-0.000 281 984 4 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 281 984 4(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
-0.000 281 984 4(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:

|-0.000 281 984 4| = 0.000 281 984 4


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: 0.000 281 984 4.

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) 0.000 281 984 4 × 2 = 0 + 0.000 563 968 8;
  • 2) 0.000 563 968 8 × 2 = 0 + 0.001 127 937 6;
  • 3) 0.001 127 937 6 × 2 = 0 + 0.002 255 875 2;
  • 4) 0.002 255 875 2 × 2 = 0 + 0.004 511 750 4;
  • 5) 0.004 511 750 4 × 2 = 0 + 0.009 023 500 8;
  • 6) 0.009 023 500 8 × 2 = 0 + 0.018 047 001 6;
  • 7) 0.018 047 001 6 × 2 = 0 + 0.036 094 003 2;
  • 8) 0.036 094 003 2 × 2 = 0 + 0.072 188 006 4;
  • 9) 0.072 188 006 4 × 2 = 0 + 0.144 376 012 8;
  • 10) 0.144 376 012 8 × 2 = 0 + 0.288 752 025 6;
  • 11) 0.288 752 025 6 × 2 = 0 + 0.577 504 051 2;
  • 12) 0.577 504 051 2 × 2 = 1 + 0.155 008 102 4;
  • 13) 0.155 008 102 4 × 2 = 0 + 0.310 016 204 8;
  • 14) 0.310 016 204 8 × 2 = 0 + 0.620 032 409 6;
  • 15) 0.620 032 409 6 × 2 = 1 + 0.240 064 819 2;
  • 16) 0.240 064 819 2 × 2 = 0 + 0.480 129 638 4;
  • 17) 0.480 129 638 4 × 2 = 0 + 0.960 259 276 8;
  • 18) 0.960 259 276 8 × 2 = 1 + 0.920 518 553 6;
  • 19) 0.920 518 553 6 × 2 = 1 + 0.841 037 107 2;
  • 20) 0.841 037 107 2 × 2 = 1 + 0.682 074 214 4;
  • 21) 0.682 074 214 4 × 2 = 1 + 0.364 148 428 8;
  • 22) 0.364 148 428 8 × 2 = 0 + 0.728 296 857 6;
  • 23) 0.728 296 857 6 × 2 = 1 + 0.456 593 715 2;
  • 24) 0.456 593 715 2 × 2 = 0 + 0.913 187 430 4;
  • 25) 0.913 187 430 4 × 2 = 1 + 0.826 374 860 8;
  • 26) 0.826 374 860 8 × 2 = 1 + 0.652 749 721 6;
  • 27) 0.652 749 721 6 × 2 = 1 + 0.305 499 443 2;
  • 28) 0.305 499 443 2 × 2 = 0 + 0.610 998 886 4;
  • 29) 0.610 998 886 4 × 2 = 1 + 0.221 997 772 8;
  • 30) 0.221 997 772 8 × 2 = 0 + 0.443 995 545 6;
  • 31) 0.443 995 545 6 × 2 = 0 + 0.887 991 091 2;
  • 32) 0.887 991 091 2 × 2 = 1 + 0.775 982 182 4;
  • 33) 0.775 982 182 4 × 2 = 1 + 0.551 964 364 8;
  • 34) 0.551 964 364 8 × 2 = 1 + 0.103 928 729 6;
  • 35) 0.103 928 729 6 × 2 = 0 + 0.207 857 459 2;
  • 36) 0.207 857 459 2 × 2 = 0 + 0.415 714 918 4;
  • 37) 0.415 714 918 4 × 2 = 0 + 0.831 429 836 8;
  • 38) 0.831 429 836 8 × 2 = 1 + 0.662 859 673 6;
  • 39) 0.662 859 673 6 × 2 = 1 + 0.325 719 347 2;
  • 40) 0.325 719 347 2 × 2 = 0 + 0.651 438 694 4;
  • 41) 0.651 438 694 4 × 2 = 1 + 0.302 877 388 8;
  • 42) 0.302 877 388 8 × 2 = 0 + 0.605 754 777 6;
  • 43) 0.605 754 777 6 × 2 = 1 + 0.211 509 555 2;
  • 44) 0.211 509 555 2 × 2 = 0 + 0.423 019 110 4;
  • 45) 0.423 019 110 4 × 2 = 0 + 0.846 038 220 8;
  • 46) 0.846 038 220 8 × 2 = 1 + 0.692 076 441 6;
  • 47) 0.692 076 441 6 × 2 = 1 + 0.384 152 883 2;
  • 48) 0.384 152 883 2 × 2 = 0 + 0.768 305 766 4;
  • 49) 0.768 305 766 4 × 2 = 1 + 0.536 611 532 8;
  • 50) 0.536 611 532 8 × 2 = 1 + 0.073 223 065 6;
  • 51) 0.073 223 065 6 × 2 = 0 + 0.146 446 131 2;
  • 52) 0.146 446 131 2 × 2 = 0 + 0.292 892 262 4;
  • 53) 0.292 892 262 4 × 2 = 0 + 0.585 784 524 8;
  • 54) 0.585 784 524 8 × 2 = 1 + 0.171 569 049 6;
  • 55) 0.171 569 049 6 × 2 = 0 + 0.343 138 099 2;
  • 56) 0.343 138 099 2 × 2 = 0 + 0.686 276 198 4;
  • 57) 0.686 276 198 4 × 2 = 1 + 0.372 552 396 8;
  • 58) 0.372 552 396 8 × 2 = 0 + 0.745 104 793 6;
  • 59) 0.745 104 793 6 × 2 = 1 + 0.490 209 587 2;
  • 60) 0.490 209 587 2 × 2 = 0 + 0.980 419 174 4;
  • 61) 0.980 419 174 4 × 2 = 1 + 0.960 838 348 8;
  • 62) 0.960 838 348 8 × 2 = 1 + 0.921 676 697 6;
  • 63) 0.921 676 697 6 × 2 = 1 + 0.843 353 395 2;
  • 64) 0.843 353 395 2 × 2 = 1 + 0.686 706 790 4;

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:


0.000 281 984 4(10) =


0.0000 0000 0001 0010 0111 1010 1110 1001 1100 0110 1010 0110 1100 0100 1010 1111(2)

6. Positive number before normalization:

0.000 281 984 4(10) =


0.0000 0000 0001 0010 0111 1010 1110 1001 1100 0110 1010 0110 1100 0100 1010 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:


0.000 281 984 4(10) =


0.0000 0000 0001 0010 0111 1010 1110 1001 1100 0110 1010 0110 1100 0100 1010 1111(2) =


0.0000 0000 0001 0010 0111 1010 1110 1001 1100 0110 1010 0110 1100 0100 1010 1111(2) × 20 =


1.0010 0111 1010 1110 1001 1100 0110 1010 0110 1100 0100 1010 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 1010 1110 1001 1100 0110 1010 0110 1100 0100 1010 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 1010 1110 1001 1100 0110 1010 0110 1100 0100 1010 1111 =


0010 0111 1010 1110 1001 1100 0110 1010 0110 1100 0100 1010 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 1010 1110 1001 1100 0110 1010 0110 1100 0100 1010 1111


Decimal number -0.000 281 984 4 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1010 1110 1001 1100 0110 1010 0110 1100 0100 1010 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