-0.000 281 997 9 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 281 997 9(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
-0.000 281 997 9(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:

|-0.000 281 997 9| = 0.000 281 997 9


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: 0.000 281 997 9.

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) 0.000 281 997 9 × 2 = 0 + 0.000 563 995 8;
  • 2) 0.000 563 995 8 × 2 = 0 + 0.001 127 991 6;
  • 3) 0.001 127 991 6 × 2 = 0 + 0.002 255 983 2;
  • 4) 0.002 255 983 2 × 2 = 0 + 0.004 511 966 4;
  • 5) 0.004 511 966 4 × 2 = 0 + 0.009 023 932 8;
  • 6) 0.009 023 932 8 × 2 = 0 + 0.018 047 865 6;
  • 7) 0.018 047 865 6 × 2 = 0 + 0.036 095 731 2;
  • 8) 0.036 095 731 2 × 2 = 0 + 0.072 191 462 4;
  • 9) 0.072 191 462 4 × 2 = 0 + 0.144 382 924 8;
  • 10) 0.144 382 924 8 × 2 = 0 + 0.288 765 849 6;
  • 11) 0.288 765 849 6 × 2 = 0 + 0.577 531 699 2;
  • 12) 0.577 531 699 2 × 2 = 1 + 0.155 063 398 4;
  • 13) 0.155 063 398 4 × 2 = 0 + 0.310 126 796 8;
  • 14) 0.310 126 796 8 × 2 = 0 + 0.620 253 593 6;
  • 15) 0.620 253 593 6 × 2 = 1 + 0.240 507 187 2;
  • 16) 0.240 507 187 2 × 2 = 0 + 0.481 014 374 4;
  • 17) 0.481 014 374 4 × 2 = 0 + 0.962 028 748 8;
  • 18) 0.962 028 748 8 × 2 = 1 + 0.924 057 497 6;
  • 19) 0.924 057 497 6 × 2 = 1 + 0.848 114 995 2;
  • 20) 0.848 114 995 2 × 2 = 1 + 0.696 229 990 4;
  • 21) 0.696 229 990 4 × 2 = 1 + 0.392 459 980 8;
  • 22) 0.392 459 980 8 × 2 = 0 + 0.784 919 961 6;
  • 23) 0.784 919 961 6 × 2 = 1 + 0.569 839 923 2;
  • 24) 0.569 839 923 2 × 2 = 1 + 0.139 679 846 4;
  • 25) 0.139 679 846 4 × 2 = 0 + 0.279 359 692 8;
  • 26) 0.279 359 692 8 × 2 = 0 + 0.558 719 385 6;
  • 27) 0.558 719 385 6 × 2 = 1 + 0.117 438 771 2;
  • 28) 0.117 438 771 2 × 2 = 0 + 0.234 877 542 4;
  • 29) 0.234 877 542 4 × 2 = 0 + 0.469 755 084 8;
  • 30) 0.469 755 084 8 × 2 = 0 + 0.939 510 169 6;
  • 31) 0.939 510 169 6 × 2 = 1 + 0.879 020 339 2;
  • 32) 0.879 020 339 2 × 2 = 1 + 0.758 040 678 4;
  • 33) 0.758 040 678 4 × 2 = 1 + 0.516 081 356 8;
  • 34) 0.516 081 356 8 × 2 = 1 + 0.032 162 713 6;
  • 35) 0.032 162 713 6 × 2 = 0 + 0.064 325 427 2;
  • 36) 0.064 325 427 2 × 2 = 0 + 0.128 650 854 4;
  • 37) 0.128 650 854 4 × 2 = 0 + 0.257 301 708 8;
  • 38) 0.257 301 708 8 × 2 = 0 + 0.514 603 417 6;
  • 39) 0.514 603 417 6 × 2 = 1 + 0.029 206 835 2;
  • 40) 0.029 206 835 2 × 2 = 0 + 0.058 413 670 4;
  • 41) 0.058 413 670 4 × 2 = 0 + 0.116 827 340 8;
  • 42) 0.116 827 340 8 × 2 = 0 + 0.233 654 681 6;
  • 43) 0.233 654 681 6 × 2 = 0 + 0.467 309 363 2;
  • 44) 0.467 309 363 2 × 2 = 0 + 0.934 618 726 4;
  • 45) 0.934 618 726 4 × 2 = 1 + 0.869 237 452 8;
  • 46) 0.869 237 452 8 × 2 = 1 + 0.738 474 905 6;
  • 47) 0.738 474 905 6 × 2 = 1 + 0.476 949 811 2;
  • 48) 0.476 949 811 2 × 2 = 0 + 0.953 899 622 4;
  • 49) 0.953 899 622 4 × 2 = 1 + 0.907 799 244 8;
  • 50) 0.907 799 244 8 × 2 = 1 + 0.815 598 489 6;
  • 51) 0.815 598 489 6 × 2 = 1 + 0.631 196 979 2;
  • 52) 0.631 196 979 2 × 2 = 1 + 0.262 393 958 4;
  • 53) 0.262 393 958 4 × 2 = 0 + 0.524 787 916 8;
  • 54) 0.524 787 916 8 × 2 = 1 + 0.049 575 833 6;
  • 55) 0.049 575 833 6 × 2 = 0 + 0.099 151 667 2;
  • 56) 0.099 151 667 2 × 2 = 0 + 0.198 303 334 4;
  • 57) 0.198 303 334 4 × 2 = 0 + 0.396 606 668 8;
  • 58) 0.396 606 668 8 × 2 = 0 + 0.793 213 337 6;
  • 59) 0.793 213 337 6 × 2 = 1 + 0.586 426 675 2;
  • 60) 0.586 426 675 2 × 2 = 1 + 0.172 853 350 4;
  • 61) 0.172 853 350 4 × 2 = 0 + 0.345 706 700 8;
  • 62) 0.345 706 700 8 × 2 = 0 + 0.691 413 401 6;
  • 63) 0.691 413 401 6 × 2 = 1 + 0.382 826 803 2;
  • 64) 0.382 826 803 2 × 2 = 0 + 0.765 653 606 4;

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:


0.000 281 997 9(10) =

0.0000 0000 0001 0010 0111 1011 0010 0011 1100 0010 0000 1110 1111 0100 0011 0010(2)

6. Positive number before normalization:

0.000 281 997 9(10) =

0.0000 0000 0001 0010 0111 1011 0010 0011 1100 0010 0000 1110 1111 0100 0011 0010(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:


0.000 281 997 9(10) =

0.0000 0000 0001 0010 0111 1011 0010 0011 1100 0010 0000 1110 1111 0100 0011 0010(2) =

0.0000 0000 0001 0010 0111 1011 0010 0011 1100 0010 0000 1110 1111 0100 0011 0010(2) × 20 =

1.0010 0111 1011 0010 0011 1100 0010 0000 1110 1111 0100 0011 0010(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 0010 0011 1100 0010 0000 1110 1111 0100 0011 0010


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 0010 0011 1100 0010 0000 1110 1111 0100 0011 0010 =

0010 0111 1011 0010 0011 1100 0010 0000 1110 1111 0100 0011 0010


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 0010 0011 1100 0010 0000 1110 1111 0100 0011 0010


Decimal number -0.000 281 997 9 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0010 0011 1100 0010 0000 1110 1111 0100 0011 0010

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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