-0.000 282 020 1 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 020 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
-0.000 282 020 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:

|-0.000 282 020 1| = 0.000 282 020 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: 0.000 282 020 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) 0.000 282 020 1 × 2 = 0 + 0.000 564 040 2;
  • 2) 0.000 564 040 2 × 2 = 0 + 0.001 128 080 4;
  • 3) 0.001 128 080 4 × 2 = 0 + 0.002 256 160 8;
  • 4) 0.002 256 160 8 × 2 = 0 + 0.004 512 321 6;
  • 5) 0.004 512 321 6 × 2 = 0 + 0.009 024 643 2;
  • 6) 0.009 024 643 2 × 2 = 0 + 0.018 049 286 4;
  • 7) 0.018 049 286 4 × 2 = 0 + 0.036 098 572 8;
  • 8) 0.036 098 572 8 × 2 = 0 + 0.072 197 145 6;
  • 9) 0.072 197 145 6 × 2 = 0 + 0.144 394 291 2;
  • 10) 0.144 394 291 2 × 2 = 0 + 0.288 788 582 4;
  • 11) 0.288 788 582 4 × 2 = 0 + 0.577 577 164 8;
  • 12) 0.577 577 164 8 × 2 = 1 + 0.155 154 329 6;
  • 13) 0.155 154 329 6 × 2 = 0 + 0.310 308 659 2;
  • 14) 0.310 308 659 2 × 2 = 0 + 0.620 617 318 4;
  • 15) 0.620 617 318 4 × 2 = 1 + 0.241 234 636 8;
  • 16) 0.241 234 636 8 × 2 = 0 + 0.482 469 273 6;
  • 17) 0.482 469 273 6 × 2 = 0 + 0.964 938 547 2;
  • 18) 0.964 938 547 2 × 2 = 1 + 0.929 877 094 4;
  • 19) 0.929 877 094 4 × 2 = 1 + 0.859 754 188 8;
  • 20) 0.859 754 188 8 × 2 = 1 + 0.719 508 377 6;
  • 21) 0.719 508 377 6 × 2 = 1 + 0.439 016 755 2;
  • 22) 0.439 016 755 2 × 2 = 0 + 0.878 033 510 4;
  • 23) 0.878 033 510 4 × 2 = 1 + 0.756 067 020 8;
  • 24) 0.756 067 020 8 × 2 = 1 + 0.512 134 041 6;
  • 25) 0.512 134 041 6 × 2 = 1 + 0.024 268 083 2;
  • 26) 0.024 268 083 2 × 2 = 0 + 0.048 536 166 4;
  • 27) 0.048 536 166 4 × 2 = 0 + 0.097 072 332 8;
  • 28) 0.097 072 332 8 × 2 = 0 + 0.194 144 665 6;
  • 29) 0.194 144 665 6 × 2 = 0 + 0.388 289 331 2;
  • 30) 0.388 289 331 2 × 2 = 0 + 0.776 578 662 4;
  • 31) 0.776 578 662 4 × 2 = 1 + 0.553 157 324 8;
  • 32) 0.553 157 324 8 × 2 = 1 + 0.106 314 649 6;
  • 33) 0.106 314 649 6 × 2 = 0 + 0.212 629 299 2;
  • 34) 0.212 629 299 2 × 2 = 0 + 0.425 258 598 4;
  • 35) 0.425 258 598 4 × 2 = 0 + 0.850 517 196 8;
  • 36) 0.850 517 196 8 × 2 = 1 + 0.701 034 393 6;
  • 37) 0.701 034 393 6 × 2 = 1 + 0.402 068 787 2;
  • 38) 0.402 068 787 2 × 2 = 0 + 0.804 137 574 4;
  • 39) 0.804 137 574 4 × 2 = 1 + 0.608 275 148 8;
  • 40) 0.608 275 148 8 × 2 = 1 + 0.216 550 297 6;
  • 41) 0.216 550 297 6 × 2 = 0 + 0.433 100 595 2;
  • 42) 0.433 100 595 2 × 2 = 0 + 0.866 201 190 4;
  • 43) 0.866 201 190 4 × 2 = 1 + 0.732 402 380 8;
  • 44) 0.732 402 380 8 × 2 = 1 + 0.464 804 761 6;
  • 45) 0.464 804 761 6 × 2 = 0 + 0.929 609 523 2;
  • 46) 0.929 609 523 2 × 2 = 1 + 0.859 219 046 4;
  • 47) 0.859 219 046 4 × 2 = 1 + 0.718 438 092 8;
  • 48) 0.718 438 092 8 × 2 = 1 + 0.436 876 185 6;
  • 49) 0.436 876 185 6 × 2 = 0 + 0.873 752 371 2;
  • 50) 0.873 752 371 2 × 2 = 1 + 0.747 504 742 4;
  • 51) 0.747 504 742 4 × 2 = 1 + 0.495 009 484 8;
  • 52) 0.495 009 484 8 × 2 = 0 + 0.990 018 969 6;
  • 53) 0.990 018 969 6 × 2 = 1 + 0.980 037 939 2;
  • 54) 0.980 037 939 2 × 2 = 1 + 0.960 075 878 4;
  • 55) 0.960 075 878 4 × 2 = 1 + 0.920 151 756 8;
  • 56) 0.920 151 756 8 × 2 = 1 + 0.840 303 513 6;
  • 57) 0.840 303 513 6 × 2 = 1 + 0.680 607 027 2;
  • 58) 0.680 607 027 2 × 2 = 1 + 0.361 214 054 4;
  • 59) 0.361 214 054 4 × 2 = 0 + 0.722 428 108 8;
  • 60) 0.722 428 108 8 × 2 = 1 + 0.444 856 217 6;
  • 61) 0.444 856 217 6 × 2 = 0 + 0.889 712 435 2;
  • 62) 0.889 712 435 2 × 2 = 1 + 0.779 424 870 4;
  • 63) 0.779 424 870 4 × 2 = 1 + 0.558 849 740 8;
  • 64) 0.558 849 740 8 × 2 = 1 + 0.117 699 481 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:


0.000 282 020 1(10) =


0.0000 0000 0001 0010 0111 1011 1000 0011 0001 1011 0011 0111 0110 1111 1101 0111(2)

6. Positive number before normalization:

0.000 282 020 1(10) =


0.0000 0000 0001 0010 0111 1011 1000 0011 0001 1011 0011 0111 0110 1111 1101 0111(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 1(10) =


0.0000 0000 0001 0010 0111 1011 1000 0011 0001 1011 0011 0111 0110 1111 1101 0111(2) =


0.0000 0000 0001 0010 0111 1011 1000 0011 0001 1011 0011 0111 0110 1111 1101 0111(2) × 20 =


1.0010 0111 1011 1000 0011 0001 1011 0011 0111 0110 1111 1101 0111(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 0001 1011 0011 0111 0110 1111 1101 0111


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 0001 1011 0011 0111 0110 1111 1101 0111 =


0010 0111 1011 1000 0011 0001 1011 0011 0111 0110 1111 1101 0111


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 0001 1011 0011 0111 0110 1111 1101 0111


Decimal number -0.000 282 020 1 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 1000 0011 0001 1011 0011 0111 0110 1111 1101 0111


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