-0.000 282 004 8 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 004 8(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
-0.000 282 004 8(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:

|-0.000 282 004 8| = 0.000 282 004 8


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: 0.000 282 004 8.

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) 0.000 282 004 8 × 2 = 0 + 0.000 564 009 6;
  • 2) 0.000 564 009 6 × 2 = 0 + 0.001 128 019 2;
  • 3) 0.001 128 019 2 × 2 = 0 + 0.002 256 038 4;
  • 4) 0.002 256 038 4 × 2 = 0 + 0.004 512 076 8;
  • 5) 0.004 512 076 8 × 2 = 0 + 0.009 024 153 6;
  • 6) 0.009 024 153 6 × 2 = 0 + 0.018 048 307 2;
  • 7) 0.018 048 307 2 × 2 = 0 + 0.036 096 614 4;
  • 8) 0.036 096 614 4 × 2 = 0 + 0.072 193 228 8;
  • 9) 0.072 193 228 8 × 2 = 0 + 0.144 386 457 6;
  • 10) 0.144 386 457 6 × 2 = 0 + 0.288 772 915 2;
  • 11) 0.288 772 915 2 × 2 = 0 + 0.577 545 830 4;
  • 12) 0.577 545 830 4 × 2 = 1 + 0.155 091 660 8;
  • 13) 0.155 091 660 8 × 2 = 0 + 0.310 183 321 6;
  • 14) 0.310 183 321 6 × 2 = 0 + 0.620 366 643 2;
  • 15) 0.620 366 643 2 × 2 = 1 + 0.240 733 286 4;
  • 16) 0.240 733 286 4 × 2 = 0 + 0.481 466 572 8;
  • 17) 0.481 466 572 8 × 2 = 0 + 0.962 933 145 6;
  • 18) 0.962 933 145 6 × 2 = 1 + 0.925 866 291 2;
  • 19) 0.925 866 291 2 × 2 = 1 + 0.851 732 582 4;
  • 20) 0.851 732 582 4 × 2 = 1 + 0.703 465 164 8;
  • 21) 0.703 465 164 8 × 2 = 1 + 0.406 930 329 6;
  • 22) 0.406 930 329 6 × 2 = 0 + 0.813 860 659 2;
  • 23) 0.813 860 659 2 × 2 = 1 + 0.627 721 318 4;
  • 24) 0.627 721 318 4 × 2 = 1 + 0.255 442 636 8;
  • 25) 0.255 442 636 8 × 2 = 0 + 0.510 885 273 6;
  • 26) 0.510 885 273 6 × 2 = 1 + 0.021 770 547 2;
  • 27) 0.021 770 547 2 × 2 = 0 + 0.043 541 094 4;
  • 28) 0.043 541 094 4 × 2 = 0 + 0.087 082 188 8;
  • 29) 0.087 082 188 8 × 2 = 0 + 0.174 164 377 6;
  • 30) 0.174 164 377 6 × 2 = 0 + 0.348 328 755 2;
  • 31) 0.348 328 755 2 × 2 = 0 + 0.696 657 510 4;
  • 32) 0.696 657 510 4 × 2 = 1 + 0.393 315 020 8;
  • 33) 0.393 315 020 8 × 2 = 0 + 0.786 630 041 6;
  • 34) 0.786 630 041 6 × 2 = 1 + 0.573 260 083 2;
  • 35) 0.573 260 083 2 × 2 = 1 + 0.146 520 166 4;
  • 36) 0.146 520 166 4 × 2 = 0 + 0.293 040 332 8;
  • 37) 0.293 040 332 8 × 2 = 0 + 0.586 080 665 6;
  • 38) 0.586 080 665 6 × 2 = 1 + 0.172 161 331 2;
  • 39) 0.172 161 331 2 × 2 = 0 + 0.344 322 662 4;
  • 40) 0.344 322 662 4 × 2 = 0 + 0.688 645 324 8;
  • 41) 0.688 645 324 8 × 2 = 1 + 0.377 290 649 6;
  • 42) 0.377 290 649 6 × 2 = 0 + 0.754 581 299 2;
  • 43) 0.754 581 299 2 × 2 = 1 + 0.509 162 598 4;
  • 44) 0.509 162 598 4 × 2 = 1 + 0.018 325 196 8;
  • 45) 0.018 325 196 8 × 2 = 0 + 0.036 650 393 6;
  • 46) 0.036 650 393 6 × 2 = 0 + 0.073 300 787 2;
  • 47) 0.073 300 787 2 × 2 = 0 + 0.146 601 574 4;
  • 48) 0.146 601 574 4 × 2 = 0 + 0.293 203 148 8;
  • 49) 0.293 203 148 8 × 2 = 0 + 0.586 406 297 6;
  • 50) 0.586 406 297 6 × 2 = 1 + 0.172 812 595 2;
  • 51) 0.172 812 595 2 × 2 = 0 + 0.345 625 190 4;
  • 52) 0.345 625 190 4 × 2 = 0 + 0.691 250 380 8;
  • 53) 0.691 250 380 8 × 2 = 1 + 0.382 500 761 6;
  • 54) 0.382 500 761 6 × 2 = 0 + 0.765 001 523 2;
  • 55) 0.765 001 523 2 × 2 = 1 + 0.530 003 046 4;
  • 56) 0.530 003 046 4 × 2 = 1 + 0.060 006 092 8;
  • 57) 0.060 006 092 8 × 2 = 0 + 0.120 012 185 6;
  • 58) 0.120 012 185 6 × 2 = 0 + 0.240 024 371 2;
  • 59) 0.240 024 371 2 × 2 = 0 + 0.480 048 742 4;
  • 60) 0.480 048 742 4 × 2 = 0 + 0.960 097 484 8;
  • 61) 0.960 097 484 8 × 2 = 1 + 0.920 194 969 6;
  • 62) 0.920 194 969 6 × 2 = 1 + 0.840 389 939 2;
  • 63) 0.840 389 939 2 × 2 = 1 + 0.680 779 878 4;
  • 64) 0.680 779 878 4 × 2 = 1 + 0.361 559 756 8;

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:


0.000 282 004 8(10) =


0.0000 0000 0001 0010 0111 1011 0100 0001 0110 0100 1011 0000 0100 1011 0000 1111(2)

6. Positive number before normalization:

0.000 282 004 8(10) =


0.0000 0000 0001 0010 0111 1011 0100 0001 0110 0100 1011 0000 0100 1011 0000 1111(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:


0.000 282 004 8(10) =


0.0000 0000 0001 0010 0111 1011 0100 0001 0110 0100 1011 0000 0100 1011 0000 1111(2) =


0.0000 0000 0001 0010 0111 1011 0100 0001 0110 0100 1011 0000 0100 1011 0000 1111(2) × 20 =


1.0010 0111 1011 0100 0001 0110 0100 1011 0000 0100 1011 0000 1111(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 0001 0110 0100 1011 0000 0100 1011 0000 1111


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 0001 0110 0100 1011 0000 0100 1011 0000 1111 =


0010 0111 1011 0100 0001 0110 0100 1011 0000 0100 1011 0000 1111


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 0001 0110 0100 1011 0000 0100 1011 0000 1111


Decimal number -0.000 282 004 8 converted to 64 bit double precision IEEE 754 binary floating point representation:

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


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