-0.000 282 005 914 315 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 914 315(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
-0.000 282 005 914 315(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:

|-0.000 282 005 914 315| = 0.000 282 005 914 315


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: 0.000 282 005 914 315.

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) 0.000 282 005 914 315 × 2 = 0 + 0.000 564 011 828 63;
  • 2) 0.000 564 011 828 63 × 2 = 0 + 0.001 128 023 657 26;
  • 3) 0.001 128 023 657 26 × 2 = 0 + 0.002 256 047 314 52;
  • 4) 0.002 256 047 314 52 × 2 = 0 + 0.004 512 094 629 04;
  • 5) 0.004 512 094 629 04 × 2 = 0 + 0.009 024 189 258 08;
  • 6) 0.009 024 189 258 08 × 2 = 0 + 0.018 048 378 516 16;
  • 7) 0.018 048 378 516 16 × 2 = 0 + 0.036 096 757 032 32;
  • 8) 0.036 096 757 032 32 × 2 = 0 + 0.072 193 514 064 64;
  • 9) 0.072 193 514 064 64 × 2 = 0 + 0.144 387 028 129 28;
  • 10) 0.144 387 028 129 28 × 2 = 0 + 0.288 774 056 258 56;
  • 11) 0.288 774 056 258 56 × 2 = 0 + 0.577 548 112 517 12;
  • 12) 0.577 548 112 517 12 × 2 = 1 + 0.155 096 225 034 24;
  • 13) 0.155 096 225 034 24 × 2 = 0 + 0.310 192 450 068 48;
  • 14) 0.310 192 450 068 48 × 2 = 0 + 0.620 384 900 136 96;
  • 15) 0.620 384 900 136 96 × 2 = 1 + 0.240 769 800 273 92;
  • 16) 0.240 769 800 273 92 × 2 = 0 + 0.481 539 600 547 84;
  • 17) 0.481 539 600 547 84 × 2 = 0 + 0.963 079 201 095 68;
  • 18) 0.963 079 201 095 68 × 2 = 1 + 0.926 158 402 191 36;
  • 19) 0.926 158 402 191 36 × 2 = 1 + 0.852 316 804 382 72;
  • 20) 0.852 316 804 382 72 × 2 = 1 + 0.704 633 608 765 44;
  • 21) 0.704 633 608 765 44 × 2 = 1 + 0.409 267 217 530 88;
  • 22) 0.409 267 217 530 88 × 2 = 0 + 0.818 534 435 061 76;
  • 23) 0.818 534 435 061 76 × 2 = 1 + 0.637 068 870 123 52;
  • 24) 0.637 068 870 123 52 × 2 = 1 + 0.274 137 740 247 04;
  • 25) 0.274 137 740 247 04 × 2 = 0 + 0.548 275 480 494 08;
  • 26) 0.548 275 480 494 08 × 2 = 1 + 0.096 550 960 988 16;
  • 27) 0.096 550 960 988 16 × 2 = 0 + 0.193 101 921 976 32;
  • 28) 0.193 101 921 976 32 × 2 = 0 + 0.386 203 843 952 64;
  • 29) 0.386 203 843 952 64 × 2 = 0 + 0.772 407 687 905 28;
  • 30) 0.772 407 687 905 28 × 2 = 1 + 0.544 815 375 810 56;
  • 31) 0.544 815 375 810 56 × 2 = 1 + 0.089 630 751 621 12;
  • 32) 0.089 630 751 621 12 × 2 = 0 + 0.179 261 503 242 24;
  • 33) 0.179 261 503 242 24 × 2 = 0 + 0.358 523 006 484 48;
  • 34) 0.358 523 006 484 48 × 2 = 0 + 0.717 046 012 968 96;
  • 35) 0.717 046 012 968 96 × 2 = 1 + 0.434 092 025 937 92;
  • 36) 0.434 092 025 937 92 × 2 = 0 + 0.868 184 051 875 84;
  • 37) 0.868 184 051 875 84 × 2 = 1 + 0.736 368 103 751 68;
  • 38) 0.736 368 103 751 68 × 2 = 1 + 0.472 736 207 503 36;
  • 39) 0.472 736 207 503 36 × 2 = 0 + 0.945 472 415 006 72;
  • 40) 0.945 472 415 006 72 × 2 = 1 + 0.890 944 830 013 44;
  • 41) 0.890 944 830 013 44 × 2 = 1 + 0.781 889 660 026 88;
  • 42) 0.781 889 660 026 88 × 2 = 1 + 0.563 779 320 053 76;
  • 43) 0.563 779 320 053 76 × 2 = 1 + 0.127 558 640 107 52;
  • 44) 0.127 558 640 107 52 × 2 = 0 + 0.255 117 280 215 04;
  • 45) 0.255 117 280 215 04 × 2 = 0 + 0.510 234 560 430 08;
  • 46) 0.510 234 560 430 08 × 2 = 1 + 0.020 469 120 860 16;
  • 47) 0.020 469 120 860 16 × 2 = 0 + 0.040 938 241 720 32;
  • 48) 0.040 938 241 720 32 × 2 = 0 + 0.081 876 483 440 64;
  • 49) 0.081 876 483 440 64 × 2 = 0 + 0.163 752 966 881 28;
  • 50) 0.163 752 966 881 28 × 2 = 0 + 0.327 505 933 762 56;
  • 51) 0.327 505 933 762 56 × 2 = 0 + 0.655 011 867 525 12;
  • 52) 0.655 011 867 525 12 × 2 = 1 + 0.310 023 735 050 24;
  • 53) 0.310 023 735 050 24 × 2 = 0 + 0.620 047 470 100 48;
  • 54) 0.620 047 470 100 48 × 2 = 1 + 0.240 094 940 200 96;
  • 55) 0.240 094 940 200 96 × 2 = 0 + 0.480 189 880 401 92;
  • 56) 0.480 189 880 401 92 × 2 = 0 + 0.960 379 760 803 84;
  • 57) 0.960 379 760 803 84 × 2 = 1 + 0.920 759 521 607 68;
  • 58) 0.920 759 521 607 68 × 2 = 1 + 0.841 519 043 215 36;
  • 59) 0.841 519 043 215 36 × 2 = 1 + 0.683 038 086 430 72;
  • 60) 0.683 038 086 430 72 × 2 = 1 + 0.366 076 172 861 44;
  • 61) 0.366 076 172 861 44 × 2 = 0 + 0.732 152 345 722 88;
  • 62) 0.732 152 345 722 88 × 2 = 1 + 0.464 304 691 445 76;
  • 63) 0.464 304 691 445 76 × 2 = 0 + 0.928 609 382 891 52;
  • 64) 0.928 609 382 891 52 × 2 = 1 + 0.857 218 765 783 04;

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:


0.000 282 005 914 315(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1110 0100 0001 0100 1111 0101(2)

6. Positive number before normalization:

0.000 282 005 914 315(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1110 0100 0001 0100 1111 0101(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:


0.000 282 005 914 315(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1110 0100 0001 0100 1111 0101(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1110 0100 0001 0100 1111 0101(2) × 20 =


1.0010 0111 1011 0100 0110 0010 1101 1110 0100 0001 0100 1111 0101(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 0010 1101 1110 0100 0001 0100 1111 0101


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 0010 1101 1110 0100 0001 0100 1111 0101 =


0010 0111 1011 0100 0110 0010 1101 1110 0100 0001 0100 1111 0101


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 0010 1101 1110 0100 0001 0100 1111 0101


Decimal number -0.000 282 005 914 315 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0010 1101 1110 0100 0001 0100 1111 0101


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