-0.000 282 014 8 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 014 8(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
-0.000 282 014 8(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:

|-0.000 282 014 8| = 0.000 282 014 8


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: 0.000 282 014 8.

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) 0.000 282 014 8 × 2 = 0 + 0.000 564 029 6;
  • 2) 0.000 564 029 6 × 2 = 0 + 0.001 128 059 2;
  • 3) 0.001 128 059 2 × 2 = 0 + 0.002 256 118 4;
  • 4) 0.002 256 118 4 × 2 = 0 + 0.004 512 236 8;
  • 5) 0.004 512 236 8 × 2 = 0 + 0.009 024 473 6;
  • 6) 0.009 024 473 6 × 2 = 0 + 0.018 048 947 2;
  • 7) 0.018 048 947 2 × 2 = 0 + 0.036 097 894 4;
  • 8) 0.036 097 894 4 × 2 = 0 + 0.072 195 788 8;
  • 9) 0.072 195 788 8 × 2 = 0 + 0.144 391 577 6;
  • 10) 0.144 391 577 6 × 2 = 0 + 0.288 783 155 2;
  • 11) 0.288 783 155 2 × 2 = 0 + 0.577 566 310 4;
  • 12) 0.577 566 310 4 × 2 = 1 + 0.155 132 620 8;
  • 13) 0.155 132 620 8 × 2 = 0 + 0.310 265 241 6;
  • 14) 0.310 265 241 6 × 2 = 0 + 0.620 530 483 2;
  • 15) 0.620 530 483 2 × 2 = 1 + 0.241 060 966 4;
  • 16) 0.241 060 966 4 × 2 = 0 + 0.482 121 932 8;
  • 17) 0.482 121 932 8 × 2 = 0 + 0.964 243 865 6;
  • 18) 0.964 243 865 6 × 2 = 1 + 0.928 487 731 2;
  • 19) 0.928 487 731 2 × 2 = 1 + 0.856 975 462 4;
  • 20) 0.856 975 462 4 × 2 = 1 + 0.713 950 924 8;
  • 21) 0.713 950 924 8 × 2 = 1 + 0.427 901 849 6;
  • 22) 0.427 901 849 6 × 2 = 0 + 0.855 803 699 2;
  • 23) 0.855 803 699 2 × 2 = 1 + 0.711 607 398 4;
  • 24) 0.711 607 398 4 × 2 = 1 + 0.423 214 796 8;
  • 25) 0.423 214 796 8 × 2 = 0 + 0.846 429 593 6;
  • 26) 0.846 429 593 6 × 2 = 1 + 0.692 859 187 2;
  • 27) 0.692 859 187 2 × 2 = 1 + 0.385 718 374 4;
  • 28) 0.385 718 374 4 × 2 = 0 + 0.771 436 748 8;
  • 29) 0.771 436 748 8 × 2 = 1 + 0.542 873 497 6;
  • 30) 0.542 873 497 6 × 2 = 1 + 0.085 746 995 2;
  • 31) 0.085 746 995 2 × 2 = 0 + 0.171 493 990 4;
  • 32) 0.171 493 990 4 × 2 = 0 + 0.342 987 980 8;
  • 33) 0.342 987 980 8 × 2 = 0 + 0.685 975 961 6;
  • 34) 0.685 975 961 6 × 2 = 1 + 0.371 951 923 2;
  • 35) 0.371 951 923 2 × 2 = 0 + 0.743 903 846 4;
  • 36) 0.743 903 846 4 × 2 = 1 + 0.487 807 692 8;
  • 37) 0.487 807 692 8 × 2 = 0 + 0.975 615 385 6;
  • 38) 0.975 615 385 6 × 2 = 1 + 0.951 230 771 2;
  • 39) 0.951 230 771 2 × 2 = 1 + 0.902 461 542 4;
  • 40) 0.902 461 542 4 × 2 = 1 + 0.804 923 084 8;
  • 41) 0.804 923 084 8 × 2 = 1 + 0.609 846 169 6;
  • 42) 0.609 846 169 6 × 2 = 1 + 0.219 692 339 2;
  • 43) 0.219 692 339 2 × 2 = 0 + 0.439 384 678 4;
  • 44) 0.439 384 678 4 × 2 = 0 + 0.878 769 356 8;
  • 45) 0.878 769 356 8 × 2 = 1 + 0.757 538 713 6;
  • 46) 0.757 538 713 6 × 2 = 1 + 0.515 077 427 2;
  • 47) 0.515 077 427 2 × 2 = 1 + 0.030 154 854 4;
  • 48) 0.030 154 854 4 × 2 = 0 + 0.060 309 708 8;
  • 49) 0.060 309 708 8 × 2 = 0 + 0.120 619 417 6;
  • 50) 0.120 619 417 6 × 2 = 0 + 0.241 238 835 2;
  • 51) 0.241 238 835 2 × 2 = 0 + 0.482 477 670 4;
  • 52) 0.482 477 670 4 × 2 = 0 + 0.964 955 340 8;
  • 53) 0.964 955 340 8 × 2 = 1 + 0.929 910 681 6;
  • 54) 0.929 910 681 6 × 2 = 1 + 0.859 821 363 2;
  • 55) 0.859 821 363 2 × 2 = 1 + 0.719 642 726 4;
  • 56) 0.719 642 726 4 × 2 = 1 + 0.439 285 452 8;
  • 57) 0.439 285 452 8 × 2 = 0 + 0.878 570 905 6;
  • 58) 0.878 570 905 6 × 2 = 1 + 0.757 141 811 2;
  • 59) 0.757 141 811 2 × 2 = 1 + 0.514 283 622 4;
  • 60) 0.514 283 622 4 × 2 = 1 + 0.028 567 244 8;
  • 61) 0.028 567 244 8 × 2 = 0 + 0.057 134 489 6;
  • 62) 0.057 134 489 6 × 2 = 0 + 0.114 268 979 2;
  • 63) 0.114 268 979 2 × 2 = 0 + 0.228 537 958 4;
  • 64) 0.228 537 958 4 × 2 = 0 + 0.457 075 916 8;

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:


0.000 282 014 8(10) =


0.0000 0000 0001 0010 0111 1011 0110 1100 0101 0111 1100 1110 0000 1111 0111 0000(2)

6. Positive number before normalization:

0.000 282 014 8(10) =


0.0000 0000 0001 0010 0111 1011 0110 1100 0101 0111 1100 1110 0000 1111 0111 0000(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:


0.000 282 014 8(10) =


0.0000 0000 0001 0010 0111 1011 0110 1100 0101 0111 1100 1110 0000 1111 0111 0000(2) =


0.0000 0000 0001 0010 0111 1011 0110 1100 0101 0111 1100 1110 0000 1111 0111 0000(2) × 20 =


1.0010 0111 1011 0110 1100 0101 0111 1100 1110 0000 1111 0111 0000(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 0110 1100 0101 0111 1100 1110 0000 1111 0111 0000


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 0110 1100 0101 0111 1100 1110 0000 1111 0111 0000 =


0010 0111 1011 0110 1100 0101 0111 1100 1110 0000 1111 0111 0000


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 0110 1100 0101 0111 1100 1110 0000 1111 0111 0000


Decimal number -0.000 282 014 8 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0110 1100 0101 0111 1100 1110 0000 1111 0111 0000


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