148 592 304.999 358 31 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 148 592 304.999 358 31(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
148 592 304.999 358 31(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: 148 592 304.
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;
  • 148 592 304 ÷ 2 = 74 296 152 + 0;
  • 74 296 152 ÷ 2 = 37 148 076 + 0;
  • 37 148 076 ÷ 2 = 18 574 038 + 0;
  • 18 574 038 ÷ 2 = 9 287 019 + 0;
  • 9 287 019 ÷ 2 = 4 643 509 + 1;
  • 4 643 509 ÷ 2 = 2 321 754 + 1;
  • 2 321 754 ÷ 2 = 1 160 877 + 0;
  • 1 160 877 ÷ 2 = 580 438 + 1;
  • 580 438 ÷ 2 = 290 219 + 0;
  • 290 219 ÷ 2 = 145 109 + 1;
  • 145 109 ÷ 2 = 72 554 + 1;
  • 72 554 ÷ 2 = 36 277 + 0;
  • 36 277 ÷ 2 = 18 138 + 1;
  • 18 138 ÷ 2 = 9 069 + 0;
  • 9 069 ÷ 2 = 4 534 + 1;
  • 4 534 ÷ 2 = 2 267 + 0;
  • 2 267 ÷ 2 = 1 133 + 1;
  • 1 133 ÷ 2 = 566 + 1;
  • 566 ÷ 2 = 283 + 0;
  • 283 ÷ 2 = 141 + 1;
  • 141 ÷ 2 = 70 + 1;
  • 70 ÷ 2 = 35 + 0;
  • 35 ÷ 2 = 17 + 1;
  • 17 ÷ 2 = 8 + 1;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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.

148 592 304(10) =


1000 1101 1011 0101 0110 1011 0000(2)


3. Convert to binary (base 2) the fractional part: 0.999 358 31.

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) 0.999 358 31 × 2 = 1 + 0.998 716 62;
  • 2) 0.998 716 62 × 2 = 1 + 0.997 433 24;
  • 3) 0.997 433 24 × 2 = 1 + 0.994 866 48;
  • 4) 0.994 866 48 × 2 = 1 + 0.989 732 96;
  • 5) 0.989 732 96 × 2 = 1 + 0.979 465 92;
  • 6) 0.979 465 92 × 2 = 1 + 0.958 931 84;
  • 7) 0.958 931 84 × 2 = 1 + 0.917 863 68;
  • 8) 0.917 863 68 × 2 = 1 + 0.835 727 36;
  • 9) 0.835 727 36 × 2 = 1 + 0.671 454 72;
  • 10) 0.671 454 72 × 2 = 1 + 0.342 909 44;
  • 11) 0.342 909 44 × 2 = 0 + 0.685 818 88;
  • 12) 0.685 818 88 × 2 = 1 + 0.371 637 76;
  • 13) 0.371 637 76 × 2 = 0 + 0.743 275 52;
  • 14) 0.743 275 52 × 2 = 1 + 0.486 551 04;
  • 15) 0.486 551 04 × 2 = 0 + 0.973 102 08;
  • 16) 0.973 102 08 × 2 = 1 + 0.946 204 16;
  • 17) 0.946 204 16 × 2 = 1 + 0.892 408 32;
  • 18) 0.892 408 32 × 2 = 1 + 0.784 816 64;
  • 19) 0.784 816 64 × 2 = 1 + 0.569 633 28;
  • 20) 0.569 633 28 × 2 = 1 + 0.139 266 56;
  • 21) 0.139 266 56 × 2 = 0 + 0.278 533 12;
  • 22) 0.278 533 12 × 2 = 0 + 0.557 066 24;
  • 23) 0.557 066 24 × 2 = 1 + 0.114 132 48;
  • 24) 0.114 132 48 × 2 = 0 + 0.228 264 96;
  • 25) 0.228 264 96 × 2 = 0 + 0.456 529 92;
  • 26) 0.456 529 92 × 2 = 0 + 0.913 059 84;
  • 27) 0.913 059 84 × 2 = 1 + 0.826 119 68;
  • 28) 0.826 119 68 × 2 = 1 + 0.652 239 36;
  • 29) 0.652 239 36 × 2 = 1 + 0.304 478 72;
  • 30) 0.304 478 72 × 2 = 0 + 0.608 957 44;
  • 31) 0.608 957 44 × 2 = 1 + 0.217 914 88;
  • 32) 0.217 914 88 × 2 = 0 + 0.435 829 76;
  • 33) 0.435 829 76 × 2 = 0 + 0.871 659 52;
  • 34) 0.871 659 52 × 2 = 1 + 0.743 319 04;
  • 35) 0.743 319 04 × 2 = 1 + 0.486 638 08;
  • 36) 0.486 638 08 × 2 = 0 + 0.973 276 16;
  • 37) 0.973 276 16 × 2 = 1 + 0.946 552 32;
  • 38) 0.946 552 32 × 2 = 1 + 0.893 104 64;
  • 39) 0.893 104 64 × 2 = 1 + 0.786 209 28;
  • 40) 0.786 209 28 × 2 = 1 + 0.572 418 56;
  • 41) 0.572 418 56 × 2 = 1 + 0.144 837 12;
  • 42) 0.144 837 12 × 2 = 0 + 0.289 674 24;
  • 43) 0.289 674 24 × 2 = 0 + 0.579 348 48;
  • 44) 0.579 348 48 × 2 = 1 + 0.158 696 96;
  • 45) 0.158 696 96 × 2 = 0 + 0.317 393 92;
  • 46) 0.317 393 92 × 2 = 0 + 0.634 787 84;
  • 47) 0.634 787 84 × 2 = 1 + 0.269 575 68;
  • 48) 0.269 575 68 × 2 = 0 + 0.539 151 36;
  • 49) 0.539 151 36 × 2 = 1 + 0.078 302 72;
  • 50) 0.078 302 72 × 2 = 0 + 0.156 605 44;
  • 51) 0.156 605 44 × 2 = 0 + 0.313 210 88;
  • 52) 0.313 210 88 × 2 = 0 + 0.626 421 76;
  • 53) 0.626 421 76 × 2 = 1 + 0.252 843 52;

