-0.000 282 006 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 2(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
-0.000 282 006 2(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:

|-0.000 282 006 2| = 0.000 282 006 2


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: 0.000 282 006 2.

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) 0.000 282 006 2 × 2 = 0 + 0.000 564 012 4;
  • 2) 0.000 564 012 4 × 2 = 0 + 0.001 128 024 8;
  • 3) 0.001 128 024 8 × 2 = 0 + 0.002 256 049 6;
  • 4) 0.002 256 049 6 × 2 = 0 + 0.004 512 099 2;
  • 5) 0.004 512 099 2 × 2 = 0 + 0.009 024 198 4;
  • 6) 0.009 024 198 4 × 2 = 0 + 0.018 048 396 8;
  • 7) 0.018 048 396 8 × 2 = 0 + 0.036 096 793 6;
  • 8) 0.036 096 793 6 × 2 = 0 + 0.072 193 587 2;
  • 9) 0.072 193 587 2 × 2 = 0 + 0.144 387 174 4;
  • 10) 0.144 387 174 4 × 2 = 0 + 0.288 774 348 8;
  • 11) 0.288 774 348 8 × 2 = 0 + 0.577 548 697 6;
  • 12) 0.577 548 697 6 × 2 = 1 + 0.155 097 395 2;
  • 13) 0.155 097 395 2 × 2 = 0 + 0.310 194 790 4;
  • 14) 0.310 194 790 4 × 2 = 0 + 0.620 389 580 8;
  • 15) 0.620 389 580 8 × 2 = 1 + 0.240 779 161 6;
  • 16) 0.240 779 161 6 × 2 = 0 + 0.481 558 323 2;
  • 17) 0.481 558 323 2 × 2 = 0 + 0.963 116 646 4;
  • 18) 0.963 116 646 4 × 2 = 1 + 0.926 233 292 8;
  • 19) 0.926 233 292 8 × 2 = 1 + 0.852 466 585 6;
  • 20) 0.852 466 585 6 × 2 = 1 + 0.704 933 171 2;
  • 21) 0.704 933 171 2 × 2 = 1 + 0.409 866 342 4;
  • 22) 0.409 866 342 4 × 2 = 0 + 0.819 732 684 8;
  • 23) 0.819 732 684 8 × 2 = 1 + 0.639 465 369 6;
  • 24) 0.639 465 369 6 × 2 = 1 + 0.278 930 739 2;
  • 25) 0.278 930 739 2 × 2 = 0 + 0.557 861 478 4;
  • 26) 0.557 861 478 4 × 2 = 1 + 0.115 722 956 8;
  • 27) 0.115 722 956 8 × 2 = 0 + 0.231 445 913 6;
  • 28) 0.231 445 913 6 × 2 = 0 + 0.462 891 827 2;
  • 29) 0.462 891 827 2 × 2 = 0 + 0.925 783 654 4;
  • 30) 0.925 783 654 4 × 2 = 1 + 0.851 567 308 8;
  • 31) 0.851 567 308 8 × 2 = 1 + 0.703 134 617 6;
  • 32) 0.703 134 617 6 × 2 = 1 + 0.406 269 235 2;
  • 33) 0.406 269 235 2 × 2 = 0 + 0.812 538 470 4;
  • 34) 0.812 538 470 4 × 2 = 1 + 0.625 076 940 8;
  • 35) 0.625 076 940 8 × 2 = 1 + 0.250 153 881 6;
  • 36) 0.250 153 881 6 × 2 = 0 + 0.500 307 763 2;
  • 37) 0.500 307 763 2 × 2 = 1 + 0.000 615 526 4;
  • 38) 0.000 615 526 4 × 2 = 0 + 0.001 231 052 8;
  • 39) 0.001 231 052 8 × 2 = 0 + 0.002 462 105 6;
  • 40) 0.002 462 105 6 × 2 = 0 + 0.004 924 211 2;
  • 41) 0.004 924 211 2 × 2 = 0 + 0.009 848 422 4;
  • 42) 0.009 848 422 4 × 2 = 0 + 0.019 696 844 8;
  • 43) 0.019 696 844 8 × 2 = 0 + 0.039 393 689 6;
  • 44) 0.039 393 689 6 × 2 = 0 + 0.078 787 379 2;
  • 45) 0.078 787 379 2 × 2 = 0 + 0.157 574 758 4;
  • 46) 0.157 574 758 4 × 2 = 0 + 0.315 149 516 8;
  • 47) 0.315 149 516 8 × 2 = 0 + 0.630 299 033 6;
  • 48) 0.630 299 033 6 × 2 = 1 + 0.260 598 067 2;
  • 49) 0.260 598 067 2 × 2 = 0 + 0.521 196 134 4;
  • 50) 0.521 196 134 4 × 2 = 1 + 0.042 392 268 8;
  • 51) 0.042 392 268 8 × 2 = 0 + 0.084 784 537 6;
  • 52) 0.084 784 537 6 × 2 = 0 + 0.169 569 075 2;
  • 53) 0.169 569 075 2 × 2 = 0 + 0.339 138 150 4;
  • 54) 0.339 138 150 4 × 2 = 0 + 0.678 276 300 8;
  • 55) 0.678 276 300 8 × 2 = 1 + 0.356 552 601 6;
  • 56) 0.356 552 601 6 × 2 = 0 + 0.713 105 203 2;
  • 57) 0.713 105 203 2 × 2 = 1 + 0.426 210 406 4;
  • 58) 0.426 210 406 4 × 2 = 0 + 0.852 420 812 8;
  • 59) 0.852 420 812 8 × 2 = 1 + 0.704 841 625 6;
  • 60) 0.704 841 625 6 × 2 = 1 + 0.409 683 251 2;
  • 61) 0.409 683 251 2 × 2 = 0 + 0.819 366 502 4;
  • 62) 0.819 366 502 4 × 2 = 1 + 0.638 733 004 8;
  • 63) 0.638 733 004 8 × 2 = 1 + 0.277 466 009 6;
  • 64) 0.277 466 009 6 × 2 = 0 + 0.554 932 019 2;

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:


0.000 282 006 2(10) =


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

6. Positive number before normalization:

0.000 282 006 2(10) =


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


0.000 282 006 2(10) =


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


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


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


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 0111 0110 1000 0000 0001 0100 0010 1011 0110 =


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


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 0111 0110 1000 0000 0001 0100 0010 1011 0110


Decimal number -0.000 282 006 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

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


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