-0.000 282 020 3 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 020 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
-0.000 282 020 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:

|-0.000 282 020 3| = 0.000 282 020 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: 0.000 282 020 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) 0.000 282 020 3 × 2 = 0 + 0.000 564 040 6;
  • 2) 0.000 564 040 6 × 2 = 0 + 0.001 128 081 2;
  • 3) 0.001 128 081 2 × 2 = 0 + 0.002 256 162 4;
  • 4) 0.002 256 162 4 × 2 = 0 + 0.004 512 324 8;
  • 5) 0.004 512 324 8 × 2 = 0 + 0.009 024 649 6;
  • 6) 0.009 024 649 6 × 2 = 0 + 0.018 049 299 2;
  • 7) 0.018 049 299 2 × 2 = 0 + 0.036 098 598 4;
  • 8) 0.036 098 598 4 × 2 = 0 + 0.072 197 196 8;
  • 9) 0.072 197 196 8 × 2 = 0 + 0.144 394 393 6;
  • 10) 0.144 394 393 6 × 2 = 0 + 0.288 788 787 2;
  • 11) 0.288 788 787 2 × 2 = 0 + 0.577 577 574 4;
  • 12) 0.577 577 574 4 × 2 = 1 + 0.155 155 148 8;
  • 13) 0.155 155 148 8 × 2 = 0 + 0.310 310 297 6;
  • 14) 0.310 310 297 6 × 2 = 0 + 0.620 620 595 2;
  • 15) 0.620 620 595 2 × 2 = 1 + 0.241 241 190 4;
  • 16) 0.241 241 190 4 × 2 = 0 + 0.482 482 380 8;
  • 17) 0.482 482 380 8 × 2 = 0 + 0.964 964 761 6;
  • 18) 0.964 964 761 6 × 2 = 1 + 0.929 929 523 2;
  • 19) 0.929 929 523 2 × 2 = 1 + 0.859 859 046 4;
  • 20) 0.859 859 046 4 × 2 = 1 + 0.719 718 092 8;
  • 21) 0.719 718 092 8 × 2 = 1 + 0.439 436 185 6;
  • 22) 0.439 436 185 6 × 2 = 0 + 0.878 872 371 2;
  • 23) 0.878 872 371 2 × 2 = 1 + 0.757 744 742 4;
  • 24) 0.757 744 742 4 × 2 = 1 + 0.515 489 484 8;
  • 25) 0.515 489 484 8 × 2 = 1 + 0.030 978 969 6;
  • 26) 0.030 978 969 6 × 2 = 0 + 0.061 957 939 2;
  • 27) 0.061 957 939 2 × 2 = 0 + 0.123 915 878 4;
  • 28) 0.123 915 878 4 × 2 = 0 + 0.247 831 756 8;
  • 29) 0.247 831 756 8 × 2 = 0 + 0.495 663 513 6;
  • 30) 0.495 663 513 6 × 2 = 0 + 0.991 327 027 2;
  • 31) 0.991 327 027 2 × 2 = 1 + 0.982 654 054 4;
  • 32) 0.982 654 054 4 × 2 = 1 + 0.965 308 108 8;
  • 33) 0.965 308 108 8 × 2 = 1 + 0.930 616 217 6;
  • 34) 0.930 616 217 6 × 2 = 1 + 0.861 232 435 2;
  • 35) 0.861 232 435 2 × 2 = 1 + 0.722 464 870 4;
  • 36) 0.722 464 870 4 × 2 = 1 + 0.444 929 740 8;
  • 37) 0.444 929 740 8 × 2 = 0 + 0.889 859 481 6;
  • 38) 0.889 859 481 6 × 2 = 1 + 0.779 718 963 2;
  • 39) 0.779 718 963 2 × 2 = 1 + 0.559 437 926 4;
  • 40) 0.559 437 926 4 × 2 = 1 + 0.118 875 852 8;
  • 41) 0.118 875 852 8 × 2 = 0 + 0.237 751 705 6;
  • 42) 0.237 751 705 6 × 2 = 0 + 0.475 503 411 2;
  • 43) 0.475 503 411 2 × 2 = 0 + 0.951 006 822 4;
  • 44) 0.951 006 822 4 × 2 = 1 + 0.902 013 644 8;
  • 45) 0.902 013 644 8 × 2 = 1 + 0.804 027 289 6;
  • 46) 0.804 027 289 6 × 2 = 1 + 0.608 054 579 2;
  • 47) 0.608 054 579 2 × 2 = 1 + 0.216 109 158 4;
  • 48) 0.216 109 158 4 × 2 = 0 + 0.432 218 316 8;
  • 49) 0.432 218 316 8 × 2 = 0 + 0.864 436 633 6;
  • 50) 0.864 436 633 6 × 2 = 1 + 0.728 873 267 2;
  • 51) 0.728 873 267 2 × 2 = 1 + 0.457 746 534 4;
  • 52) 0.457 746 534 4 × 2 = 0 + 0.915 493 068 8;
  • 53) 0.915 493 068 8 × 2 = 1 + 0.830 986 137 6;
  • 54) 0.830 986 137 6 × 2 = 1 + 0.661 972 275 2;
  • 55) 0.661 972 275 2 × 2 = 1 + 0.323 944 550 4;
  • 56) 0.323 944 550 4 × 2 = 0 + 0.647 889 100 8;
  • 57) 0.647 889 100 8 × 2 = 1 + 0.295 778 201 6;
  • 58) 0.295 778 201 6 × 2 = 0 + 0.591 556 403 2;
  • 59) 0.591 556 403 2 × 2 = 1 + 0.183 112 806 4;
  • 60) 0.183 112 806 4 × 2 = 0 + 0.366 225 612 8;
  • 61) 0.366 225 612 8 × 2 = 0 + 0.732 451 225 6;
  • 62) 0.732 451 225 6 × 2 = 1 + 0.464 902 451 2;
  • 63) 0.464 902 451 2 × 2 = 0 + 0.929 804 902 4;
  • 64) 0.929 804 902 4 × 2 = 1 + 0.859 609 804 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:


0.000 282 020 3(10) =


0.0000 0000 0001 0010 0111 1011 1000 0011 1111 0111 0001 1110 0110 1110 1010 0101(2)

6. Positive number before normalization:

0.000 282 020 3(10) =


0.0000 0000 0001 0010 0111 1011 1000 0011 1111 0111 0001 1110 0110 1110 1010 0101(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:


0.000 282 020 3(10) =


0.0000 0000 0001 0010 0111 1011 1000 0011 1111 0111 0001 1110 0110 1110 1010 0101(2) =


0.0000 0000 0001 0010 0111 1011 1000 0011 1111 0111 0001 1110 0110 1110 1010 0101(2) × 20 =


1.0010 0111 1011 1000 0011 1111 0111 0001 1110 0110 1110 1010 0101(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 1000 0011 1111 0111 0001 1110 0110 1110 1010 0101


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 1000 0011 1111 0111 0001 1110 0110 1110 1010 0101 =


0010 0111 1011 1000 0011 1111 0111 0001 1110 0110 1110 1010 0101


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 1000 0011 1111 0111 0001 1110 0110 1110 1010 0101


Decimal number -0.000 282 020 3 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 1000 0011 1111 0111 0001 1110 0110 1110 1010 0101


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