-0.000 282 043 6 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 043 6(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
-0.000 282 043 6(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:

|-0.000 282 043 6| = 0.000 282 043 6


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: 0.000 282 043 6.

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) 0.000 282 043 6 × 2 = 0 + 0.000 564 087 2;
  • 2) 0.000 564 087 2 × 2 = 0 + 0.001 128 174 4;
  • 3) 0.001 128 174 4 × 2 = 0 + 0.002 256 348 8;
  • 4) 0.002 256 348 8 × 2 = 0 + 0.004 512 697 6;
  • 5) 0.004 512 697 6 × 2 = 0 + 0.009 025 395 2;
  • 6) 0.009 025 395 2 × 2 = 0 + 0.018 050 790 4;
  • 7) 0.018 050 790 4 × 2 = 0 + 0.036 101 580 8;
  • 8) 0.036 101 580 8 × 2 = 0 + 0.072 203 161 6;
  • 9) 0.072 203 161 6 × 2 = 0 + 0.144 406 323 2;
  • 10) 0.144 406 323 2 × 2 = 0 + 0.288 812 646 4;
  • 11) 0.288 812 646 4 × 2 = 0 + 0.577 625 292 8;
  • 12) 0.577 625 292 8 × 2 = 1 + 0.155 250 585 6;
  • 13) 0.155 250 585 6 × 2 = 0 + 0.310 501 171 2;
  • 14) 0.310 501 171 2 × 2 = 0 + 0.621 002 342 4;
  • 15) 0.621 002 342 4 × 2 = 1 + 0.242 004 684 8;
  • 16) 0.242 004 684 8 × 2 = 0 + 0.484 009 369 6;
  • 17) 0.484 009 369 6 × 2 = 0 + 0.968 018 739 2;
  • 18) 0.968 018 739 2 × 2 = 1 + 0.936 037 478 4;
  • 19) 0.936 037 478 4 × 2 = 1 + 0.872 074 956 8;
  • 20) 0.872 074 956 8 × 2 = 1 + 0.744 149 913 6;
  • 21) 0.744 149 913 6 × 2 = 1 + 0.488 299 827 2;
  • 22) 0.488 299 827 2 × 2 = 0 + 0.976 599 654 4;
  • 23) 0.976 599 654 4 × 2 = 1 + 0.953 199 308 8;
  • 24) 0.953 199 308 8 × 2 = 1 + 0.906 398 617 6;
  • 25) 0.906 398 617 6 × 2 = 1 + 0.812 797 235 2;
  • 26) 0.812 797 235 2 × 2 = 1 + 0.625 594 470 4;
  • 27) 0.625 594 470 4 × 2 = 1 + 0.251 188 940 8;
  • 28) 0.251 188 940 8 × 2 = 0 + 0.502 377 881 6;
  • 29) 0.502 377 881 6 × 2 = 1 + 0.004 755 763 2;
  • 30) 0.004 755 763 2 × 2 = 0 + 0.009 511 526 4;
  • 31) 0.009 511 526 4 × 2 = 0 + 0.019 023 052 8;
  • 32) 0.019 023 052 8 × 2 = 0 + 0.038 046 105 6;
  • 33) 0.038 046 105 6 × 2 = 0 + 0.076 092 211 2;
  • 34) 0.076 092 211 2 × 2 = 0 + 0.152 184 422 4;
  • 35) 0.152 184 422 4 × 2 = 0 + 0.304 368 844 8;
  • 36) 0.304 368 844 8 × 2 = 0 + 0.608 737 689 6;
  • 37) 0.608 737 689 6 × 2 = 1 + 0.217 475 379 2;
  • 38) 0.217 475 379 2 × 2 = 0 + 0.434 950 758 4;
  • 39) 0.434 950 758 4 × 2 = 0 + 0.869 901 516 8;
  • 40) 0.869 901 516 8 × 2 = 1 + 0.739 803 033 6;
  • 41) 0.739 803 033 6 × 2 = 1 + 0.479 606 067 2;
  • 42) 0.479 606 067 2 × 2 = 0 + 0.959 212 134 4;
  • 43) 0.959 212 134 4 × 2 = 1 + 0.918 424 268 8;
  • 44) 0.918 424 268 8 × 2 = 1 + 0.836 848 537 6;
  • 45) 0.836 848 537 6 × 2 = 1 + 0.673 697 075 2;
  • 46) 0.673 697 075 2 × 2 = 1 + 0.347 394 150 4;
  • 47) 0.347 394 150 4 × 2 = 0 + 0.694 788 300 8;
  • 48) 0.694 788 300 8 × 2 = 1 + 0.389 576 601 6;
  • 49) 0.389 576 601 6 × 2 = 0 + 0.779 153 203 2;
  • 50) 0.779 153 203 2 × 2 = 1 + 0.558 306 406 4;
  • 51) 0.558 306 406 4 × 2 = 1 + 0.116 612 812 8;
  • 52) 0.116 612 812 8 × 2 = 0 + 0.233 225 625 6;
  • 53) 0.233 225 625 6 × 2 = 0 + 0.466 451 251 2;
  • 54) 0.466 451 251 2 × 2 = 0 + 0.932 902 502 4;
  • 55) 0.932 902 502 4 × 2 = 1 + 0.865 805 004 8;
  • 56) 0.865 805 004 8 × 2 = 1 + 0.731 610 009 6;
  • 57) 0.731 610 009 6 × 2 = 1 + 0.463 220 019 2;
  • 58) 0.463 220 019 2 × 2 = 0 + 0.926 440 038 4;
  • 59) 0.926 440 038 4 × 2 = 1 + 0.852 880 076 8;
  • 60) 0.852 880 076 8 × 2 = 1 + 0.705 760 153 6;
  • 61) 0.705 760 153 6 × 2 = 1 + 0.411 520 307 2;
  • 62) 0.411 520 307 2 × 2 = 0 + 0.823 040 614 4;
  • 63) 0.823 040 614 4 × 2 = 1 + 0.646 081 228 8;
  • 64) 0.646 081 228 8 × 2 = 1 + 0.292 162 457 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:


0.000 282 043 6(10) =


0.0000 0000 0001 0010 0111 1011 1110 1000 0000 1001 1011 1101 0110 0011 1011 1011(2)

6. Positive number before normalization:

0.000 282 043 6(10) =


0.0000 0000 0001 0010 0111 1011 1110 1000 0000 1001 1011 1101 0110 0011 1011 1011(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:


0.000 282 043 6(10) =


0.0000 0000 0001 0010 0111 1011 1110 1000 0000 1001 1011 1101 0110 0011 1011 1011(2) =


0.0000 0000 0001 0010 0111 1011 1110 1000 0000 1001 1011 1101 0110 0011 1011 1011(2) × 20 =


1.0010 0111 1011 1110 1000 0000 1001 1011 1101 0110 0011 1011 1011(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 1110 1000 0000 1001 1011 1101 0110 0011 1011 1011


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 1110 1000 0000 1001 1011 1101 0110 0011 1011 1011 =


0010 0111 1011 1110 1000 0000 1001 1011 1101 0110 0011 1011 1011


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 1110 1000 0000 1001 1011 1101 0110 0011 1011 1011


Decimal number -0.000 282 043 6 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 1110 1000 0000 1001 1011 1101 0110 0011 1011 1011


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