-0.000 281 997 7 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 281 997 7(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 7(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 7| = 0.000 281 997 7


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 7.

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 7 × 2 = 0 + 0.000 563 995 4;
  • 2) 0.000 563 995 4 × 2 = 0 + 0.001 127 990 8;
  • 3) 0.001 127 990 8 × 2 = 0 + 0.002 255 981 6;
  • 4) 0.002 255 981 6 × 2 = 0 + 0.004 511 963 2;
  • 5) 0.004 511 963 2 × 2 = 0 + 0.009 023 926 4;
  • 6) 0.009 023 926 4 × 2 = 0 + 0.018 047 852 8;
  • 7) 0.018 047 852 8 × 2 = 0 + 0.036 095 705 6;
  • 8) 0.036 095 705 6 × 2 = 0 + 0.072 191 411 2;
  • 9) 0.072 191 411 2 × 2 = 0 + 0.144 382 822 4;
  • 10) 0.144 382 822 4 × 2 = 0 + 0.288 765 644 8;
  • 11) 0.288 765 644 8 × 2 = 0 + 0.577 531 289 6;
  • 12) 0.577 531 289 6 × 2 = 1 + 0.155 062 579 2;
  • 13) 0.155 062 579 2 × 2 = 0 + 0.310 125 158 4;
  • 14) 0.310 125 158 4 × 2 = 0 + 0.620 250 316 8;
  • 15) 0.620 250 316 8 × 2 = 1 + 0.240 500 633 6;
  • 16) 0.240 500 633 6 × 2 = 0 + 0.481 001 267 2;
  • 17) 0.481 001 267 2 × 2 = 0 + 0.962 002 534 4;
  • 18) 0.962 002 534 4 × 2 = 1 + 0.924 005 068 8;
  • 19) 0.924 005 068 8 × 2 = 1 + 0.848 010 137 6;
  • 20) 0.848 010 137 6 × 2 = 1 + 0.696 020 275 2;
  • 21) 0.696 020 275 2 × 2 = 1 + 0.392 040 550 4;
  • 22) 0.392 040 550 4 × 2 = 0 + 0.784 081 100 8;
  • 23) 0.784 081 100 8 × 2 = 1 + 0.568 162 201 6;
  • 24) 0.568 162 201 6 × 2 = 1 + 0.136 324 403 2;
  • 25) 0.136 324 403 2 × 2 = 0 + 0.272 648 806 4;
  • 26) 0.272 648 806 4 × 2 = 0 + 0.545 297 612 8;
  • 27) 0.545 297 612 8 × 2 = 1 + 0.090 595 225 6;
  • 28) 0.090 595 225 6 × 2 = 0 + 0.181 190 451 2;
  • 29) 0.181 190 451 2 × 2 = 0 + 0.362 380 902 4;
  • 30) 0.362 380 902 4 × 2 = 0 + 0.724 761 804 8;
  • 31) 0.724 761 804 8 × 2 = 1 + 0.449 523 609 6;
  • 32) 0.449 523 609 6 × 2 = 0 + 0.899 047 219 2;
  • 33) 0.899 047 219 2 × 2 = 1 + 0.798 094 438 4;
  • 34) 0.798 094 438 4 × 2 = 1 + 0.596 188 876 8;
  • 35) 0.596 188 876 8 × 2 = 1 + 0.192 377 753 6;
  • 36) 0.192 377 753 6 × 2 = 0 + 0.384 755 507 2;
  • 37) 0.384 755 507 2 × 2 = 0 + 0.769 511 014 4;
  • 38) 0.769 511 014 4 × 2 = 1 + 0.539 022 028 8;
  • 39) 0.539 022 028 8 × 2 = 1 + 0.078 044 057 6;
  • 40) 0.078 044 057 6 × 2 = 0 + 0.156 088 115 2;
  • 41) 0.156 088 115 2 × 2 = 0 + 0.312 176 230 4;
  • 42) 0.312 176 230 4 × 2 = 0 + 0.624 352 460 8;
  • 43) 0.624 352 460 8 × 2 = 1 + 0.248 704 921 6;
  • 44) 0.248 704 921 6 × 2 = 0 + 0.497 409 843 2;
  • 45) 0.497 409 843 2 × 2 = 0 + 0.994 819 686 4;
  • 46) 0.994 819 686 4 × 2 = 1 + 0.989 639 372 8;
  • 47) 0.989 639 372 8 × 2 = 1 + 0.979 278 745 6;
  • 48) 0.979 278 745 6 × 2 = 1 + 0.958 557 491 2;
  • 49) 0.958 557 491 2 × 2 = 1 + 0.917 114 982 4;
  • 50) 0.917 114 982 4 × 2 = 1 + 0.834 229 964 8;
  • 51) 0.834 229 964 8 × 2 = 1 + 0.668 459 929 6;
  • 52) 0.668 459 929 6 × 2 = 1 + 0.336 919 859 2;
  • 53) 0.336 919 859 2 × 2 = 0 + 0.673 839 718 4;
  • 54) 0.673 839 718 4 × 2 = 1 + 0.347 679 436 8;
  • 55) 0.347 679 436 8 × 2 = 0 + 0.695 358 873 6;
  • 56) 0.695 358 873 6 × 2 = 1 + 0.390 717 747 2;
  • 57) 0.390 717 747 2 × 2 = 0 + 0.781 435 494 4;
  • 58) 0.781 435 494 4 × 2 = 1 + 0.562 870 988 8;
  • 59) 0.562 870 988 8 × 2 = 1 + 0.125 741 977 6;
  • 60) 0.125 741 977 6 × 2 = 0 + 0.251 483 955 2;
  • 61) 0.251 483 955 2 × 2 = 0 + 0.502 967 910 4;
  • 62) 0.502 967 910 4 × 2 = 1 + 0.005 935 820 8;
  • 63) 0.005 935 820 8 × 2 = 0 + 0.011 871 641 6;
  • 64) 0.011 871 641 6 × 2 = 0 + 0.023 743 283 2;

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 7(10) =


0.0000 0000 0001 0010 0111 1011 0010 0010 1110 0110 0010 0111 1111 0101 0110 0100(2)

6. Positive number before normalization:

0.000 281 997 7(10) =


0.0000 0000 0001 0010 0111 1011 0010 0010 1110 0110 0010 0111 1111 0101 0110 0100(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 7(10) =


0.0000 0000 0001 0010 0111 1011 0010 0010 1110 0110 0010 0111 1111 0101 0110 0100(2) =


0.0000 0000 0001 0010 0111 1011 0010 0010 1110 0110 0010 0111 1111 0101 0110 0100(2) × 20 =


1.0010 0111 1011 0010 0010 1110 0110 0010 0111 1111 0101 0110 0100(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 0010 1110 0110 0010 0111 1111 0101 0110 0100


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 0010 1110 0110 0010 0111 1111 0101 0110 0100 =


0010 0111 1011 0010 0010 1110 0110 0010 0111 1111 0101 0110 0100


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 0010 1110 0110 0010 0111 1111 0101 0110 0100


Decimal number -0.000 281 997 7 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0010 0010 1110 0110 0010 0111 1111 0101 0110 0100


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