-0.000 282 005 908 5 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 908 5(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
-0.000 282 005 908 5(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:

|-0.000 282 005 908 5| = 0.000 282 005 908 5


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: 0.000 282 005 908 5.

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) 0.000 282 005 908 5 × 2 = 0 + 0.000 564 011 817;
  • 2) 0.000 564 011 817 × 2 = 0 + 0.001 128 023 634;
  • 3) 0.001 128 023 634 × 2 = 0 + 0.002 256 047 268;
  • 4) 0.002 256 047 268 × 2 = 0 + 0.004 512 094 536;
  • 5) 0.004 512 094 536 × 2 = 0 + 0.009 024 189 072;
  • 6) 0.009 024 189 072 × 2 = 0 + 0.018 048 378 144;
  • 7) 0.018 048 378 144 × 2 = 0 + 0.036 096 756 288;
  • 8) 0.036 096 756 288 × 2 = 0 + 0.072 193 512 576;
  • 9) 0.072 193 512 576 × 2 = 0 + 0.144 387 025 152;
  • 10) 0.144 387 025 152 × 2 = 0 + 0.288 774 050 304;
  • 11) 0.288 774 050 304 × 2 = 0 + 0.577 548 100 608;
  • 12) 0.577 548 100 608 × 2 = 1 + 0.155 096 201 216;
  • 13) 0.155 096 201 216 × 2 = 0 + 0.310 192 402 432;
  • 14) 0.310 192 402 432 × 2 = 0 + 0.620 384 804 864;
  • 15) 0.620 384 804 864 × 2 = 1 + 0.240 769 609 728;
  • 16) 0.240 769 609 728 × 2 = 0 + 0.481 539 219 456;
  • 17) 0.481 539 219 456 × 2 = 0 + 0.963 078 438 912;
  • 18) 0.963 078 438 912 × 2 = 1 + 0.926 156 877 824;
  • 19) 0.926 156 877 824 × 2 = 1 + 0.852 313 755 648;
  • 20) 0.852 313 755 648 × 2 = 1 + 0.704 627 511 296;
  • 21) 0.704 627 511 296 × 2 = 1 + 0.409 255 022 592;
  • 22) 0.409 255 022 592 × 2 = 0 + 0.818 510 045 184;
  • 23) 0.818 510 045 184 × 2 = 1 + 0.637 020 090 368;
  • 24) 0.637 020 090 368 × 2 = 1 + 0.274 040 180 736;
  • 25) 0.274 040 180 736 × 2 = 0 + 0.548 080 361 472;
  • 26) 0.548 080 361 472 × 2 = 1 + 0.096 160 722 944;
  • 27) 0.096 160 722 944 × 2 = 0 + 0.192 321 445 888;
  • 28) 0.192 321 445 888 × 2 = 0 + 0.384 642 891 776;
  • 29) 0.384 642 891 776 × 2 = 0 + 0.769 285 783 552;
  • 30) 0.769 285 783 552 × 2 = 1 + 0.538 571 567 104;
  • 31) 0.538 571 567 104 × 2 = 1 + 0.077 143 134 208;
  • 32) 0.077 143 134 208 × 2 = 0 + 0.154 286 268 416;
  • 33) 0.154 286 268 416 × 2 = 0 + 0.308 572 536 832;
  • 34) 0.308 572 536 832 × 2 = 0 + 0.617 145 073 664;
  • 35) 0.617 145 073 664 × 2 = 1 + 0.234 290 147 328;
  • 36) 0.234 290 147 328 × 2 = 0 + 0.468 580 294 656;
  • 37) 0.468 580 294 656 × 2 = 0 + 0.937 160 589 312;
  • 38) 0.937 160 589 312 × 2 = 1 + 0.874 321 178 624;
  • 39) 0.874 321 178 624 × 2 = 1 + 0.748 642 357 248;
  • 40) 0.748 642 357 248 × 2 = 1 + 0.497 284 714 496;
  • 41) 0.497 284 714 496 × 2 = 0 + 0.994 569 428 992;
  • 42) 0.994 569 428 992 × 2 = 1 + 0.989 138 857 984;
  • 43) 0.989 138 857 984 × 2 = 1 + 0.978 277 715 968;
  • 44) 0.978 277 715 968 × 2 = 1 + 0.956 555 431 936;
  • 45) 0.956 555 431 936 × 2 = 1 + 0.913 110 863 872;
  • 46) 0.913 110 863 872 × 2 = 1 + 0.826 221 727 744;
  • 47) 0.826 221 727 744 × 2 = 1 + 0.652 443 455 488;
  • 48) 0.652 443 455 488 × 2 = 1 + 0.304 886 910 976;
  • 49) 0.304 886 910 976 × 2 = 0 + 0.609 773 821 952;
  • 50) 0.609 773 821 952 × 2 = 1 + 0.219 547 643 904;
  • 51) 0.219 547 643 904 × 2 = 0 + 0.439 095 287 808;
  • 52) 0.439 095 287 808 × 2 = 0 + 0.878 190 575 616;
  • 53) 0.878 190 575 616 × 2 = 1 + 0.756 381 151 232;
  • 54) 0.756 381 151 232 × 2 = 1 + 0.512 762 302 464;
  • 55) 0.512 762 302 464 × 2 = 1 + 0.025 524 604 928;
  • 56) 0.025 524 604 928 × 2 = 0 + 0.051 049 209 856;
  • 57) 0.051 049 209 856 × 2 = 0 + 0.102 098 419 712;
  • 58) 0.102 098 419 712 × 2 = 0 + 0.204 196 839 424;
  • 59) 0.204 196 839 424 × 2 = 0 + 0.408 393 678 848;
  • 60) 0.408 393 678 848 × 2 = 0 + 0.816 787 357 696;
  • 61) 0.816 787 357 696 × 2 = 1 + 0.633 574 715 392;
  • 62) 0.633 574 715 392 × 2 = 1 + 0.267 149 430 784;
  • 63) 0.267 149 430 784 × 2 = 0 + 0.534 298 861 568;
  • 64) 0.534 298 861 568 × 2 = 1 + 0.068 597 723 136;

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:


0.000 282 005 908 5(10) =


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

6. Positive number before normalization:

0.000 282 005 908 5(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 0111 0111 1111 0100 1110 0000 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:


0.000 282 005 908 5(10) =


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


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


1.0010 0111 1011 0100 0110 0010 0111 0111 1111 0100 1110 0000 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 0111 0111 1111 0100 1110 0000 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 0111 0111 1111 0100 1110 0000 1101 =


0010 0111 1011 0100 0110 0010 0111 0111 1111 0100 1110 0000 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 0111 0111 1111 0100 1110 0000 1101


Decimal number -0.000 282 005 908 5 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0010 0111 0111 1111 0100 1110 0000 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