-0.000 282 005 925 6 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 925 6(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
-0.000 282 005 925 6(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:

|-0.000 282 005 925 6| = 0.000 282 005 925 6


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: 0.000 282 005 925 6.

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) 0.000 282 005 925 6 × 2 = 0 + 0.000 564 011 851 2;
  • 2) 0.000 564 011 851 2 × 2 = 0 + 0.001 128 023 702 4;
  • 3) 0.001 128 023 702 4 × 2 = 0 + 0.002 256 047 404 8;
  • 4) 0.002 256 047 404 8 × 2 = 0 + 0.004 512 094 809 6;
  • 5) 0.004 512 094 809 6 × 2 = 0 + 0.009 024 189 619 2;
  • 6) 0.009 024 189 619 2 × 2 = 0 + 0.018 048 379 238 4;
  • 7) 0.018 048 379 238 4 × 2 = 0 + 0.036 096 758 476 8;
  • 8) 0.036 096 758 476 8 × 2 = 0 + 0.072 193 516 953 6;
  • 9) 0.072 193 516 953 6 × 2 = 0 + 0.144 387 033 907 2;
  • 10) 0.144 387 033 907 2 × 2 = 0 + 0.288 774 067 814 4;
  • 11) 0.288 774 067 814 4 × 2 = 0 + 0.577 548 135 628 8;
  • 12) 0.577 548 135 628 8 × 2 = 1 + 0.155 096 271 257 6;
  • 13) 0.155 096 271 257 6 × 2 = 0 + 0.310 192 542 515 2;
  • 14) 0.310 192 542 515 2 × 2 = 0 + 0.620 385 085 030 4;
  • 15) 0.620 385 085 030 4 × 2 = 1 + 0.240 770 170 060 8;
  • 16) 0.240 770 170 060 8 × 2 = 0 + 0.481 540 340 121 6;
  • 17) 0.481 540 340 121 6 × 2 = 0 + 0.963 080 680 243 2;
  • 18) 0.963 080 680 243 2 × 2 = 1 + 0.926 161 360 486 4;
  • 19) 0.926 161 360 486 4 × 2 = 1 + 0.852 322 720 972 8;
  • 20) 0.852 322 720 972 8 × 2 = 1 + 0.704 645 441 945 6;
  • 21) 0.704 645 441 945 6 × 2 = 1 + 0.409 290 883 891 2;
  • 22) 0.409 290 883 891 2 × 2 = 0 + 0.818 581 767 782 4;
  • 23) 0.818 581 767 782 4 × 2 = 1 + 0.637 163 535 564 8;
  • 24) 0.637 163 535 564 8 × 2 = 1 + 0.274 327 071 129 6;
  • 25) 0.274 327 071 129 6 × 2 = 0 + 0.548 654 142 259 2;
  • 26) 0.548 654 142 259 2 × 2 = 1 + 0.097 308 284 518 4;
  • 27) 0.097 308 284 518 4 × 2 = 0 + 0.194 616 569 036 8;
  • 28) 0.194 616 569 036 8 × 2 = 0 + 0.389 233 138 073 6;
  • 29) 0.389 233 138 073 6 × 2 = 0 + 0.778 466 276 147 2;
  • 30) 0.778 466 276 147 2 × 2 = 1 + 0.556 932 552 294 4;
  • 31) 0.556 932 552 294 4 × 2 = 1 + 0.113 865 104 588 8;
  • 32) 0.113 865 104 588 8 × 2 = 0 + 0.227 730 209 177 6;
  • 33) 0.227 730 209 177 6 × 2 = 0 + 0.455 460 418 355 2;
  • 34) 0.455 460 418 355 2 × 2 = 0 + 0.910 920 836 710 4;
  • 35) 0.910 920 836 710 4 × 2 = 1 + 0.821 841 673 420 8;
  • 36) 0.821 841 673 420 8 × 2 = 1 + 0.643 683 346 841 6;
  • 37) 0.643 683 346 841 6 × 2 = 1 + 0.287 366 693 683 2;
  • 38) 0.287 366 693 683 2 × 2 = 0 + 0.574 733 387 366 4;
  • 39) 0.574 733 387 366 4 × 2 = 1 + 0.149 466 774 732 8;
  • 40) 0.149 466 774 732 8 × 2 = 0 + 0.298 933 549 465 6;
  • 41) 0.298 933 549 465 6 × 2 = 0 + 0.597 867 098 931 2;
  • 42) 0.597 867 098 931 2 × 2 = 1 + 0.195 734 197 862 4;
  • 43) 0.195 734 197 862 4 × 2 = 0 + 0.391 468 395 724 8;
  • 44) 0.391 468 395 724 8 × 2 = 0 + 0.782 936 791 449 6;
  • 45) 0.782 936 791 449 6 × 2 = 1 + 0.565 873 582 899 2;
  • 46) 0.565 873 582 899 2 × 2 = 1 + 0.131 747 165 798 4;
  • 47) 0.131 747 165 798 4 × 2 = 0 + 0.263 494 331 596 8;
  • 48) 0.263 494 331 596 8 × 2 = 0 + 0.526 988 663 193 6;
  • 49) 0.526 988 663 193 6 × 2 = 1 + 0.053 977 326 387 2;
  • 50) 0.053 977 326 387 2 × 2 = 0 + 0.107 954 652 774 4;
  • 51) 0.107 954 652 774 4 × 2 = 0 + 0.215 909 305 548 8;
  • 52) 0.215 909 305 548 8 × 2 = 0 + 0.431 818 611 097 6;
  • 53) 0.431 818 611 097 6 × 2 = 0 + 0.863 637 222 195 2;
  • 54) 0.863 637 222 195 2 × 2 = 1 + 0.727 274 444 390 4;
  • 55) 0.727 274 444 390 4 × 2 = 1 + 0.454 548 888 780 8;
  • 56) 0.454 548 888 780 8 × 2 = 0 + 0.909 097 777 561 6;
  • 57) 0.909 097 777 561 6 × 2 = 1 + 0.818 195 555 123 2;
  • 58) 0.818 195 555 123 2 × 2 = 1 + 0.636 391 110 246 4;
  • 59) 0.636 391 110 246 4 × 2 = 1 + 0.272 782 220 492 8;
  • 60) 0.272 782 220 492 8 × 2 = 0 + 0.545 564 440 985 6;
  • 61) 0.545 564 440 985 6 × 2 = 1 + 0.091 128 881 971 2;
  • 62) 0.091 128 881 971 2 × 2 = 0 + 0.182 257 763 942 4;
  • 63) 0.182 257 763 942 4 × 2 = 0 + 0.364 515 527 884 8;
  • 64) 0.364 515 527 884 8 × 2 = 0 + 0.729 031 055 769 6;

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:


0.000 282 005 925 6(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0011 1010 0100 1100 1000 0110 1110 1000(2)

6. Positive number before normalization:

0.000 282 005 925 6(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0011 1010 0100 1100 1000 0110 1110 1000(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:


0.000 282 005 925 6(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0011 1010 0100 1100 1000 0110 1110 1000(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0011 1010 0100 1100 1000 0110 1110 1000(2) × 20 =


1.0010 0111 1011 0100 0110 0011 1010 0100 1100 1000 0110 1110 1000(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 0011 1010 0100 1100 1000 0110 1110 1000


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 0011 1010 0100 1100 1000 0110 1110 1000 =


0010 0111 1011 0100 0110 0011 1010 0100 1100 1000 0110 1110 1000


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 0011 1010 0100 1100 1000 0110 1110 1000


Decimal number -0.000 282 005 925 6 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0011 1010 0100 1100 1000 0110 1110 1000


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