-0.000 282 005 906 3 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 906 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
-0.000 282 005 906 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:

|-0.000 282 005 906 3| = 0.000 282 005 906 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: 0.000 282 005 906 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) 0.000 282 005 906 3 × 2 = 0 + 0.000 564 011 812 6;
  • 2) 0.000 564 011 812 6 × 2 = 0 + 0.001 128 023 625 2;
  • 3) 0.001 128 023 625 2 × 2 = 0 + 0.002 256 047 250 4;
  • 4) 0.002 256 047 250 4 × 2 = 0 + 0.004 512 094 500 8;
  • 5) 0.004 512 094 500 8 × 2 = 0 + 0.009 024 189 001 6;
  • 6) 0.009 024 189 001 6 × 2 = 0 + 0.018 048 378 003 2;
  • 7) 0.018 048 378 003 2 × 2 = 0 + 0.036 096 756 006 4;
  • 8) 0.036 096 756 006 4 × 2 = 0 + 0.072 193 512 012 8;
  • 9) 0.072 193 512 012 8 × 2 = 0 + 0.144 387 024 025 6;
  • 10) 0.144 387 024 025 6 × 2 = 0 + 0.288 774 048 051 2;
  • 11) 0.288 774 048 051 2 × 2 = 0 + 0.577 548 096 102 4;
  • 12) 0.577 548 096 102 4 × 2 = 1 + 0.155 096 192 204 8;
  • 13) 0.155 096 192 204 8 × 2 = 0 + 0.310 192 384 409 6;
  • 14) 0.310 192 384 409 6 × 2 = 0 + 0.620 384 768 819 2;
  • 15) 0.620 384 768 819 2 × 2 = 1 + 0.240 769 537 638 4;
  • 16) 0.240 769 537 638 4 × 2 = 0 + 0.481 539 075 276 8;
  • 17) 0.481 539 075 276 8 × 2 = 0 + 0.963 078 150 553 6;
  • 18) 0.963 078 150 553 6 × 2 = 1 + 0.926 156 301 107 2;
  • 19) 0.926 156 301 107 2 × 2 = 1 + 0.852 312 602 214 4;
  • 20) 0.852 312 602 214 4 × 2 = 1 + 0.704 625 204 428 8;
  • 21) 0.704 625 204 428 8 × 2 = 1 + 0.409 250 408 857 6;
  • 22) 0.409 250 408 857 6 × 2 = 0 + 0.818 500 817 715 2;
  • 23) 0.818 500 817 715 2 × 2 = 1 + 0.637 001 635 430 4;
  • 24) 0.637 001 635 430 4 × 2 = 1 + 0.274 003 270 860 8;
  • 25) 0.274 003 270 860 8 × 2 = 0 + 0.548 006 541 721 6;
  • 26) 0.548 006 541 721 6 × 2 = 1 + 0.096 013 083 443 2;
  • 27) 0.096 013 083 443 2 × 2 = 0 + 0.192 026 166 886 4;
  • 28) 0.192 026 166 886 4 × 2 = 0 + 0.384 052 333 772 8;
  • 29) 0.384 052 333 772 8 × 2 = 0 + 0.768 104 667 545 6;
  • 30) 0.768 104 667 545 6 × 2 = 1 + 0.536 209 335 091 2;
  • 31) 0.536 209 335 091 2 × 2 = 1 + 0.072 418 670 182 4;
  • 32) 0.072 418 670 182 4 × 2 = 0 + 0.144 837 340 364 8;
  • 33) 0.144 837 340 364 8 × 2 = 0 + 0.289 674 680 729 6;
  • 34) 0.289 674 680 729 6 × 2 = 0 + 0.579 349 361 459 2;
  • 35) 0.579 349 361 459 2 × 2 = 1 + 0.158 698 722 918 4;
  • 36) 0.158 698 722 918 4 × 2 = 0 + 0.317 397 445 836 8;
  • 37) 0.317 397 445 836 8 × 2 = 0 + 0.634 794 891 673 6;
  • 38) 0.634 794 891 673 6 × 2 = 1 + 0.269 589 783 347 2;
  • 39) 0.269 589 783 347 2 × 2 = 0 + 0.539 179 566 694 4;
  • 40) 0.539 179 566 694 4 × 2 = 1 + 0.078 359 133 388 8;
  • 41) 0.078 359 133 388 8 × 2 = 0 + 0.156 718 266 777 6;
  • 42) 0.156 718 266 777 6 × 2 = 0 + 0.313 436 533 555 2;
  • 43) 0.313 436 533 555 2 × 2 = 0 + 0.626 873 067 110 4;
  • 44) 0.626 873 067 110 4 × 2 = 1 + 0.253 746 134 220 8;
  • 45) 0.253 746 134 220 8 × 2 = 0 + 0.507 492 268 441 6;
  • 46) 0.507 492 268 441 6 × 2 = 1 + 0.014 984 536 883 2;
  • 47) 0.014 984 536 883 2 × 2 = 0 + 0.029 969 073 766 4;
  • 48) 0.029 969 073 766 4 × 2 = 0 + 0.059 938 147 532 8;
  • 49) 0.059 938 147 532 8 × 2 = 0 + 0.119 876 295 065 6;
  • 50) 0.119 876 295 065 6 × 2 = 0 + 0.239 752 590 131 2;
  • 51) 0.239 752 590 131 2 × 2 = 0 + 0.479 505 180 262 4;
  • 52) 0.479 505 180 262 4 × 2 = 0 + 0.959 010 360 524 8;
  • 53) 0.959 010 360 524 8 × 2 = 1 + 0.918 020 721 049 6;
  • 54) 0.918 020 721 049 6 × 2 = 1 + 0.836 041 442 099 2;
  • 55) 0.836 041 442 099 2 × 2 = 1 + 0.672 082 884 198 4;
  • 56) 0.672 082 884 198 4 × 2 = 1 + 0.344 165 768 396 8;
  • 57) 0.344 165 768 396 8 × 2 = 0 + 0.688 331 536 793 6;
  • 58) 0.688 331 536 793 6 × 2 = 1 + 0.376 663 073 587 2;
  • 59) 0.376 663 073 587 2 × 2 = 0 + 0.753 326 147 174 4;
  • 60) 0.753 326 147 174 4 × 2 = 1 + 0.506 652 294 348 8;
  • 61) 0.506 652 294 348 8 × 2 = 1 + 0.013 304 588 697 6;
  • 62) 0.013 304 588 697 6 × 2 = 0 + 0.026 609 177 395 2;
  • 63) 0.026 609 177 395 2 × 2 = 0 + 0.053 218 354 790 4;
  • 64) 0.053 218 354 790 4 × 2 = 0 + 0.106 436 709 580 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:


0.000 282 005 906 3(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 0101 0001 0100 0000 1111 0101 1000(2)

6. Positive number before normalization:

0.000 282 005 906 3(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 0101 0001 0100 0000 1111 0101 1000(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:


0.000 282 005 906 3(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 0101 0001 0100 0000 1111 0101 1000(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 0101 0001 0100 0000 1111 0101 1000(2) × 20 =


1.0010 0111 1011 0100 0110 0010 0101 0001 0100 0000 1111 0101 1000(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 0110 0010 0101 0001 0100 0000 1111 0101 1000


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 0110 0010 0101 0001 0100 0000 1111 0101 1000 =


0010 0111 1011 0100 0110 0010 0101 0001 0100 0000 1111 0101 1000


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 0110 0010 0101 0001 0100 0000 1111 0101 1000


Decimal number -0.000 282 005 906 3 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0010 0101 0001 0100 0000 1111 0101 1000


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