-0.000 282 047 1 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 047 1(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
-0.000 282 047 1(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:

|-0.000 282 047 1| = 0.000 282 047 1


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: 0.000 282 047 1.

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) 0.000 282 047 1 × 2 = 0 + 0.000 564 094 2;
  • 2) 0.000 564 094 2 × 2 = 0 + 0.001 128 188 4;
  • 3) 0.001 128 188 4 × 2 = 0 + 0.002 256 376 8;
  • 4) 0.002 256 376 8 × 2 = 0 + 0.004 512 753 6;
  • 5) 0.004 512 753 6 × 2 = 0 + 0.009 025 507 2;
  • 6) 0.009 025 507 2 × 2 = 0 + 0.018 051 014 4;
  • 7) 0.018 051 014 4 × 2 = 0 + 0.036 102 028 8;
  • 8) 0.036 102 028 8 × 2 = 0 + 0.072 204 057 6;
  • 9) 0.072 204 057 6 × 2 = 0 + 0.144 408 115 2;
  • 10) 0.144 408 115 2 × 2 = 0 + 0.288 816 230 4;
  • 11) 0.288 816 230 4 × 2 = 0 + 0.577 632 460 8;
  • 12) 0.577 632 460 8 × 2 = 1 + 0.155 264 921 6;
  • 13) 0.155 264 921 6 × 2 = 0 + 0.310 529 843 2;
  • 14) 0.310 529 843 2 × 2 = 0 + 0.621 059 686 4;
  • 15) 0.621 059 686 4 × 2 = 1 + 0.242 119 372 8;
  • 16) 0.242 119 372 8 × 2 = 0 + 0.484 238 745 6;
  • 17) 0.484 238 745 6 × 2 = 0 + 0.968 477 491 2;
  • 18) 0.968 477 491 2 × 2 = 1 + 0.936 954 982 4;
  • 19) 0.936 954 982 4 × 2 = 1 + 0.873 909 964 8;
  • 20) 0.873 909 964 8 × 2 = 1 + 0.747 819 929 6;
  • 21) 0.747 819 929 6 × 2 = 1 + 0.495 639 859 2;
  • 22) 0.495 639 859 2 × 2 = 0 + 0.991 279 718 4;
  • 23) 0.991 279 718 4 × 2 = 1 + 0.982 559 436 8;
  • 24) 0.982 559 436 8 × 2 = 1 + 0.965 118 873 6;
  • 25) 0.965 118 873 6 × 2 = 1 + 0.930 237 747 2;
  • 26) 0.930 237 747 2 × 2 = 1 + 0.860 475 494 4;
  • 27) 0.860 475 494 4 × 2 = 1 + 0.720 950 988 8;
  • 28) 0.720 950 988 8 × 2 = 1 + 0.441 901 977 6;
  • 29) 0.441 901 977 6 × 2 = 0 + 0.883 803 955 2;
  • 30) 0.883 803 955 2 × 2 = 1 + 0.767 607 910 4;
  • 31) 0.767 607 910 4 × 2 = 1 + 0.535 215 820 8;
  • 32) 0.535 215 820 8 × 2 = 1 + 0.070 431 641 6;
  • 33) 0.070 431 641 6 × 2 = 0 + 0.140 863 283 2;
  • 34) 0.140 863 283 2 × 2 = 0 + 0.281 726 566 4;
  • 35) 0.281 726 566 4 × 2 = 0 + 0.563 453 132 8;
  • 36) 0.563 453 132 8 × 2 = 1 + 0.126 906 265 6;
  • 37) 0.126 906 265 6 × 2 = 0 + 0.253 812 531 2;
  • 38) 0.253 812 531 2 × 2 = 0 + 0.507 625 062 4;
  • 39) 0.507 625 062 4 × 2 = 1 + 0.015 250 124 8;
  • 40) 0.015 250 124 8 × 2 = 0 + 0.030 500 249 6;
  • 41) 0.030 500 249 6 × 2 = 0 + 0.061 000 499 2;
  • 42) 0.061 000 499 2 × 2 = 0 + 0.122 000 998 4;
  • 43) 0.122 000 998 4 × 2 = 0 + 0.244 001 996 8;
  • 44) 0.244 001 996 8 × 2 = 0 + 0.488 003 993 6;
  • 45) 0.488 003 993 6 × 2 = 0 + 0.976 007 987 2;
  • 46) 0.976 007 987 2 × 2 = 1 + 0.952 015 974 4;
  • 47) 0.952 015 974 4 × 2 = 1 + 0.904 031 948 8;
  • 48) 0.904 031 948 8 × 2 = 1 + 0.808 063 897 6;
  • 49) 0.808 063 897 6 × 2 = 1 + 0.616 127 795 2;
  • 50) 0.616 127 795 2 × 2 = 1 + 0.232 255 590 4;
  • 51) 0.232 255 590 4 × 2 = 0 + 0.464 511 180 8;
  • 52) 0.464 511 180 8 × 2 = 0 + 0.929 022 361 6;
  • 53) 0.929 022 361 6 × 2 = 1 + 0.858 044 723 2;
  • 54) 0.858 044 723 2 × 2 = 1 + 0.716 089 446 4;
  • 55) 0.716 089 446 4 × 2 = 1 + 0.432 178 892 8;
  • 56) 0.432 178 892 8 × 2 = 0 + 0.864 357 785 6;
  • 57) 0.864 357 785 6 × 2 = 1 + 0.728 715 571 2;
  • 58) 0.728 715 571 2 × 2 = 1 + 0.457 431 142 4;
  • 59) 0.457 431 142 4 × 2 = 0 + 0.914 862 284 8;
  • 60) 0.914 862 284 8 × 2 = 1 + 0.829 724 569 6;
  • 61) 0.829 724 569 6 × 2 = 1 + 0.659 449 139 2;
  • 62) 0.659 449 139 2 × 2 = 1 + 0.318 898 278 4;
  • 63) 0.318 898 278 4 × 2 = 0 + 0.637 796 556 8;
  • 64) 0.637 796 556 8 × 2 = 1 + 0.275 593 113 6;

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:


0.000 282 047 1(10) =


0.0000 0000 0001 0010 0111 1011 1111 0111 0001 0010 0000 0111 1100 1110 1101 1101(2)

6. Positive number before normalization:

0.000 282 047 1(10) =


0.0000 0000 0001 0010 0111 1011 1111 0111 0001 0010 0000 0111 1100 1110 1101 1101(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:


0.000 282 047 1(10) =


0.0000 0000 0001 0010 0111 1011 1111 0111 0001 0010 0000 0111 1100 1110 1101 1101(2) =


0.0000 0000 0001 0010 0111 1011 1111 0111 0001 0010 0000 0111 1100 1110 1101 1101(2) × 20 =


1.0010 0111 1011 1111 0111 0001 0010 0000 0111 1100 1110 1101 1101(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 1111 0111 0001 0010 0000 0111 1100 1110 1101 1101


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 1111 0111 0001 0010 0000 0111 1100 1110 1101 1101 =


0010 0111 1011 1111 0111 0001 0010 0000 0111 1100 1110 1101 1101


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 1111 0111 0001 0010 0000 0111 1100 1110 1101 1101


Decimal number -0.000 282 047 1 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 1111 0111 0001 0010 0000 0111 1100 1110 1101 1101


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