-0.000 282 009 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 009 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
-0.000 282 009 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:

|-0.000 282 009 2| = 0.000 282 009 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: 0.000 282 009 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) 0.000 282 009 2 × 2 = 0 + 0.000 564 018 4;
  • 2) 0.000 564 018 4 × 2 = 0 + 0.001 128 036 8;
  • 3) 0.001 128 036 8 × 2 = 0 + 0.002 256 073 6;
  • 4) 0.002 256 073 6 × 2 = 0 + 0.004 512 147 2;
  • 5) 0.004 512 147 2 × 2 = 0 + 0.009 024 294 4;
  • 6) 0.009 024 294 4 × 2 = 0 + 0.018 048 588 8;
  • 7) 0.018 048 588 8 × 2 = 0 + 0.036 097 177 6;
  • 8) 0.036 097 177 6 × 2 = 0 + 0.072 194 355 2;
  • 9) 0.072 194 355 2 × 2 = 0 + 0.144 388 710 4;
  • 10) 0.144 388 710 4 × 2 = 0 + 0.288 777 420 8;
  • 11) 0.288 777 420 8 × 2 = 0 + 0.577 554 841 6;
  • 12) 0.577 554 841 6 × 2 = 1 + 0.155 109 683 2;
  • 13) 0.155 109 683 2 × 2 = 0 + 0.310 219 366 4;
  • 14) 0.310 219 366 4 × 2 = 0 + 0.620 438 732 8;
  • 15) 0.620 438 732 8 × 2 = 1 + 0.240 877 465 6;
  • 16) 0.240 877 465 6 × 2 = 0 + 0.481 754 931 2;
  • 17) 0.481 754 931 2 × 2 = 0 + 0.963 509 862 4;
  • 18) 0.963 509 862 4 × 2 = 1 + 0.927 019 724 8;
  • 19) 0.927 019 724 8 × 2 = 1 + 0.854 039 449 6;
  • 20) 0.854 039 449 6 × 2 = 1 + 0.708 078 899 2;
  • 21) 0.708 078 899 2 × 2 = 1 + 0.416 157 798 4;
  • 22) 0.416 157 798 4 × 2 = 0 + 0.832 315 596 8;
  • 23) 0.832 315 596 8 × 2 = 1 + 0.664 631 193 6;
  • 24) 0.664 631 193 6 × 2 = 1 + 0.329 262 387 2;
  • 25) 0.329 262 387 2 × 2 = 0 + 0.658 524 774 4;
  • 26) 0.658 524 774 4 × 2 = 1 + 0.317 049 548 8;
  • 27) 0.317 049 548 8 × 2 = 0 + 0.634 099 097 6;
  • 28) 0.634 099 097 6 × 2 = 1 + 0.268 198 195 2;
  • 29) 0.268 198 195 2 × 2 = 0 + 0.536 396 390 4;
  • 30) 0.536 396 390 4 × 2 = 1 + 0.072 792 780 8;
  • 31) 0.072 792 780 8 × 2 = 0 + 0.145 585 561 6;
  • 32) 0.145 585 561 6 × 2 = 0 + 0.291 171 123 2;
  • 33) 0.291 171 123 2 × 2 = 0 + 0.582 342 246 4;
  • 34) 0.582 342 246 4 × 2 = 1 + 0.164 684 492 8;
  • 35) 0.164 684 492 8 × 2 = 0 + 0.329 368 985 6;
  • 36) 0.329 368 985 6 × 2 = 0 + 0.658 737 971 2;
  • 37) 0.658 737 971 2 × 2 = 1 + 0.317 475 942 4;
  • 38) 0.317 475 942 4 × 2 = 0 + 0.634 951 884 8;
  • 39) 0.634 951 884 8 × 2 = 1 + 0.269 903 769 6;
  • 40) 0.269 903 769 6 × 2 = 0 + 0.539 807 539 2;
  • 41) 0.539 807 539 2 × 2 = 1 + 0.079 615 078 4;
  • 42) 0.079 615 078 4 × 2 = 0 + 0.159 230 156 8;
  • 43) 0.159 230 156 8 × 2 = 0 + 0.318 460 313 6;
  • 44) 0.318 460 313 6 × 2 = 0 + 0.636 920 627 2;
  • 45) 0.636 920 627 2 × 2 = 1 + 0.273 841 254 4;
  • 46) 0.273 841 254 4 × 2 = 0 + 0.547 682 508 8;
  • 47) 0.547 682 508 8 × 2 = 1 + 0.095 365 017 6;
  • 48) 0.095 365 017 6 × 2 = 0 + 0.190 730 035 2;
  • 49) 0.190 730 035 2 × 2 = 0 + 0.381 460 070 4;
  • 50) 0.381 460 070 4 × 2 = 0 + 0.762 920 140 8;
  • 51) 0.762 920 140 8 × 2 = 1 + 0.525 840 281 6;
  • 52) 0.525 840 281 6 × 2 = 1 + 0.051 680 563 2;
  • 53) 0.051 680 563 2 × 2 = 0 + 0.103 361 126 4;
  • 54) 0.103 361 126 4 × 2 = 0 + 0.206 722 252 8;
  • 55) 0.206 722 252 8 × 2 = 0 + 0.413 444 505 6;
  • 56) 0.413 444 505 6 × 2 = 0 + 0.826 889 011 2;
  • 57) 0.826 889 011 2 × 2 = 1 + 0.653 778 022 4;
  • 58) 0.653 778 022 4 × 2 = 1 + 0.307 556 044 8;
  • 59) 0.307 556 044 8 × 2 = 0 + 0.615 112 089 6;
  • 60) 0.615 112 089 6 × 2 = 1 + 0.230 224 179 2;
  • 61) 0.230 224 179 2 × 2 = 0 + 0.460 448 358 4;
  • 62) 0.460 448 358 4 × 2 = 0 + 0.920 896 716 8;
  • 63) 0.920 896 716 8 × 2 = 1 + 0.841 793 433 6;
  • 64) 0.841 793 433 6 × 2 = 1 + 0.683 586 867 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:


0.000 282 009 2(10) =


0.0000 0000 0001 0010 0111 1011 0101 0100 0100 1010 1000 1010 0011 0000 1101 0011(2)

6. Positive number before normalization:

0.000 282 009 2(10) =


0.0000 0000 0001 0010 0111 1011 0101 0100 0100 1010 1000 1010 0011 0000 1101 0011(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:


0.000 282 009 2(10) =


0.0000 0000 0001 0010 0111 1011 0101 0100 0100 1010 1000 1010 0011 0000 1101 0011(2) =


0.0000 0000 0001 0010 0111 1011 0101 0100 0100 1010 1000 1010 0011 0000 1101 0011(2) × 20 =


1.0010 0111 1011 0101 0100 0100 1010 1000 1010 0011 0000 1101 0011(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 0101 0100 0100 1010 1000 1010 0011 0000 1101 0011


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 0101 0100 0100 1010 1000 1010 0011 0000 1101 0011 =


0010 0111 1011 0101 0100 0100 1010 1000 1010 0011 0000 1101 0011


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 0101 0100 0100 1010 1000 1010 0011 0000 1101 0011


Decimal number -0.000 282 009 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0101 0100 0100 1010 1000 1010 0011 0000 1101 0011


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