-0.000 282 016 7 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 016 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
-0.000 282 016 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:

|-0.000 282 016 7| = 0.000 282 016 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: 0.000 282 016 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) 0.000 282 016 7 × 2 = 0 + 0.000 564 033 4;
  • 2) 0.000 564 033 4 × 2 = 0 + 0.001 128 066 8;
  • 3) 0.001 128 066 8 × 2 = 0 + 0.002 256 133 6;
  • 4) 0.002 256 133 6 × 2 = 0 + 0.004 512 267 2;
  • 5) 0.004 512 267 2 × 2 = 0 + 0.009 024 534 4;
  • 6) 0.009 024 534 4 × 2 = 0 + 0.018 049 068 8;
  • 7) 0.018 049 068 8 × 2 = 0 + 0.036 098 137 6;
  • 8) 0.036 098 137 6 × 2 = 0 + 0.072 196 275 2;
  • 9) 0.072 196 275 2 × 2 = 0 + 0.144 392 550 4;
  • 10) 0.144 392 550 4 × 2 = 0 + 0.288 785 100 8;
  • 11) 0.288 785 100 8 × 2 = 0 + 0.577 570 201 6;
  • 12) 0.577 570 201 6 × 2 = 1 + 0.155 140 403 2;
  • 13) 0.155 140 403 2 × 2 = 0 + 0.310 280 806 4;
  • 14) 0.310 280 806 4 × 2 = 0 + 0.620 561 612 8;
  • 15) 0.620 561 612 8 × 2 = 1 + 0.241 123 225 6;
  • 16) 0.241 123 225 6 × 2 = 0 + 0.482 246 451 2;
  • 17) 0.482 246 451 2 × 2 = 0 + 0.964 492 902 4;
  • 18) 0.964 492 902 4 × 2 = 1 + 0.928 985 804 8;
  • 19) 0.928 985 804 8 × 2 = 1 + 0.857 971 609 6;
  • 20) 0.857 971 609 6 × 2 = 1 + 0.715 943 219 2;
  • 21) 0.715 943 219 2 × 2 = 1 + 0.431 886 438 4;
  • 22) 0.431 886 438 4 × 2 = 0 + 0.863 772 876 8;
  • 23) 0.863 772 876 8 × 2 = 1 + 0.727 545 753 6;
  • 24) 0.727 545 753 6 × 2 = 1 + 0.455 091 507 2;
  • 25) 0.455 091 507 2 × 2 = 0 + 0.910 183 014 4;
  • 26) 0.910 183 014 4 × 2 = 1 + 0.820 366 028 8;
  • 27) 0.820 366 028 8 × 2 = 1 + 0.640 732 057 6;
  • 28) 0.640 732 057 6 × 2 = 1 + 0.281 464 115 2;
  • 29) 0.281 464 115 2 × 2 = 0 + 0.562 928 230 4;
  • 30) 0.562 928 230 4 × 2 = 1 + 0.125 856 460 8;
  • 31) 0.125 856 460 8 × 2 = 0 + 0.251 712 921 6;
  • 32) 0.251 712 921 6 × 2 = 0 + 0.503 425 843 2;
  • 33) 0.503 425 843 2 × 2 = 1 + 0.006 851 686 4;
  • 34) 0.006 851 686 4 × 2 = 0 + 0.013 703 372 8;
  • 35) 0.013 703 372 8 × 2 = 0 + 0.027 406 745 6;
  • 36) 0.027 406 745 6 × 2 = 0 + 0.054 813 491 2;
  • 37) 0.054 813 491 2 × 2 = 0 + 0.109 626 982 4;
  • 38) 0.109 626 982 4 × 2 = 0 + 0.219 253 964 8;
  • 39) 0.219 253 964 8 × 2 = 0 + 0.438 507 929 6;
  • 40) 0.438 507 929 6 × 2 = 0 + 0.877 015 859 2;
  • 41) 0.877 015 859 2 × 2 = 1 + 0.754 031 718 4;
  • 42) 0.754 031 718 4 × 2 = 1 + 0.508 063 436 8;
  • 43) 0.508 063 436 8 × 2 = 1 + 0.016 126 873 6;
  • 44) 0.016 126 873 6 × 2 = 0 + 0.032 253 747 2;
  • 45) 0.032 253 747 2 × 2 = 0 + 0.064 507 494 4;
  • 46) 0.064 507 494 4 × 2 = 0 + 0.129 014 988 8;
  • 47) 0.129 014 988 8 × 2 = 0 + 0.258 029 977 6;
  • 48) 0.258 029 977 6 × 2 = 0 + 0.516 059 955 2;
  • 49) 0.516 059 955 2 × 2 = 1 + 0.032 119 910 4;
  • 50) 0.032 119 910 4 × 2 = 0 + 0.064 239 820 8;
  • 51) 0.064 239 820 8 × 2 = 0 + 0.128 479 641 6;
  • 52) 0.128 479 641 6 × 2 = 0 + 0.256 959 283 2;
  • 53) 0.256 959 283 2 × 2 = 0 + 0.513 918 566 4;
  • 54) 0.513 918 566 4 × 2 = 1 + 0.027 837 132 8;
  • 55) 0.027 837 132 8 × 2 = 0 + 0.055 674 265 6;
  • 56) 0.055 674 265 6 × 2 = 0 + 0.111 348 531 2;
  • 57) 0.111 348 531 2 × 2 = 0 + 0.222 697 062 4;
  • 58) 0.222 697 062 4 × 2 = 0 + 0.445 394 124 8;
  • 59) 0.445 394 124 8 × 2 = 0 + 0.890 788 249 6;
  • 60) 0.890 788 249 6 × 2 = 1 + 0.781 576 499 2;
  • 61) 0.781 576 499 2 × 2 = 1 + 0.563 152 998 4;
  • 62) 0.563 152 998 4 × 2 = 1 + 0.126 305 996 8;
  • 63) 0.126 305 996 8 × 2 = 0 + 0.252 611 993 6;
  • 64) 0.252 611 993 6 × 2 = 0 + 0.505 223 987 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:


0.000 282 016 7(10) =


0.0000 0000 0001 0010 0111 1011 0111 0100 1000 0000 1110 0000 1000 0100 0001 1100(2)

6. Positive number before normalization:

0.000 282 016 7(10) =


0.0000 0000 0001 0010 0111 1011 0111 0100 1000 0000 1110 0000 1000 0100 0001 1100(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:


0.000 282 016 7(10) =


0.0000 0000 0001 0010 0111 1011 0111 0100 1000 0000 1110 0000 1000 0100 0001 1100(2) =


0.0000 0000 0001 0010 0111 1011 0111 0100 1000 0000 1110 0000 1000 0100 0001 1100(2) × 20 =


1.0010 0111 1011 0111 0100 1000 0000 1110 0000 1000 0100 0001 1100(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 0111 0100 1000 0000 1110 0000 1000 0100 0001 1100


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 0111 0100 1000 0000 1110 0000 1000 0100 0001 1100 =


0010 0111 1011 0111 0100 1000 0000 1110 0000 1000 0100 0001 1100


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 0111 0100 1000 0000 1110 0000 1000 0100 0001 1100


Decimal number -0.000 282 016 7 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0111 0100 1000 0000 1110 0000 1000 0100 0001 1100


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