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:


0.999 358 31(10) =


0.1111 1111 1101 0101 1111 0010 0011 1010 0110 1111 1001 0010 1000 1(2)

5. Positive number before normalization:

148 592 304.999 358 31(10) =


1000 1101 1011 0101 0110 1011 0000.1111 1111 1101 0101 1111 0010 0011 1010 0110 1111 1001 0010 1000 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 27 positions to the left, so that only one non zero digit remains to the left of it:


148 592 304.999 358 31(10) =


1000 1101 1011 0101 0110 1011 0000.1111 1111 1101 0101 1111 0010 0011 1010 0110 1111 1001 0010 1000 1(2) =


1000 1101 1011 0101 0110 1011 0000.1111 1111 1101 0101 1111 0010 0011 1010 0110 1111 1001 0010 1000 1(2) × 20 =


1.0001 1011 0110 1010 1101 0110 0001 1111 1111 1010 1011 1110 0100 0111 0100 1101 1111 0010 0101 0001(2) × 227


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): 27


Mantissa (not normalized):
1.0001 1011 0110 1010 1101 0110 0001 1111 1111 1010 1011 1110 0100 0111 0100 1101 1111 0010 0101 0001


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


27 + 2(11-1) - 1 =


(27 + 1 023)(10) =


1 050(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;
  • 1 050 ÷ 2 = 525 + 0;
  • 525 ÷ 2 = 262 + 1;
  • 262 ÷ 2 = 131 + 0;
  • 131 ÷ 2 = 65 + 1;
  • 65 ÷ 2 = 32 + 1;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 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) =


1050(10) =


100 0001 1010(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, by removing the excess bits, from the right (if any of the excess bits is set on 1, we are losing precision...).


Mantissa (normalized) =


1. 0001 1011 0110 1010 1101 0110 0001 1111 1111 1010 1011 1110 0100 0111 0100 1101 1111 0010 0101 0001 =


0001 1011 0110 1010 1101 0110 0001 1111 1111 1010 1011 1110 0100


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) =
100 0001 1010


Mantissa (52 bits) =
0001 1011 0110 1010 1101 0110 0001 1111 1111 1010 1011 1110 0100


Decimal number 148 592 304.999 358 31 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0001 1010 - 0001 1011 0110 1010 1101 0110 0001 1111 1111 1010 1011 1110 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