 0.688 785 100 8 × 2 = 1 + 0.377 570 201 6;
  • 22) 0.377 570 201 6 × 2 = 0 + 0.755 140 403 2;
  • 23) 0.755 140 403 2 × 2 = 1 + 0.510 280 806 4;
  • 24) 0.510 280 806 4 × 2 = 1 + 0.020 561 612 8;
  • 25) 0.020 561 612 8 × 2 = 0 + 0.041 123 225 6;
  • 26) 0.041 123 225 6 × 2 = 0 + 0.082 246 451 2;
  • 27) 0.082 246 451 2 × 2 = 0 + 0.164 492 902 4;
  • 28) 0.164 492 902 4 × 2 = 0 + 0.328 985 804 8;
  • 29) 0.328 985 804 8 × 2 = 0 + 0.657 971 609 6;
  • 30) 0.657 971 609 6 × 2 = 1 + 0.315 943 219 2;
  • 31) 0.315 943 219 2 × 2 = 0 + 0.631 886 438 4;
  • 32) 0.631 886 438 4 × 2 = 1 + 0.263 772 876 8;
  • 33) 0.263 772 876 8 × 2 = 0 + 0.527 545 753 6;
  • 34) 0.527 545 753 6 × 2 = 1 + 0.055 091 507 2;
  • 35) 0.055 091 507 2 × 2 = 0 + 0.110 183 014 4;
  • 36) 0.110 183 014 4 × 2 = 0 + 0.220 366 028 8;
  • 37) 0.220 366 028 8 × 2 = 0 + 0.440 732 057 6;
  • 38) 0.440 732 057 6 × 2 = 0 + 0.881 464 115 2;
  • 39) 0.881 464 115 2 × 2 = 1 + 0.762 928 230 4;
  • 40) 0.762 928 230 4 × 2 = 1 + 0.525 856 460 8;
  • 41) 0.525 856 460 8 × 2 = 1 + 0.051 712 921 6;
  • 42) 0.051 712 921 6 × 2 = 0 + 0.103 425 843 2;
  • 43) 0.103 425 843 2 × 2 = 0 + 0.206 851 686 4;
  • 44) 0.206 851 686 4 × 2 = 0 + 0.413 703 372 8;
  • 45) 0.413 703 372 8 × 2 = 0 + 0.827 406 745 6;
  • 46) 0.827 406 745 6 × 2 = 1 + 0.654 813 491 2;
  • 47) 0.654 813 491 2 × 2 = 1 + 0.309 626 982 4;
  • 48) 0.309 626 982 4 × 2 = 0 + 0.619 253 964 8;
  • 49) 0.619 253 964 8 × 2 = 1 + 0.238 507 929 6;
  • 50) 0.238 507 929 6 × 2 = 0 + 0.477 015 859 2;
  • 51) 0.477 015 859 2 × 2 = 0 + 0.954 031 718 4;
  • 52) 0.954 031 718 4 × 2 = 1 + 0.908 063 436 8;
  • 53) 0.908 063 436 8 × 2 = 1 + 0.816 126 873 6;
  • 54) 0.816 126 873 6 × 2 = 1 + 0.632 253 747 2;
  • 55) 0.632 253 747 2 × 2 = 1 + 0.264 507 494 4;
  • 56) 0.264 507 494 4 × 2 = 0 + 0.529 014 988 8;
  • 57) 0.529 014 988 8 × 2 = 1 + 0.058 029 977 6;
  • 58) 0.058 029 977 6 × 2 = 0 + 0.116 059 955 2;
  • 59) 0.116 059 955 2 × 2 = 0 + 0.232 119 910 4;
  • 60) 0.232 119 910 4 × 2 = 0 + 0.464 239 820 8;
  • 61) 0.464 239 820 8 × 2 = 0 + 0.928 479 641 6;
  • 62) 0.928 479 641 6 × 2 = 1 + 0.856 959 283 2;
  • 63) 0.856 959 283 2 × 2 = 1 + 0.713 918 566 4;
  • 64) 0.713 918 566 4 × 2 = 1 + 0.427 837 132 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:


0.000 281 990 8(10) =


0.0000 0000 0001 0010 0111 1011 0000 0101 0100 0011 1000 0110 1001 1110 1000 0111(2)

6. Positive number before normalization:

0.000 281 990 8(10) =


0.0000 0000 0001 0010 0111 1011 0000 0101 0100 0011 1000 0110 1001 1110 1000 0111(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:


0.000 281 990 8(10) =


0.0000 0000 0001 0010 0111 1011 0000 0101 0100 0011 1000 0110 1001 1110 1000 0111(2) =


0.0000 0000 0001 0010 0111 1011 0000 0101 0100 0011 1000 0110 1001 1110 1000 0111(2) × 20 =


1.0010 0111 1011 0000 0101 0100 0011 1000 0110 1001 1110 1000 0111(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 0000 0101 0100 0011 1000 0110 1001 1110 1000 0111


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 0000 0101 0100 0011 1000 0110 1001 1110 1000 0111 =


0010 0111 1011 0000 0101 0100 0011 1000 0110 1001 1110 1000 0111


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 0000 0101 0100 0011 1000 0110 1001 1110 1000 0111


Decimal number -0.000 281 990 8 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0000 0101 0100 0011 1000 0110 1001 1110 1000 0111


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