-0.000 282 005 798 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 798(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
-0.000 282 005 798(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:

|-0.000 282 005 798| = 0.000 282 005 798


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: 0.000 282 005 798.

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) 0.000 282 005 798 × 2 = 0 + 0.000 564 011 596;
  • 2) 0.000 564 011 596 × 2 = 0 + 0.001 128 023 192;
  • 3) 0.001 128 023 192 × 2 = 0 + 0.002 256 046 384;
  • 4) 0.002 256 046 384 × 2 = 0 + 0.004 512 092 768;
  • 5) 0.004 512 092 768 × 2 = 0 + 0.009 024 185 536;
  • 6) 0.009 024 185 536 × 2 = 0 + 0.018 048 371 072;
  • 7) 0.018 048 371 072 × 2 = 0 + 0.036 096 742 144;
  • 8) 0.036 096 742 144 × 2 = 0 + 0.072 193 484 288;
  • 9) 0.072 193 484 288 × 2 = 0 + 0.144 386 968 576;
  • 10) 0.144 386 968 576 × 2 = 0 + 0.288 773 937 152;
  • 11) 0.288 773 937 152 × 2 = 0 + 0.577 547 874 304;
  • 12) 0.577 547 874 304 × 2 = 1 + 0.155 095 748 608;
  • 13) 0.155 095 748 608 × 2 = 0 + 0.310 191 497 216;
  • 14) 0.310 191 497 216 × 2 = 0 + 0.620 382 994 432;
  • 15) 0.620 382 994 432 × 2 = 1 + 0.240 765 988 864;
  • 16) 0.240 765 988 864 × 2 = 0 + 0.481 531 977 728;
  • 17) 0.481 531 977 728 × 2 = 0 + 0.963 063 955 456;
  • 18) 0.963 063 955 456 × 2 = 1 + 0.926 127 910 912;
  • 19) 0.926 127 910 912 × 2 = 1 + 0.852 255 821 824;
  • 20) 0.852 255 821 824 × 2 = 1 + 0.704 511 643 648;
  • 21) 0.704 511 643 648 × 2 = 1 + 0.409 023 287 296;
  • 22) 0.409 023 287 296 × 2 = 0 + 0.818 046 574 592;
  • 23) 0.818 046 574 592 × 2 = 1 + 0.636 093 149 184;
  • 24) 0.636 093 149 184 × 2 = 1 + 0.272 186 298 368;
  • 25) 0.272 186 298 368 × 2 = 0 + 0.544 372 596 736;
  • 26) 0.544 372 596 736 × 2 = 1 + 0.088 745 193 472;
  • 27) 0.088 745 193 472 × 2 = 0 + 0.177 490 386 944;
  • 28) 0.177 490 386 944 × 2 = 0 + 0.354 980 773 888;
  • 29) 0.354 980 773 888 × 2 = 0 + 0.709 961 547 776;
  • 30) 0.709 961 547 776 × 2 = 1 + 0.419 923 095 552;
  • 31) 0.419 923 095 552 × 2 = 0 + 0.839 846 191 104;
  • 32) 0.839 846 191 104 × 2 = 1 + 0.679 692 382 208;
  • 33) 0.679 692 382 208 × 2 = 1 + 0.359 384 764 416;
  • 34) 0.359 384 764 416 × 2 = 0 + 0.718 769 528 832;
  • 35) 0.718 769 528 832 × 2 = 1 + 0.437 539 057 664;
  • 36) 0.437 539 057 664 × 2 = 0 + 0.875 078 115 328;
  • 37) 0.875 078 115 328 × 2 = 1 + 0.750 156 230 656;
  • 38) 0.750 156 230 656 × 2 = 1 + 0.500 312 461 312;
  • 39) 0.500 312 461 312 × 2 = 1 + 0.000 624 922 624;
  • 40) 0.000 624 922 624 × 2 = 0 + 0.001 249 845 248;
  • 41) 0.001 249 845 248 × 2 = 0 + 0.002 499 690 496;
  • 42) 0.002 499 690 496 × 2 = 0 + 0.004 999 380 992;
  • 43) 0.004 999 380 992 × 2 = 0 + 0.009 998 761 984;
  • 44) 0.009 998 761 984 × 2 = 0 + 0.019 997 523 968;
  • 45) 0.019 997 523 968 × 2 = 0 + 0.039 995 047 936;
  • 46) 0.039 995 047 936 × 2 = 0 + 0.079 990 095 872;
  • 47) 0.079 990 095 872 × 2 = 0 + 0.159 980 191 744;
  • 48) 0.159 980 191 744 × 2 = 0 + 0.319 960 383 488;
  • 49) 0.319 960 383 488 × 2 = 0 + 0.639 920 766 976;
  • 50) 0.639 920 766 976 × 2 = 1 + 0.279 841 533 952;
  • 51) 0.279 841 533 952 × 2 = 0 + 0.559 683 067 904;
  • 52) 0.559 683 067 904 × 2 = 1 + 0.119 366 135 808;
  • 53) 0.119 366 135 808 × 2 = 0 + 0.238 732 271 616;
  • 54) 0.238 732 271 616 × 2 = 0 + 0.477 464 543 232;
  • 55) 0.477 464 543 232 × 2 = 0 + 0.954 929 086 464;
  • 56) 0.954 929 086 464 × 2 = 1 + 0.909 858 172 928;
  • 57) 0.909 858 172 928 × 2 = 1 + 0.819 716 345 856;
  • 58) 0.819 716 345 856 × 2 = 1 + 0.639 432 691 712;
  • 59) 0.639 432 691 712 × 2 = 1 + 0.278 865 383 424;
  • 60) 0.278 865 383 424 × 2 = 0 + 0.557 730 766 848;
  • 61) 0.557 730 766 848 × 2 = 1 + 0.115 461 533 696;
  • 62) 0.115 461 533 696 × 2 = 0 + 0.230 923 067 392;
  • 63) 0.230 923 067 392 × 2 = 0 + 0.461 846 134 784;
  • 64) 0.461 846 134 784 × 2 = 0 + 0.923 692 269 568;

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:


0.000 282 005 798(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1010 1110 0000 0000 0101 0001 1110 1000(2)

6. Positive number before normalization:

0.000 282 005 798(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1010 1110 0000 0000 0101 0001 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:


0.000 282 005 798(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1010 1110 0000 0000 0101 0001 1110 1000(2) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1010 1110 0000 0000 0101 0001 1110 1000(2) × 20 =


1.0010 0111 1011 0100 0101 1010 1110 0000 0000 0101 0001 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 0101 1010 1110 0000 0000 0101 0001 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 0101 1010 1110 0000 0000 0101 0001 1110 1000 =


0010 0111 1011 0100 0101 1010 1110 0000 0000 0101 0001 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 0101 1010 1110 0000 0000 0101 0001 1110 1000


Decimal number -0.000 282 005 798 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0101 1010 1110 0000 0000 0101 0001 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