-0.000 282 006 486 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 486(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
-0.000 282 006 486(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:

|-0.000 282 006 486| = 0.000 282 006 486


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: 0.000 282 006 486.

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) 0.000 282 006 486 × 2 = 0 + 0.000 564 012 972;
  • 2) 0.000 564 012 972 × 2 = 0 + 0.001 128 025 944;
  • 3) 0.001 128 025 944 × 2 = 0 + 0.002 256 051 888;
  • 4) 0.002 256 051 888 × 2 = 0 + 0.004 512 103 776;
  • 5) 0.004 512 103 776 × 2 = 0 + 0.009 024 207 552;
  • 6) 0.009 024 207 552 × 2 = 0 + 0.018 048 415 104;
  • 7) 0.018 048 415 104 × 2 = 0 + 0.036 096 830 208;
  • 8) 0.036 096 830 208 × 2 = 0 + 0.072 193 660 416;
  • 9) 0.072 193 660 416 × 2 = 0 + 0.144 387 320 832;
  • 10) 0.144 387 320 832 × 2 = 0 + 0.288 774 641 664;
  • 11) 0.288 774 641 664 × 2 = 0 + 0.577 549 283 328;
  • 12) 0.577 549 283 328 × 2 = 1 + 0.155 098 566 656;
  • 13) 0.155 098 566 656 × 2 = 0 + 0.310 197 133 312;
  • 14) 0.310 197 133 312 × 2 = 0 + 0.620 394 266 624;
  • 15) 0.620 394 266 624 × 2 = 1 + 0.240 788 533 248;
  • 16) 0.240 788 533 248 × 2 = 0 + 0.481 577 066 496;
  • 17) 0.481 577 066 496 × 2 = 0 + 0.963 154 132 992;
  • 18) 0.963 154 132 992 × 2 = 1 + 0.926 308 265 984;
  • 19) 0.926 308 265 984 × 2 = 1 + 0.852 616 531 968;
  • 20) 0.852 616 531 968 × 2 = 1 + 0.705 233 063 936;
  • 21) 0.705 233 063 936 × 2 = 1 + 0.410 466 127 872;
  • 22) 0.410 466 127 872 × 2 = 0 + 0.820 932 255 744;
  • 23) 0.820 932 255 744 × 2 = 1 + 0.641 864 511 488;
  • 24) 0.641 864 511 488 × 2 = 1 + 0.283 729 022 976;
  • 25) 0.283 729 022 976 × 2 = 0 + 0.567 458 045 952;
  • 26) 0.567 458 045 952 × 2 = 1 + 0.134 916 091 904;
  • 27) 0.134 916 091 904 × 2 = 0 + 0.269 832 183 808;
  • 28) 0.269 832 183 808 × 2 = 0 + 0.539 664 367 616;
  • 29) 0.539 664 367 616 × 2 = 1 + 0.079 328 735 232;
  • 30) 0.079 328 735 232 × 2 = 0 + 0.158 657 470 464;
  • 31) 0.158 657 470 464 × 2 = 0 + 0.317 314 940 928;
  • 32) 0.317 314 940 928 × 2 = 0 + 0.634 629 881 856;
  • 33) 0.634 629 881 856 × 2 = 1 + 0.269 259 763 712;
  • 34) 0.269 259 763 712 × 2 = 0 + 0.538 519 527 424;
  • 35) 0.538 519 527 424 × 2 = 1 + 0.077 039 054 848;
  • 36) 0.077 039 054 848 × 2 = 0 + 0.154 078 109 696;
  • 37) 0.154 078 109 696 × 2 = 0 + 0.308 156 219 392;
  • 38) 0.308 156 219 392 × 2 = 0 + 0.616 312 438 784;
  • 39) 0.616 312 438 784 × 2 = 1 + 0.232 624 877 568;
  • 40) 0.232 624 877 568 × 2 = 0 + 0.465 249 755 136;
  • 41) 0.465 249 755 136 × 2 = 0 + 0.930 499 510 272;
  • 42) 0.930 499 510 272 × 2 = 1 + 0.860 999 020 544;
  • 43) 0.860 999 020 544 × 2 = 1 + 0.721 998 041 088;
  • 44) 0.721 998 041 088 × 2 = 1 + 0.443 996 082 176;
  • 45) 0.443 996 082 176 × 2 = 0 + 0.887 992 164 352;
  • 46) 0.887 992 164 352 × 2 = 1 + 0.775 984 328 704;
  • 47) 0.775 984 328 704 × 2 = 1 + 0.551 968 657 408;
  • 48) 0.551 968 657 408 × 2 = 1 + 0.103 937 314 816;
  • 49) 0.103 937 314 816 × 2 = 0 + 0.207 874 629 632;
  • 50) 0.207 874 629 632 × 2 = 0 + 0.415 749 259 264;
  • 51) 0.415 749 259 264 × 2 = 0 + 0.831 498 518 528;
  • 52) 0.831 498 518 528 × 2 = 1 + 0.662 997 037 056;
  • 53) 0.662 997 037 056 × 2 = 1 + 0.325 994 074 112;
  • 54) 0.325 994 074 112 × 2 = 0 + 0.651 988 148 224;
  • 55) 0.651 988 148 224 × 2 = 1 + 0.303 976 296 448;
  • 56) 0.303 976 296 448 × 2 = 0 + 0.607 952 592 896;
  • 57) 0.607 952 592 896 × 2 = 1 + 0.215 905 185 792;
  • 58) 0.215 905 185 792 × 2 = 0 + 0.431 810 371 584;
  • 59) 0.431 810 371 584 × 2 = 0 + 0.863 620 743 168;
  • 60) 0.863 620 743 168 × 2 = 1 + 0.727 241 486 336;
  • 61) 0.727 241 486 336 × 2 = 1 + 0.454 482 972 672;
  • 62) 0.454 482 972 672 × 2 = 0 + 0.908 965 945 344;
  • 63) 0.908 965 945 344 × 2 = 1 + 0.817 931 890 688;
  • 64) 0.817 931 890 688 × 2 = 1 + 0.635 863 781 376;

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:


0.000 282 006 486(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 1010 0010 0111 0111 0001 1010 1001 1011(2)

6. Positive number before normalization:

0.000 282 006 486(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 1010 0010 0111 0111 0001 1010 1001 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:


0.000 282 006 486(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 1010 0010 0111 0111 0001 1010 1001 1011(2) =


0.0000 0000 0001 0010 0111 1011 0100 1000 1010 0010 0111 0111 0001 1010 1001 1011(2) × 20 =


1.0010 0111 1011 0100 1000 1010 0010 0111 0111 0001 1010 1001 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 1000 1010 0010 0111 0111 0001 1010 1001 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 1000 1010 0010 0111 0111 0001 1010 1001 1011 =


0010 0111 1011 0100 1000 1010 0010 0111 0111 0001 1010 1001 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 1000 1010 0010 0111 0111 0001 1010 1001 1011


Decimal number -0.000 282 006 486 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 1000 1010 0010 0111 0111 0001 1010 1001 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