-0.000 282 005 879 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 879 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
-0.000 282 005 879 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:

|-0.000 282 005 879 2| = 0.000 282 005 879 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: 0.000 282 005 879 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) 0.000 282 005 879 2 × 2 = 0 + 0.000 564 011 758 4;
  • 2) 0.000 564 011 758 4 × 2 = 0 + 0.001 128 023 516 8;
  • 3) 0.001 128 023 516 8 × 2 = 0 + 0.002 256 047 033 6;
  • 4) 0.002 256 047 033 6 × 2 = 0 + 0.004 512 094 067 2;
  • 5) 0.004 512 094 067 2 × 2 = 0 + 0.009 024 188 134 4;
  • 6) 0.009 024 188 134 4 × 2 = 0 + 0.018 048 376 268 8;
  • 7) 0.018 048 376 268 8 × 2 = 0 + 0.036 096 752 537 6;
  • 8) 0.036 096 752 537 6 × 2 = 0 + 0.072 193 505 075 2;
  • 9) 0.072 193 505 075 2 × 2 = 0 + 0.144 387 010 150 4;
  • 10) 0.144 387 010 150 4 × 2 = 0 + 0.288 774 020 300 8;
  • 11) 0.288 774 020 300 8 × 2 = 0 + 0.577 548 040 601 6;
  • 12) 0.577 548 040 601 6 × 2 = 1 + 0.155 096 081 203 2;
  • 13) 0.155 096 081 203 2 × 2 = 0 + 0.310 192 162 406 4;
  • 14) 0.310 192 162 406 4 × 2 = 0 + 0.620 384 324 812 8;
  • 15) 0.620 384 324 812 8 × 2 = 1 + 0.240 768 649 625 6;
  • 16) 0.240 768 649 625 6 × 2 = 0 + 0.481 537 299 251 2;
  • 17) 0.481 537 299 251 2 × 2 = 0 + 0.963 074 598 502 4;
  • 18) 0.963 074 598 502 4 × 2 = 1 + 0.926 149 197 004 8;
  • 19) 0.926 149 197 004 8 × 2 = 1 + 0.852 298 394 009 6;
  • 20) 0.852 298 394 009 6 × 2 = 1 + 0.704 596 788 019 2;
  • 21) 0.704 596 788 019 2 × 2 = 1 + 0.409 193 576 038 4;
  • 22) 0.409 193 576 038 4 × 2 = 0 + 0.818 387 152 076 8;
  • 23) 0.818 387 152 076 8 × 2 = 1 + 0.636 774 304 153 6;
  • 24) 0.636 774 304 153 6 × 2 = 1 + 0.273 548 608 307 2;
  • 25) 0.273 548 608 307 2 × 2 = 0 + 0.547 097 216 614 4;
  • 26) 0.547 097 216 614 4 × 2 = 1 + 0.094 194 433 228 8;
  • 27) 0.094 194 433 228 8 × 2 = 0 + 0.188 388 866 457 6;
  • 28) 0.188 388 866 457 6 × 2 = 0 + 0.376 777 732 915 2;
  • 29) 0.376 777 732 915 2 × 2 = 0 + 0.753 555 465 830 4;
  • 30) 0.753 555 465 830 4 × 2 = 1 + 0.507 110 931 660 8;
  • 31) 0.507 110 931 660 8 × 2 = 1 + 0.014 221 863 321 6;
  • 32) 0.014 221 863 321 6 × 2 = 0 + 0.028 443 726 643 2;
  • 33) 0.028 443 726 643 2 × 2 = 0 + 0.056 887 453 286 4;
  • 34) 0.056 887 453 286 4 × 2 = 0 + 0.113 774 906 572 8;
  • 35) 0.113 774 906 572 8 × 2 = 0 + 0.227 549 813 145 6;
  • 36) 0.227 549 813 145 6 × 2 = 0 + 0.455 099 626 291 2;
  • 37) 0.455 099 626 291 2 × 2 = 0 + 0.910 199 252 582 4;
  • 38) 0.910 199 252 582 4 × 2 = 1 + 0.820 398 505 164 8;
  • 39) 0.820 398 505 164 8 × 2 = 1 + 0.640 797 010 329 6;
  • 40) 0.640 797 010 329 6 × 2 = 1 + 0.281 594 020 659 2;
  • 41) 0.281 594 020 659 2 × 2 = 0 + 0.563 188 041 318 4;
  • 42) 0.563 188 041 318 4 × 2 = 1 + 0.126 376 082 636 8;
  • 43) 0.126 376 082 636 8 × 2 = 0 + 0.252 752 165 273 6;
  • 44) 0.252 752 165 273 6 × 2 = 0 + 0.505 504 330 547 2;
  • 45) 0.505 504 330 547 2 × 2 = 1 + 0.011 008 661 094 4;
  • 46) 0.011 008 661 094 4 × 2 = 0 + 0.022 017 322 188 8;
  • 47) 0.022 017 322 188 8 × 2 = 0 + 0.044 034 644 377 6;
  • 48) 0.044 034 644 377 6 × 2 = 0 + 0.088 069 288 755 2;
  • 49) 0.088 069 288 755 2 × 2 = 0 + 0.176 138 577 510 4;
  • 50) 0.176 138 577 510 4 × 2 = 0 + 0.352 277 155 020 8;
  • 51) 0.352 277 155 020 8 × 2 = 0 + 0.704 554 310 041 6;
  • 52) 0.704 554 310 041 6 × 2 = 1 + 0.409 108 620 083 2;
  • 53) 0.409 108 620 083 2 × 2 = 0 + 0.818 217 240 166 4;
  • 54) 0.818 217 240 166 4 × 2 = 1 + 0.636 434 480 332 8;
  • 55) 0.636 434 480 332 8 × 2 = 1 + 0.272 868 960 665 6;
  • 56) 0.272 868 960 665 6 × 2 = 0 + 0.545 737 921 331 2;
  • 57) 0.545 737 921 331 2 × 2 = 1 + 0.091 475 842 662 4;
  • 58) 0.091 475 842 662 4 × 2 = 0 + 0.182 951 685 324 8;
  • 59) 0.182 951 685 324 8 × 2 = 0 + 0.365 903 370 649 6;
  • 60) 0.365 903 370 649 6 × 2 = 0 + 0.731 806 741 299 2;
  • 61) 0.731 806 741 299 2 × 2 = 1 + 0.463 613 482 598 4;
  • 62) 0.463 613 482 598 4 × 2 = 0 + 0.927 226 965 196 8;
  • 63) 0.927 226 965 196 8 × 2 = 1 + 0.854 453 930 393 6;
  • 64) 0.854 453 930 393 6 × 2 = 1 + 0.708 907 860 787 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:


0.000 282 005 879 2(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 0111 0100 1000 0001 0110 1000 1011(2)

6. Positive number before normalization:

0.000 282 005 879 2(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 0111 0100 1000 0001 0110 1000 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:


0.000 282 005 879 2(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 0111 0100 1000 0001 0110 1000 1011(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 0111 0100 1000 0001 0110 1000 1011(2) × 20 =


1.0010 0111 1011 0100 0110 0000 0111 0100 1000 0001 0110 1000 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 0100 0110 0000 0111 0100 1000 0001 0110 1000 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 0100 0110 0000 0111 0100 1000 0001 0110 1000 1011 =


0010 0111 1011 0100 0110 0000 0111 0100 1000 0001 0110 1000 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 0100 0110 0000 0111 0100 1000 0001 0110 1000 1011


Decimal number -0.000 282 005 879 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0000 0111 0100 1000 0001 0110 1000 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