-0.000 282 005 776 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 776(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
-0.000 282 005 776(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:

|-0.000 282 005 776| = 0.000 282 005 776


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: 0.000 282 005 776.

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) 0.000 282 005 776 × 2 = 0 + 0.000 564 011 552;
  • 2) 0.000 564 011 552 × 2 = 0 + 0.001 128 023 104;
  • 3) 0.001 128 023 104 × 2 = 0 + 0.002 256 046 208;
  • 4) 0.002 256 046 208 × 2 = 0 + 0.004 512 092 416;
  • 5) 0.004 512 092 416 × 2 = 0 + 0.009 024 184 832;
  • 6) 0.009 024 184 832 × 2 = 0 + 0.018 048 369 664;
  • 7) 0.018 048 369 664 × 2 = 0 + 0.036 096 739 328;
  • 8) 0.036 096 739 328 × 2 = 0 + 0.072 193 478 656;
  • 9) 0.072 193 478 656 × 2 = 0 + 0.144 386 957 312;
  • 10) 0.144 386 957 312 × 2 = 0 + 0.288 773 914 624;
  • 11) 0.288 773 914 624 × 2 = 0 + 0.577 547 829 248;
  • 12) 0.577 547 829 248 × 2 = 1 + 0.155 095 658 496;
  • 13) 0.155 095 658 496 × 2 = 0 + 0.310 191 316 992;
  • 14) 0.310 191 316 992 × 2 = 0 + 0.620 382 633 984;
  • 15) 0.620 382 633 984 × 2 = 1 + 0.240 765 267 968;
  • 16) 0.240 765 267 968 × 2 = 0 + 0.481 530 535 936;
  • 17) 0.481 530 535 936 × 2 = 0 + 0.963 061 071 872;
  • 18) 0.963 061 071 872 × 2 = 1 + 0.926 122 143 744;
  • 19) 0.926 122 143 744 × 2 = 1 + 0.852 244 287 488;
  • 20) 0.852 244 287 488 × 2 = 1 + 0.704 488 574 976;
  • 21) 0.704 488 574 976 × 2 = 1 + 0.408 977 149 952;
  • 22) 0.408 977 149 952 × 2 = 0 + 0.817 954 299 904;
  • 23) 0.817 954 299 904 × 2 = 1 + 0.635 908 599 808;
  • 24) 0.635 908 599 808 × 2 = 1 + 0.271 817 199 616;
  • 25) 0.271 817 199 616 × 2 = 0 + 0.543 634 399 232;
  • 26) 0.543 634 399 232 × 2 = 1 + 0.087 268 798 464;
  • 27) 0.087 268 798 464 × 2 = 0 + 0.174 537 596 928;
  • 28) 0.174 537 596 928 × 2 = 0 + 0.349 075 193 856;
  • 29) 0.349 075 193 856 × 2 = 0 + 0.698 150 387 712;
  • 30) 0.698 150 387 712 × 2 = 1 + 0.396 300 775 424;
  • 31) 0.396 300 775 424 × 2 = 0 + 0.792 601 550 848;
  • 32) 0.792 601 550 848 × 2 = 1 + 0.585 203 101 696;
  • 33) 0.585 203 101 696 × 2 = 1 + 0.170 406 203 392;
  • 34) 0.170 406 203 392 × 2 = 0 + 0.340 812 406 784;
  • 35) 0.340 812 406 784 × 2 = 0 + 0.681 624 813 568;
  • 36) 0.681 624 813 568 × 2 = 1 + 0.363 249 627 136;
  • 37) 0.363 249 627 136 × 2 = 0 + 0.726 499 254 272;
  • 38) 0.726 499 254 272 × 2 = 1 + 0.452 998 508 544;
  • 39) 0.452 998 508 544 × 2 = 0 + 0.905 997 017 088;
  • 40) 0.905 997 017 088 × 2 = 1 + 0.811 994 034 176;
  • 41) 0.811 994 034 176 × 2 = 1 + 0.623 988 068 352;
  • 42) 0.623 988 068 352 × 2 = 1 + 0.247 976 136 704;
  • 43) 0.247 976 136 704 × 2 = 0 + 0.495 952 273 408;
  • 44) 0.495 952 273 408 × 2 = 0 + 0.991 904 546 816;
  • 45) 0.991 904 546 816 × 2 = 1 + 0.983 809 093 632;
  • 46) 0.983 809 093 632 × 2 = 1 + 0.967 618 187 264;
  • 47) 0.967 618 187 264 × 2 = 1 + 0.935 236 374 528;
  • 48) 0.935 236 374 528 × 2 = 1 + 0.870 472 749 056;
  • 49) 0.870 472 749 056 × 2 = 1 + 0.740 945 498 112;
  • 50) 0.740 945 498 112 × 2 = 1 + 0.481 890 996 224;
  • 51) 0.481 890 996 224 × 2 = 0 + 0.963 781 992 448;
  • 52) 0.963 781 992 448 × 2 = 1 + 0.927 563 984 896;
  • 53) 0.927 563 984 896 × 2 = 1 + 0.855 127 969 792;
  • 54) 0.855 127 969 792 × 2 = 1 + 0.710 255 939 584;
  • 55) 0.710 255 939 584 × 2 = 1 + 0.420 511 879 168;
  • 56) 0.420 511 879 168 × 2 = 0 + 0.841 023 758 336;
  • 57) 0.841 023 758 336 × 2 = 1 + 0.682 047 516 672;
  • 58) 0.682 047 516 672 × 2 = 1 + 0.364 095 033 344;
  • 59) 0.364 095 033 344 × 2 = 0 + 0.728 190 066 688;
  • 60) 0.728 190 066 688 × 2 = 1 + 0.456 380 133 376;
  • 61) 0.456 380 133 376 × 2 = 0 + 0.912 760 266 752;
  • 62) 0.912 760 266 752 × 2 = 1 + 0.825 520 533 504;
  • 63) 0.825 520 533 504 × 2 = 1 + 0.651 041 067 008;
  • 64) 0.651 041 067 008 × 2 = 1 + 0.302 082 134 016;

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:


0.000 282 005 776(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1001 0101 1100 1111 1101 1110 1101 0111(2)

6. Positive number before normalization:

0.000 282 005 776(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1001 0101 1100 1111 1101 1110 1101 0111(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:


0.000 282 005 776(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1001 0101 1100 1111 1101 1110 1101 0111(2) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1001 0101 1100 1111 1101 1110 1101 0111(2) × 20 =


1.0010 0111 1011 0100 0101 1001 0101 1100 1111 1101 1110 1101 0111(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 0101 1001 0101 1100 1111 1101 1110 1101 0111


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 0101 1001 0101 1100 1111 1101 1110 1101 0111 =


0010 0111 1011 0100 0101 1001 0101 1100 1111 1101 1110 1101 0111


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 0101 1001 0101 1100 1111 1101 1110 1101 0111


Decimal number -0.000 282 005 776 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0101 1001 0101 1100 1111 1101 1110 1101 0111


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