-0.000 282 038 1 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 038 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
-0.000 282 038 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:

|-0.000 282 038 1| = 0.000 282 038 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: 0.000 282 038 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) 0.000 282 038 1 × 2 = 0 + 0.000 564 076 2;
  • 2) 0.000 564 076 2 × 2 = 0 + 0.001 128 152 4;
  • 3) 0.001 128 152 4 × 2 = 0 + 0.002 256 304 8;
  • 4) 0.002 256 304 8 × 2 = 0 + 0.004 512 609 6;
  • 5) 0.004 512 609 6 × 2 = 0 + 0.009 025 219 2;
  • 6) 0.009 025 219 2 × 2 = 0 + 0.018 050 438 4;
  • 7) 0.018 050 438 4 × 2 = 0 + 0.036 100 876 8;
  • 8) 0.036 100 876 8 × 2 = 0 + 0.072 201 753 6;
  • 9) 0.072 201 753 6 × 2 = 0 + 0.144 403 507 2;
  • 10) 0.144 403 507 2 × 2 = 0 + 0.288 807 014 4;
  • 11) 0.288 807 014 4 × 2 = 0 + 0.577 614 028 8;
  • 12) 0.577 614 028 8 × 2 = 1 + 0.155 228 057 6;
  • 13) 0.155 228 057 6 × 2 = 0 + 0.310 456 115 2;
  • 14) 0.310 456 115 2 × 2 = 0 + 0.620 912 230 4;
  • 15) 0.620 912 230 4 × 2 = 1 + 0.241 824 460 8;
  • 16) 0.241 824 460 8 × 2 = 0 + 0.483 648 921 6;
  • 17) 0.483 648 921 6 × 2 = 0 + 0.967 297 843 2;
  • 18) 0.967 297 843 2 × 2 = 1 + 0.934 595 686 4;
  • 19) 0.934 595 686 4 × 2 = 1 + 0.869 191 372 8;
  • 20) 0.869 191 372 8 × 2 = 1 + 0.738 382 745 6;
  • 21) 0.738 382 745 6 × 2 = 1 + 0.476 765 491 2;
  • 22) 0.476 765 491 2 × 2 = 0 + 0.953 530 982 4;
  • 23) 0.953 530 982 4 × 2 = 1 + 0.907 061 964 8;
  • 24) 0.907 061 964 8 × 2 = 1 + 0.814 123 929 6;
  • 25) 0.814 123 929 6 × 2 = 1 + 0.628 247 859 2;
  • 26) 0.628 247 859 2 × 2 = 1 + 0.256 495 718 4;
  • 27) 0.256 495 718 4 × 2 = 0 + 0.512 991 436 8;
  • 28) 0.512 991 436 8 × 2 = 1 + 0.025 982 873 6;
  • 29) 0.025 982 873 6 × 2 = 0 + 0.051 965 747 2;
  • 30) 0.051 965 747 2 × 2 = 0 + 0.103 931 494 4;
  • 31) 0.103 931 494 4 × 2 = 0 + 0.207 862 988 8;
  • 32) 0.207 862 988 8 × 2 = 0 + 0.415 725 977 6;
  • 33) 0.415 725 977 6 × 2 = 0 + 0.831 451 955 2;
  • 34) 0.831 451 955 2 × 2 = 1 + 0.662 903 910 4;
  • 35) 0.662 903 910 4 × 2 = 1 + 0.325 807 820 8;
  • 36) 0.325 807 820 8 × 2 = 0 + 0.651 615 641 6;
  • 37) 0.651 615 641 6 × 2 = 1 + 0.303 231 283 2;
  • 38) 0.303 231 283 2 × 2 = 0 + 0.606 462 566 4;
  • 39) 0.606 462 566 4 × 2 = 1 + 0.212 925 132 8;
  • 40) 0.212 925 132 8 × 2 = 0 + 0.425 850 265 6;
  • 41) 0.425 850 265 6 × 2 = 0 + 0.851 700 531 2;
  • 42) 0.851 700 531 2 × 2 = 1 + 0.703 401 062 4;
  • 43) 0.703 401 062 4 × 2 = 1 + 0.406 802 124 8;
  • 44) 0.406 802 124 8 × 2 = 0 + 0.813 604 249 6;
  • 45) 0.813 604 249 6 × 2 = 1 + 0.627 208 499 2;
  • 46) 0.627 208 499 2 × 2 = 1 + 0.254 416 998 4;
  • 47) 0.254 416 998 4 × 2 = 0 + 0.508 833 996 8;
  • 48) 0.508 833 996 8 × 2 = 1 + 0.017 667 993 6;
  • 49) 0.017 667 993 6 × 2 = 0 + 0.035 335 987 2;
  • 50) 0.035 335 987 2 × 2 = 0 + 0.070 671 974 4;
  • 51) 0.070 671 974 4 × 2 = 0 + 0.141 343 948 8;
  • 52) 0.141 343 948 8 × 2 = 0 + 0.282 687 897 6;
  • 53) 0.282 687 897 6 × 2 = 0 + 0.565 375 795 2;
  • 54) 0.565 375 795 2 × 2 = 1 + 0.130 751 590 4;
  • 55) 0.130 751 590 4 × 2 = 0 + 0.261 503 180 8;
  • 56) 0.261 503 180 8 × 2 = 0 + 0.523 006 361 6;
  • 57) 0.523 006 361 6 × 2 = 1 + 0.046 012 723 2;
  • 58) 0.046 012 723 2 × 2 = 0 + 0.092 025 446 4;
  • 59) 0.092 025 446 4 × 2 = 0 + 0.184 050 892 8;
  • 60) 0.184 050 892 8 × 2 = 0 + 0.368 101 785 6;
  • 61) 0.368 101 785 6 × 2 = 0 + 0.736 203 571 2;
  • 62) 0.736 203 571 2 × 2 = 1 + 0.472 407 142 4;
  • 63) 0.472 407 142 4 × 2 = 0 + 0.944 814 284 8;
  • 64) 0.944 814 284 8 × 2 = 1 + 0.889 628 569 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:


0.000 282 038 1(10) =


0.0000 0000 0001 0010 0111 1011 1101 0000 0110 1010 0110 1101 0000 0100 1000 0101(2)

6. Positive number before normalization:

0.000 282 038 1(10) =


0.0000 0000 0001 0010 0111 1011 1101 0000 0110 1010 0110 1101 0000 0100 1000 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:


0.000 282 038 1(10) =


0.0000 0000 0001 0010 0111 1011 1101 0000 0110 1010 0110 1101 0000 0100 1000 0101(2) =


0.0000 0000 0001 0010 0111 1011 1101 0000 0110 1010 0110 1101 0000 0100 1000 0101(2) × 20 =


1.0010 0111 1011 1101 0000 0110 1010 0110 1101 0000 0100 1000 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 1101 0000 0110 1010 0110 1101 0000 0100 1000 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 1101 0000 0110 1010 0110 1101 0000 0100 1000 0101 =


0010 0111 1011 1101 0000 0110 1010 0110 1101 0000 0100 1000 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 1101 0000 0110 1010 0110 1101 0000 0100 1000 0101


Decimal number -0.000 282 038 1 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 1101 0000 0110 1010 0110 1101 0000 0100 1000 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