-0.000 282 005 85 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 85(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
-0.000 282 005 85(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:

|-0.000 282 005 85| = 0.000 282 005 85


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: 0.000 282 005 85.

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) 0.000 282 005 85 × 2 = 0 + 0.000 564 011 7;
  • 2) 0.000 564 011 7 × 2 = 0 + 0.001 128 023 4;
  • 3) 0.001 128 023 4 × 2 = 0 + 0.002 256 046 8;
  • 4) 0.002 256 046 8 × 2 = 0 + 0.004 512 093 6;
  • 5) 0.004 512 093 6 × 2 = 0 + 0.009 024 187 2;
  • 6) 0.009 024 187 2 × 2 = 0 + 0.018 048 374 4;
  • 7) 0.018 048 374 4 × 2 = 0 + 0.036 096 748 8;
  • 8) 0.036 096 748 8 × 2 = 0 + 0.072 193 497 6;
  • 9) 0.072 193 497 6 × 2 = 0 + 0.144 386 995 2;
  • 10) 0.144 386 995 2 × 2 = 0 + 0.288 773 990 4;
  • 11) 0.288 773 990 4 × 2 = 0 + 0.577 547 980 8;
  • 12) 0.577 547 980 8 × 2 = 1 + 0.155 095 961 6;
  • 13) 0.155 095 961 6 × 2 = 0 + 0.310 191 923 2;
  • 14) 0.310 191 923 2 × 2 = 0 + 0.620 383 846 4;
  • 15) 0.620 383 846 4 × 2 = 1 + 0.240 767 692 8;
  • 16) 0.240 767 692 8 × 2 = 0 + 0.481 535 385 6;
  • 17) 0.481 535 385 6 × 2 = 0 + 0.963 070 771 2;
  • 18) 0.963 070 771 2 × 2 = 1 + 0.926 141 542 4;
  • 19) 0.926 141 542 4 × 2 = 1 + 0.852 283 084 8;
  • 20) 0.852 283 084 8 × 2 = 1 + 0.704 566 169 6;
  • 21) 0.704 566 169 6 × 2 = 1 + 0.409 132 339 2;
  • 22) 0.409 132 339 2 × 2 = 0 + 0.818 264 678 4;
  • 23) 0.818 264 678 4 × 2 = 1 + 0.636 529 356 8;
  • 24) 0.636 529 356 8 × 2 = 1 + 0.273 058 713 6;
  • 25) 0.273 058 713 6 × 2 = 0 + 0.546 117 427 2;
  • 26) 0.546 117 427 2 × 2 = 1 + 0.092 234 854 4;
  • 27) 0.092 234 854 4 × 2 = 0 + 0.184 469 708 8;
  • 28) 0.184 469 708 8 × 2 = 0 + 0.368 939 417 6;
  • 29) 0.368 939 417 6 × 2 = 0 + 0.737 878 835 2;
  • 30) 0.737 878 835 2 × 2 = 1 + 0.475 757 670 4;
  • 31) 0.475 757 670 4 × 2 = 0 + 0.951 515 340 8;
  • 32) 0.951 515 340 8 × 2 = 1 + 0.903 030 681 6;
  • 33) 0.903 030 681 6 × 2 = 1 + 0.806 061 363 2;
  • 34) 0.806 061 363 2 × 2 = 1 + 0.612 122 726 4;
  • 35) 0.612 122 726 4 × 2 = 1 + 0.224 245 452 8;
  • 36) 0.224 245 452 8 × 2 = 0 + 0.448 490 905 6;
  • 37) 0.448 490 905 6 × 2 = 0 + 0.896 981 811 2;
  • 38) 0.896 981 811 2 × 2 = 1 + 0.793 963 622 4;
  • 39) 0.793 963 622 4 × 2 = 1 + 0.587 927 244 8;
  • 40) 0.587 927 244 8 × 2 = 1 + 0.175 854 489 6;
  • 41) 0.175 854 489 6 × 2 = 0 + 0.351 708 979 2;
  • 42) 0.351 708 979 2 × 2 = 0 + 0.703 417 958 4;
  • 43) 0.703 417 958 4 × 2 = 1 + 0.406 835 916 8;
  • 44) 0.406 835 916 8 × 2 = 0 + 0.813 671 833 6;
  • 45) 0.813 671 833 6 × 2 = 1 + 0.627 343 667 2;
  • 46) 0.627 343 667 2 × 2 = 1 + 0.254 687 334 4;
  • 47) 0.254 687 334 4 × 2 = 0 + 0.509 374 668 8;
  • 48) 0.509 374 668 8 × 2 = 1 + 0.018 749 337 6;
  • 49) 0.018 749 337 6 × 2 = 0 + 0.037 498 675 2;
  • 50) 0.037 498 675 2 × 2 = 0 + 0.074 997 350 4;
  • 51) 0.074 997 350 4 × 2 = 0 + 0.149 994 700 8;
  • 52) 0.149 994 700 8 × 2 = 0 + 0.299 989 401 6;
  • 53) 0.299 989 401 6 × 2 = 0 + 0.599 978 803 2;
  • 54) 0.599 978 803 2 × 2 = 1 + 0.199 957 606 4;
  • 55) 0.199 957 606 4 × 2 = 0 + 0.399 915 212 8;
  • 56) 0.399 915 212 8 × 2 = 0 + 0.799 830 425 6;
  • 57) 0.799 830 425 6 × 2 = 1 + 0.599 660 851 2;
  • 58) 0.599 660 851 2 × 2 = 1 + 0.199 321 702 4;
  • 59) 0.199 321 702 4 × 2 = 0 + 0.398 643 404 8;
  • 60) 0.398 643 404 8 × 2 = 0 + 0.797 286 809 6;
  • 61) 0.797 286 809 6 × 2 = 1 + 0.594 573 619 2;
  • 62) 0.594 573 619 2 × 2 = 1 + 0.189 147 238 4;
  • 63) 0.189 147 238 4 × 2 = 0 + 0.378 294 476 8;
  • 64) 0.378 294 476 8 × 2 = 0 + 0.756 588 953 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:


0.000 282 005 85(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1110 0111 0010 1101 0000 0100 1100 1100(2)

6. Positive number before normalization:

0.000 282 005 85(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1110 0111 0010 1101 0000 0100 1100 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:


0.000 282 005 85(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1110 0111 0010 1101 0000 0100 1100 1100(2) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1110 0111 0010 1101 0000 0100 1100 1100(2) × 20 =


1.0010 0111 1011 0100 0101 1110 0111 0010 1101 0000 0100 1100 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 0100 0101 1110 0111 0010 1101 0000 0100 1100 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 0100 0101 1110 0111 0010 1101 0000 0100 1100 1100 =


0010 0111 1011 0100 0101 1110 0111 0010 1101 0000 0100 1100 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 0100 0101 1110 0111 0010 1101 0000 0100 1100 1100


Decimal number -0.000 282 005 85 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0101 1110 0111 0010 1101 0000 0100 1100 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