-0.000 282 007 1 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 007 1(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
-0.000 282 007 1(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:

|-0.000 282 007 1| = 0.000 282 007 1


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: 0.000 282 007 1.

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) 0.000 282 007 1 × 2 = 0 + 0.000 564 014 2;
  • 2) 0.000 564 014 2 × 2 = 0 + 0.001 128 028 4;
  • 3) 0.001 128 028 4 × 2 = 0 + 0.002 256 056 8;
  • 4) 0.002 256 056 8 × 2 = 0 + 0.004 512 113 6;
  • 5) 0.004 512 113 6 × 2 = 0 + 0.009 024 227 2;
  • 6) 0.009 024 227 2 × 2 = 0 + 0.018 048 454 4;
  • 7) 0.018 048 454 4 × 2 = 0 + 0.036 096 908 8;
  • 8) 0.036 096 908 8 × 2 = 0 + 0.072 193 817 6;
  • 9) 0.072 193 817 6 × 2 = 0 + 0.144 387 635 2;
  • 10) 0.144 387 635 2 × 2 = 0 + 0.288 775 270 4;
  • 11) 0.288 775 270 4 × 2 = 0 + 0.577 550 540 8;
  • 12) 0.577 550 540 8 × 2 = 1 + 0.155 101 081 6;
  • 13) 0.155 101 081 6 × 2 = 0 + 0.310 202 163 2;
  • 14) 0.310 202 163 2 × 2 = 0 + 0.620 404 326 4;
  • 15) 0.620 404 326 4 × 2 = 1 + 0.240 808 652 8;
  • 16) 0.240 808 652 8 × 2 = 0 + 0.481 617 305 6;
  • 17) 0.481 617 305 6 × 2 = 0 + 0.963 234 611 2;
  • 18) 0.963 234 611 2 × 2 = 1 + 0.926 469 222 4;
  • 19) 0.926 469 222 4 × 2 = 1 + 0.852 938 444 8;
  • 20) 0.852 938 444 8 × 2 = 1 + 0.705 876 889 6;
  • 21) 0.705 876 889 6 × 2 = 1 + 0.411 753 779 2;
  • 22) 0.411 753 779 2 × 2 = 0 + 0.823 507 558 4;
  • 23) 0.823 507 558 4 × 2 = 1 + 0.647 015 116 8;
  • 24) 0.647 015 116 8 × 2 = 1 + 0.294 030 233 6;
  • 25) 0.294 030 233 6 × 2 = 0 + 0.588 060 467 2;
  • 26) 0.588 060 467 2 × 2 = 1 + 0.176 120 934 4;
  • 27) 0.176 120 934 4 × 2 = 0 + 0.352 241 868 8;
  • 28) 0.352 241 868 8 × 2 = 0 + 0.704 483 737 6;
  • 29) 0.704 483 737 6 × 2 = 1 + 0.408 967 475 2;
  • 30) 0.408 967 475 2 × 2 = 0 + 0.817 934 950 4;
  • 31) 0.817 934 950 4 × 2 = 1 + 0.635 869 900 8;
  • 32) 0.635 869 900 8 × 2 = 1 + 0.271 739 801 6;
  • 33) 0.271 739 801 6 × 2 = 0 + 0.543 479 603 2;
  • 34) 0.543 479 603 2 × 2 = 1 + 0.086 959 206 4;
  • 35) 0.086 959 206 4 × 2 = 0 + 0.173 918 412 8;
  • 36) 0.173 918 412 8 × 2 = 0 + 0.347 836 825 6;
  • 37) 0.347 836 825 6 × 2 = 0 + 0.695 673 651 2;
  • 38) 0.695 673 651 2 × 2 = 1 + 0.391 347 302 4;
  • 39) 0.391 347 302 4 × 2 = 0 + 0.782 694 604 8;
  • 40) 0.782 694 604 8 × 2 = 1 + 0.565 389 209 6;
  • 41) 0.565 389 209 6 × 2 = 1 + 0.130 778 419 2;
  • 42) 0.130 778 419 2 × 2 = 0 + 0.261 556 838 4;
  • 43) 0.261 556 838 4 × 2 = 0 + 0.523 113 676 8;
  • 44) 0.523 113 676 8 × 2 = 1 + 0.046 227 353 6;
  • 45) 0.046 227 353 6 × 2 = 0 + 0.092 454 707 2;
  • 46) 0.092 454 707 2 × 2 = 0 + 0.184 909 414 4;
  • 47) 0.184 909 414 4 × 2 = 0 + 0.369 818 828 8;
  • 48) 0.369 818 828 8 × 2 = 0 + 0.739 637 657 6;
  • 49) 0.739 637 657 6 × 2 = 1 + 0.479 275 315 2;
  • 50) 0.479 275 315 2 × 2 = 0 + 0.958 550 630 4;
  • 51) 0.958 550 630 4 × 2 = 1 + 0.917 101 260 8;
  • 52) 0.917 101 260 8 × 2 = 1 + 0.834 202 521 6;
  • 53) 0.834 202 521 6 × 2 = 1 + 0.668 405 043 2;
  • 54) 0.668 405 043 2 × 2 = 1 + 0.336 810 086 4;
  • 55) 0.336 810 086 4 × 2 = 0 + 0.673 620 172 8;
  • 56) 0.673 620 172 8 × 2 = 1 + 0.347 240 345 6;
  • 57) 0.347 240 345 6 × 2 = 0 + 0.694 480 691 2;
  • 58) 0.694 480 691 2 × 2 = 1 + 0.388 961 382 4;
  • 59) 0.388 961 382 4 × 2 = 0 + 0.777 922 764 8;
  • 60) 0.777 922 764 8 × 2 = 1 + 0.555 845 529 6;
  • 61) 0.555 845 529 6 × 2 = 1 + 0.111 691 059 2;
  • 62) 0.111 691 059 2 × 2 = 0 + 0.223 382 118 4;
  • 63) 0.223 382 118 4 × 2 = 0 + 0.446 764 236 8;
  • 64) 0.446 764 236 8 × 2 = 0 + 0.893 528 473 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:


0.000 282 007 1(10) =


0.0000 0000 0001 0010 0111 1011 0100 1011 0100 0101 1001 0000 1011 1101 0101 1000(2)

6. Positive number before normalization:

0.000 282 007 1(10) =


0.0000 0000 0001 0010 0111 1011 0100 1011 0100 0101 1001 0000 1011 1101 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:


0.000 282 007 1(10) =


0.0000 0000 0001 0010 0111 1011 0100 1011 0100 0101 1001 0000 1011 1101 0101 1000(2) =


0.0000 0000 0001 0010 0111 1011 0100 1011 0100 0101 1001 0000 1011 1101 0101 1000(2) × 20 =


1.0010 0111 1011 0100 1011 0100 0101 1001 0000 1011 1101 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 1011 0100 0101 1001 0000 1011 1101 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 1011 0100 0101 1001 0000 1011 1101 0101 1000 =


0010 0111 1011 0100 1011 0100 0101 1001 0000 1011 1101 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 1011 0100 0101 1001 0000 1011 1101 0101 1000


Decimal number -0.000 282 007 1 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 1011 0100 0101 1001 0000 1011 1101 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