0.026 915 1 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.026 915 1(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
0.026 915 1(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. 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;

2. 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)


3. Convert to binary (base 2) the fractional part: 0.026 915 1.

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) 0.026 915 1 × 2 = 0 + 0.053 830 2;
  • 2) 0.053 830 2 × 2 = 0 + 0.107 660 4;
  • 3) 0.107 660 4 × 2 = 0 + 0.215 320 8;
  • 4) 0.215 320 8 × 2 = 0 + 0.430 641 6;
  • 5) 0.430 641 6 × 2 = 0 + 0.861 283 2;
  • 6) 0.861 283 2 × 2 = 1 + 0.722 566 4;
  • 7) 0.722 566 4 × 2 = 1 + 0.445 132 8;
  • 8) 0.445 132 8 × 2 = 0 + 0.890 265 6;
  • 9) 0.890 265 6 × 2 = 1 + 0.780 531 2;
  • 10) 0.780 531 2 × 2 = 1 + 0.561 062 4;
  • 11) 0.561 062 4 × 2 = 1 + 0.122 124 8;
  • 12) 0.122 124 8 × 2 = 0 + 0.244 249 6;
  • 13) 0.244 249 6 × 2 = 0 + 0.488 499 2;
  • 14) 0.488 499 2 × 2 = 0 + 0.976 998 4;
  • 15) 0.976 998 4 × 2 = 1 + 0.953 996 8;
  • 16) 0.953 996 8 × 2 = 1 + 0.907 993 6;
  • 17) 0.907 993 6 × 2 = 1 + 0.815 987 2;
  • 18) 0.815 987 2 × 2 = 1 + 0.631 974 4;
  • 19) 0.631 974 4 × 2 = 1 + 0.263 948 8;
  • 20) 0.263 948 8 × 2 = 0 + 0.527 897 6;
  • 21) 0.527 897 6 × 2 = 1 + 0.055 795 2;
  • 22) 0.055 795 2 × 2 = 0 + 0.111 590 4;
  • 23) 0.111 590 4 × 2 = 0 + 0.223 180 8;
  • 24) 0.223 180 8 × 2 = 0 + 0.446 361 6;
  • 25) 0.446 361 6 × 2 = 0 + 0.892 723 2;
  • 26) 0.892 723 2 × 2 = 1 + 0.785 446 4;
  • 27) 0.785 446 4 × 2 = 1 + 0.570 892 8;
  • 28) 0.570 892 8 × 2 = 1 + 0.141 785 6;
  • 29) 0.141 785 6 × 2 = 0 + 0.283 571 2;
  • 30) 0.283 571 2 × 2 = 0 + 0.567 142 4;
  • 31) 0.567 142 4 × 2 = 1 + 0.134 284 8;
  • 32) 0.134 284 8 × 2 = 0 + 0.268 569 6;
  • 33) 0.268 569 6 × 2 = 0 + 0.537 139 2;
  • 34) 0.537 139 2 × 2 = 1 + 0.074 278 4;
  • 35) 0.074 278 4 × 2 = 0 + 0.148 556 8;
  • 36) 0.148 556 8 × 2 = 0 + 0.297 113 6;
  • 37) 0.297 113 6 × 2 = 0 + 0.594 227 2;
  • 38) 0.594 227 2 × 2 = 1 + 0.188 454 4;
  • 39) 0.188 454 4 × 2 = 0 + 0.376 908 8;
  • 40) 0.376 908 8 × 2 = 0 + 0.753 817 6;
  • 41) 0.753 817 6 × 2 = 1 + 0.507 635 2;
  • 42) 0.507 635 2 × 2 = 1 + 0.015 270 4;
  • 43) 0.015 270 4 × 2 = 0 + 0.030 540 8;
  • 44) 0.030 540 8 × 2 = 0 + 0.061 081 6;
  • 45) 0.061 081 6 × 2 = 0 + 0.122 163 2;
  • 46) 0.122 163 2 × 2 = 0 + 0.244 326 4;
  • 47) 0.244 326 4 × 2 = 0 + 0.488 652 8;
  • 48) 0.488 652 8 × 2 = 0 + 0.977 305 6;
  • 49) 0.977 305 6 × 2 = 1 + 0.954 611 2;
  • 50) 0.954 611 2 × 2 = 1 + 0.909 222 4;
  • 51) 0.909 222 4 × 2 = 1 + 0.818 444 8;
  • 52) 0.818 444 8 × 2 = 1 + 0.636 889 6;
  • 53) 0.636 889 6 × 2 = 1 + 0.273 779 2;
  • 54) 0.273 779 2 × 2 = 0 + 0.547 558 4;
  • 55) 0.547 558 4 × 2 = 1 + 0.095 116 8;
  • 56) 0.095 116 8 × 2 = 0 + 0.190 233 6;
  • 57) 0.190 233 6 × 2 = 0 + 0.380 467 2;
  • 58) 0.380 467 2 × 2 = 0 + 0.760 934 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).


4. 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:


0.026 915 1(10) =

0.0000 0110 1110 0011 1110 1000 0111 0010 0100 0100 1100 0000 1111 1010 00(2)

5. Positive number before normalization:

0.026 915 1(10) =

0.0000 0110 1110 0011 1110 1000 0111 0010 0100 0100 1100 0000 1111 1010 00(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 6 positions to the right, so that only one non zero digit remains to the left of it:


0.026 915 1(10) =

0.0000 0110 1110 0011 1110 1000 0111 0010 0100 0100 1100 0000 1111 1010 00(2) =

0.0000 0110 1110 0011 1110 1000 0111 0010 0100 0100 1100 0000 1111 1010 00(2) × 20 =

1.1011 1000 1111 1010 0001 1100 1001 0001 0011 0000 0011 1110 1000(2) × 2-6


7. 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 0 (a positive number)

Exponent (unadjusted): -6

Mantissa (not normalized):
1.1011 1000 1111 1010 0001 1100 1001 0001 0011 0000 0011 1110 1000


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =

Exponent (unadjusted) + 2(11-1) - 1 =

-6 + 2(11-1) - 1 =

(-6 + 1 023)(10) =

1 017(10)


9. 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;
  • 1 017 ÷ 2 = 508 + 1;
  • 508 ÷ 2 = 254 + 0;
  • 254 ÷ 2 = 127 + 0;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

10. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =

1017(10) =

011 1111 1001(2)


11. 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. 1011 1000 1111 1010 0001 1100 1001 0001 0011 0000 0011 1110 1000 =

1011 1000 1111 1010 0001 1100 1001 0001 0011 0000 0011 1110 1000


12. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
0 (a positive number)

Exponent (11 bits) =
011 1111 1001

Mantissa (52 bits) =
1011 1000 1111 1010 0001 1100 1001 0001 0011 0000 0011 1110 1000


Decimal number 0.026 915 1 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1001 - 1011 1000 1111 1010 0001 1100 1001 0001 0011 0000 0011 1110 1000

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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