-0.000 282 005 914 385 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 914 385(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
-0.000 282 005 914 385(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:

|-0.000 282 005 914 385| = 0.000 282 005 914 385


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: 0.000 282 005 914 385.

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) 0.000 282 005 914 385 × 2 = 0 + 0.000 564 011 828 77;
  • 2) 0.000 564 011 828 77 × 2 = 0 + 0.001 128 023 657 54;
  • 3) 0.001 128 023 657 54 × 2 = 0 + 0.002 256 047 315 08;
  • 4) 0.002 256 047 315 08 × 2 = 0 + 0.004 512 094 630 16;
  • 5) 0.004 512 094 630 16 × 2 = 0 + 0.009 024 189 260 32;
  • 6) 0.009 024 189 260 32 × 2 = 0 + 0.018 048 378 520 64;
  • 7) 0.018 048 378 520 64 × 2 = 0 + 0.036 096 757 041 28;
  • 8) 0.036 096 757 041 28 × 2 = 0 + 0.072 193 514 082 56;
  • 9) 0.072 193 514 082 56 × 2 = 0 + 0.144 387 028 165 12;
  • 10) 0.144 387 028 165 12 × 2 = 0 + 0.288 774 056 330 24;
  • 11) 0.288 774 056 330 24 × 2 = 0 + 0.577 548 112 660 48;
  • 12) 0.577 548 112 660 48 × 2 = 1 + 0.155 096 225 320 96;
  • 13) 0.155 096 225 320 96 × 2 = 0 + 0.310 192 450 641 92;
  • 14) 0.310 192 450 641 92 × 2 = 0 + 0.620 384 901 283 84;
  • 15) 0.620 384 901 283 84 × 2 = 1 + 0.240 769 802 567 68;
  • 16) 0.240 769 802 567 68 × 2 = 0 + 0.481 539 605 135 36;
  • 17) 0.481 539 605 135 36 × 2 = 0 + 0.963 079 210 270 72;
  • 18) 0.963 079 210 270 72 × 2 = 1 + 0.926 158 420 541 44;
  • 19) 0.926 158 420 541 44 × 2 = 1 + 0.852 316 841 082 88;
  • 20) 0.852 316 841 082 88 × 2 = 1 + 0.704 633 682 165 76;
  • 21) 0.704 633 682 165 76 × 2 = 1 + 0.409 267 364 331 52;
  • 22) 0.409 267 364 331 52 × 2 = 0 + 0.818 534 728 663 04;
  • 23) 0.818 534 728 663 04 × 2 = 1 + 0.637 069 457 326 08;
  • 24) 0.637 069 457 326 08 × 2 = 1 + 0.274 138 914 652 16;
  • 25) 0.274 138 914 652 16 × 2 = 0 + 0.548 277 829 304 32;
  • 26) 0.548 277 829 304 32 × 2 = 1 + 0.096 555 658 608 64;
  • 27) 0.096 555 658 608 64 × 2 = 0 + 0.193 111 317 217 28;
  • 28) 0.193 111 317 217 28 × 2 = 0 + 0.386 222 634 434 56;
  • 29) 0.386 222 634 434 56 × 2 = 0 + 0.772 445 268 869 12;
  • 30) 0.772 445 268 869 12 × 2 = 1 + 0.544 890 537 738 24;
  • 31) 0.544 890 537 738 24 × 2 = 1 + 0.089 781 075 476 48;
  • 32) 0.089 781 075 476 48 × 2 = 0 + 0.179 562 150 952 96;
  • 33) 0.179 562 150 952 96 × 2 = 0 + 0.359 124 301 905 92;
  • 34) 0.359 124 301 905 92 × 2 = 0 + 0.718 248 603 811 84;
  • 35) 0.718 248 603 811 84 × 2 = 1 + 0.436 497 207 623 68;
  • 36) 0.436 497 207 623 68 × 2 = 0 + 0.872 994 415 247 36;
  • 37) 0.872 994 415 247 36 × 2 = 1 + 0.745 988 830 494 72;
  • 38) 0.745 988 830 494 72 × 2 = 1 + 0.491 977 660 989 44;
  • 39) 0.491 977 660 989 44 × 2 = 0 + 0.983 955 321 978 88;
  • 40) 0.983 955 321 978 88 × 2 = 1 + 0.967 910 643 957 76;
  • 41) 0.967 910 643 957 76 × 2 = 1 + 0.935 821 287 915 52;
  • 42) 0.935 821 287 915 52 × 2 = 1 + 0.871 642 575 831 04;
  • 43) 0.871 642 575 831 04 × 2 = 1 + 0.743 285 151 662 08;
  • 44) 0.743 285 151 662 08 × 2 = 1 + 0.486 570 303 324 16;
  • 45) 0.486 570 303 324 16 × 2 = 0 + 0.973 140 606 648 32;
  • 46) 0.973 140 606 648 32 × 2 = 1 + 0.946 281 213 296 64;
  • 47) 0.946 281 213 296 64 × 2 = 1 + 0.892 562 426 593 28;
  • 48) 0.892 562 426 593 28 × 2 = 1 + 0.785 124 853 186 56;
  • 49) 0.785 124 853 186 56 × 2 = 1 + 0.570 249 706 373 12;
  • 50) 0.570 249 706 373 12 × 2 = 1 + 0.140 499 412 746 24;
  • 51) 0.140 499 412 746 24 × 2 = 0 + 0.280 998 825 492 48;
  • 52) 0.280 998 825 492 48 × 2 = 0 + 0.561 997 650 984 96;
  • 53) 0.561 997 650 984 96 × 2 = 1 + 0.123 995 301 969 92;
  • 54) 0.123 995 301 969 92 × 2 = 0 + 0.247 990 603 939 84;
  • 55) 0.247 990 603 939 84 × 2 = 0 + 0.495 981 207 879 68;
  • 56) 0.495 981 207 879 68 × 2 = 0 + 0.991 962 415 759 36;
  • 57) 0.991 962 415 759 36 × 2 = 1 + 0.983 924 831 518 72;
  • 58) 0.983 924 831 518 72 × 2 = 1 + 0.967 849 663 037 44;
  • 59) 0.967 849 663 037 44 × 2 = 1 + 0.935 699 326 074 88;
  • 60) 0.935 699 326 074 88 × 2 = 1 + 0.871 398 652 149 76;
  • 61) 0.871 398 652 149 76 × 2 = 1 + 0.742 797 304 299 52;
  • 62) 0.742 797 304 299 52 × 2 = 1 + 0.485 594 608 599 04;
  • 63) 0.485 594 608 599 04 × 2 = 0 + 0.971 189 217 198 08;
  • 64) 0.971 189 217 198 08 × 2 = 1 + 0.942 378 434 396 16;

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:


0.000 282 005 914 385(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1111 0111 1100 1000 1111 1101(2)

6. Positive number before normalization:

0.000 282 005 914 385(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1111 0111 1100 1000 1111 1101(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:


0.000 282 005 914 385(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1111 0111 1100 1000 1111 1101(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1111 0111 1100 1000 1111 1101(2) × 20 =


1.0010 0111 1011 0100 0110 0010 1101 1111 0111 1100 1000 1111 1101(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 1111 0111 1100 1000 1111 1101


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 1111 0111 1100 1000 1111 1101 =


0010 0111 1011 0100 0110 0010 1101 1111 0111 1100 1000 1111 1101


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 1111 0111 1100 1000 1111 1101


Decimal number -0.000 282 005 914 385 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0010 1101 1111 0111 1100 1000 1111 1101


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