-0.000 282 005 914 33 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 914 33(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 33(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 33| = 0.000 282 005 914 33


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 33.

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 33 × 2 = 0 + 0.000 564 011 828 66;
  • 2) 0.000 564 011 828 66 × 2 = 0 + 0.001 128 023 657 32;
  • 3) 0.001 128 023 657 32 × 2 = 0 + 0.002 256 047 314 64;
  • 4) 0.002 256 047 314 64 × 2 = 0 + 0.004 512 094 629 28;
  • 5) 0.004 512 094 629 28 × 2 = 0 + 0.009 024 189 258 56;
  • 6) 0.009 024 189 258 56 × 2 = 0 + 0.018 048 378 517 12;
  • 7) 0.018 048 378 517 12 × 2 = 0 + 0.036 096 757 034 24;
  • 8) 0.036 096 757 034 24 × 2 = 0 + 0.072 193 514 068 48;
  • 9) 0.072 193 514 068 48 × 2 = 0 + 0.144 387 028 136 96;
  • 10) 0.144 387 028 136 96 × 2 = 0 + 0.288 774 056 273 92;
  • 11) 0.288 774 056 273 92 × 2 = 0 + 0.577 548 112 547 84;
  • 12) 0.577 548 112 547 84 × 2 = 1 + 0.155 096 225 095 68;
  • 13) 0.155 096 225 095 68 × 2 = 0 + 0.310 192 450 191 36;
  • 14) 0.310 192 450 191 36 × 2 = 0 + 0.620 384 900 382 72;
  • 15) 0.620 384 900 382 72 × 2 = 1 + 0.240 769 800 765 44;
  • 16) 0.240 769 800 765 44 × 2 = 0 + 0.481 539 601 530 88;
  • 17) 0.481 539 601 530 88 × 2 = 0 + 0.963 079 203 061 76;
  • 18) 0.963 079 203 061 76 × 2 = 1 + 0.926 158 406 123 52;
  • 19) 0.926 158 406 123 52 × 2 = 1 + 0.852 316 812 247 04;
  • 20) 0.852 316 812 247 04 × 2 = 1 + 0.704 633 624 494 08;
  • 21) 0.704 633 624 494 08 × 2 = 1 + 0.409 267 248 988 16;
  • 22) 0.409 267 248 988 16 × 2 = 0 + 0.818 534 497 976 32;
  • 23) 0.818 534 497 976 32 × 2 = 1 + 0.637 068 995 952 64;
  • 24) 0.637 068 995 952 64 × 2 = 1 + 0.274 137 991 905 28;
  • 25) 0.274 137 991 905 28 × 2 = 0 + 0.548 275 983 810 56;
  • 26) 0.548 275 983 810 56 × 2 = 1 + 0.096 551 967 621 12;
  • 27) 0.096 551 967 621 12 × 2 = 0 + 0.193 103 935 242 24;
  • 28) 0.193 103 935 242 24 × 2 = 0 + 0.386 207 870 484 48;
  • 29) 0.386 207 870 484 48 × 2 = 0 + 0.772 415 740 968 96;
  • 30) 0.772 415 740 968 96 × 2 = 1 + 0.544 831 481 937 92;
  • 31) 0.544 831 481 937 92 × 2 = 1 + 0.089 662 963 875 84;
  • 32) 0.089 662 963 875 84 × 2 = 0 + 0.179 325 927 751 68;
  • 33) 0.179 325 927 751 68 × 2 = 0 + 0.358 651 855 503 36;
  • 34) 0.358 651 855 503 36 × 2 = 0 + 0.717 303 711 006 72;
  • 35) 0.717 303 711 006 72 × 2 = 1 + 0.434 607 422 013 44;
  • 36) 0.434 607 422 013 44 × 2 = 0 + 0.869 214 844 026 88;
  • 37) 0.869 214 844 026 88 × 2 = 1 + 0.738 429 688 053 76;
  • 38) 0.738 429 688 053 76 × 2 = 1 + 0.476 859 376 107 52;
  • 39) 0.476 859 376 107 52 × 2 = 0 + 0.953 718 752 215 04;
  • 40) 0.953 718 752 215 04 × 2 = 1 + 0.907 437 504 430 08;
  • 41) 0.907 437 504 430 08 × 2 = 1 + 0.814 875 008 860 16;
  • 42) 0.814 875 008 860 16 × 2 = 1 + 0.629 750 017 720 32;
  • 43) 0.629 750 017 720 32 × 2 = 1 + 0.259 500 035 440 64;
  • 44) 0.259 500 035 440 64 × 2 = 0 + 0.519 000 070 881 28;
  • 45) 0.519 000 070 881 28 × 2 = 1 + 0.038 000 141 762 56;
  • 46) 0.038 000 141 762 56 × 2 = 0 + 0.076 000 283 525 12;
  • 47) 0.076 000 283 525 12 × 2 = 0 + 0.152 000 567 050 24;
  • 48) 0.152 000 567 050 24 × 2 = 0 + 0.304 001 134 100 48;
  • 49) 0.304 001 134 100 48 × 2 = 0 + 0.608 002 268 200 96;
  • 50) 0.608 002 268 200 96 × 2 = 1 + 0.216 004 536 401 92;
  • 51) 0.216 004 536 401 92 × 2 = 0 + 0.432 009 072 803 84;
  • 52) 0.432 009 072 803 84 × 2 = 0 + 0.864 018 145 607 68;
  • 53) 0.864 018 145 607 68 × 2 = 1 + 0.728 036 291 215 36;
  • 54) 0.728 036 291 215 36 × 2 = 1 + 0.456 072 582 430 72;
  • 55) 0.456 072 582 430 72 × 2 = 0 + 0.912 145 164 861 44;
  • 56) 0.912 145 164 861 44 × 2 = 1 + 0.824 290 329 722 88;
  • 57) 0.824 290 329 722 88 × 2 = 1 + 0.648 580 659 445 76;
  • 58) 0.648 580 659 445 76 × 2 = 1 + 0.297 161 318 891 52;
  • 59) 0.297 161 318 891 52 × 2 = 0 + 0.594 322 637 783 04;
  • 60) 0.594 322 637 783 04 × 2 = 1 + 0.188 645 275 566 08;
  • 61) 0.188 645 275 566 08 × 2 = 0 + 0.377 290 551 132 16;
  • 62) 0.377 290 551 132 16 × 2 = 0 + 0.754 581 102 264 32;
  • 63) 0.754 581 102 264 32 × 2 = 1 + 0.509 162 204 528 64;
  • 64) 0.509 162 204 528 64 × 2 = 1 + 0.018 324 409 057 28;

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 33(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1110 1000 0100 1101 1101 0011(2)

6. Positive number before normalization:

0.000 282 005 914 33(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1110 1000 0100 1101 1101 0011(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 33(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1110 1000 0100 1101 1101 0011(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1110 1000 0100 1101 1101 0011(2) × 20 =


1.0010 0111 1011 0100 0110 0010 1101 1110 1000 0100 1101 1101 0011(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 1000 0100 1101 1101 0011


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 1000 0100 1101 1101 0011 =


0010 0111 1011 0100 0110 0010 1101 1110 1000 0100 1101 1101 0011


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 1000 0100 1101 1101 0011


Decimal number -0.000 282 005 914 33 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0010 1101 1110 1000 0100 1101 1101 0011


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