-0.000 282 016 35 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 016 35(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
-0.000 282 016 35(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:

|-0.000 282 016 35| = 0.000 282 016 35


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: 0.000 282 016 35.

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) 0.000 282 016 35 × 2 = 0 + 0.000 564 032 7;
  • 2) 0.000 564 032 7 × 2 = 0 + 0.001 128 065 4;
  • 3) 0.001 128 065 4 × 2 = 0 + 0.002 256 130 8;
  • 4) 0.002 256 130 8 × 2 = 0 + 0.004 512 261 6;
  • 5) 0.004 512 261 6 × 2 = 0 + 0.009 024 523 2;
  • 6) 0.009 024 523 2 × 2 = 0 + 0.018 049 046 4;
  • 7) 0.018 049 046 4 × 2 = 0 + 0.036 098 092 8;
  • 8) 0.036 098 092 8 × 2 = 0 + 0.072 196 185 6;
  • 9) 0.072 196 185 6 × 2 = 0 + 0.144 392 371 2;
  • 10) 0.144 392 371 2 × 2 = 0 + 0.288 784 742 4;
  • 11) 0.288 784 742 4 × 2 = 0 + 0.577 569 484 8;
  • 12) 0.577 569 484 8 × 2 = 1 + 0.155 138 969 6;
  • 13) 0.155 138 969 6 × 2 = 0 + 0.310 277 939 2;
  • 14) 0.310 277 939 2 × 2 = 0 + 0.620 555 878 4;
  • 15) 0.620 555 878 4 × 2 = 1 + 0.241 111 756 8;
  • 16) 0.241 111 756 8 × 2 = 0 + 0.482 223 513 6;
  • 17) 0.482 223 513 6 × 2 = 0 + 0.964 447 027 2;
  • 18) 0.964 447 027 2 × 2 = 1 + 0.928 894 054 4;
  • 19) 0.928 894 054 4 × 2 = 1 + 0.857 788 108 8;
  • 20) 0.857 788 108 8 × 2 = 1 + 0.715 576 217 6;
  • 21) 0.715 576 217 6 × 2 = 1 + 0.431 152 435 2;
  • 22) 0.431 152 435 2 × 2 = 0 + 0.862 304 870 4;
  • 23) 0.862 304 870 4 × 2 = 1 + 0.724 609 740 8;
  • 24) 0.724 609 740 8 × 2 = 1 + 0.449 219 481 6;
  • 25) 0.449 219 481 6 × 2 = 0 + 0.898 438 963 2;
  • 26) 0.898 438 963 2 × 2 = 1 + 0.796 877 926 4;
  • 27) 0.796 877 926 4 × 2 = 1 + 0.593 755 852 8;
  • 28) 0.593 755 852 8 × 2 = 1 + 0.187 511 705 6;
  • 29) 0.187 511 705 6 × 2 = 0 + 0.375 023 411 2;
  • 30) 0.375 023 411 2 × 2 = 0 + 0.750 046 822 4;
  • 31) 0.750 046 822 4 × 2 = 1 + 0.500 093 644 8;
  • 32) 0.500 093 644 8 × 2 = 1 + 0.000 187 289 6;
  • 33) 0.000 187 289 6 × 2 = 0 + 0.000 374 579 2;
  • 34) 0.000 374 579 2 × 2 = 0 + 0.000 749 158 4;
  • 35) 0.000 749 158 4 × 2 = 0 + 0.001 498 316 8;
  • 36) 0.001 498 316 8 × 2 = 0 + 0.002 996 633 6;
  • 37) 0.002 996 633 6 × 2 = 0 + 0.005 993 267 2;
  • 38) 0.005 993 267 2 × 2 = 0 + 0.011 986 534 4;
  • 39) 0.011 986 534 4 × 2 = 0 + 0.023 973 068 8;
  • 40) 0.023 973 068 8 × 2 = 0 + 0.047 946 137 6;
  • 41) 0.047 946 137 6 × 2 = 0 + 0.095 892 275 2;
  • 42) 0.095 892 275 2 × 2 = 0 + 0.191 784 550 4;
  • 43) 0.191 784 550 4 × 2 = 0 + 0.383 569 100 8;
  • 44) 0.383 569 100 8 × 2 = 0 + 0.767 138 201 6;
  • 45) 0.767 138 201 6 × 2 = 1 + 0.534 276 403 2;
  • 46) 0.534 276 403 2 × 2 = 1 + 0.068 552 806 4;
  • 47) 0.068 552 806 4 × 2 = 0 + 0.137 105 612 8;
  • 48) 0.137 105 612 8 × 2 = 0 + 0.274 211 225 6;
  • 49) 0.274 211 225 6 × 2 = 0 + 0.548 422 451 2;
  • 50) 0.548 422 451 2 × 2 = 1 + 0.096 844 902 4;
  • 51) 0.096 844 902 4 × 2 = 0 + 0.193 689 804 8;
  • 52) 0.193 689 804 8 × 2 = 0 + 0.387 379 609 6;
  • 53) 0.387 379 609 6 × 2 = 0 + 0.774 759 219 2;
  • 54) 0.774 759 219 2 × 2 = 1 + 0.549 518 438 4;
  • 55) 0.549 518 438 4 × 2 = 1 + 0.099 036 876 8;
  • 56) 0.099 036 876 8 × 2 = 0 + 0.198 073 753 6;
  • 57) 0.198 073 753 6 × 2 = 0 + 0.396 147 507 2;
  • 58) 0.396 147 507 2 × 2 = 0 + 0.792 295 014 4;
  • 59) 0.792 295 014 4 × 2 = 1 + 0.584 590 028 8;
  • 60) 0.584 590 028 8 × 2 = 1 + 0.169 180 057 6;
  • 61) 0.169 180 057 6 × 2 = 0 + 0.338 360 115 2;
  • 62) 0.338 360 115 2 × 2 = 0 + 0.676 720 230 4;
  • 63) 0.676 720 230 4 × 2 = 1 + 0.353 440 460 8;
  • 64) 0.353 440 460 8 × 2 = 0 + 0.706 880 921 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:


0.000 282 016 35(10) =


0.0000 0000 0001 0010 0111 1011 0111 0011 0000 0000 0000 1100 0100 0110 0011 0010(2)

6. Positive number before normalization:

0.000 282 016 35(10) =


0.0000 0000 0001 0010 0111 1011 0111 0011 0000 0000 0000 1100 0100 0110 0011 0010(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:


0.000 282 016 35(10) =


0.0000 0000 0001 0010 0111 1011 0111 0011 0000 0000 0000 1100 0100 0110 0011 0010(2) =


0.0000 0000 0001 0010 0111 1011 0111 0011 0000 0000 0000 1100 0100 0110 0011 0010(2) × 20 =


1.0010 0111 1011 0111 0011 0000 0000 0000 1100 0100 0110 0011 0010(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 0111 0011 0000 0000 0000 1100 0100 0110 0011 0010


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 0111 0011 0000 0000 0000 1100 0100 0110 0011 0010 =


0010 0111 1011 0111 0011 0000 0000 0000 1100 0100 0110 0011 0010


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 0111 0011 0000 0000 0000 1100 0100 0110 0011 0010


Decimal number -0.000 282 016 35 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0111 0011 0000 0000 0000 1100 0100 0110 0011 0010


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