-532.234 275 078 342 3 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -532.234 275 078 342 3(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
-532.234 275 078 342 3(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:

|-532.234 275 078 342 3| = 532.234 275 078 342 3


2. First, convert to binary (in base 2) the integer part: 532.
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;
  • 532 ÷ 2 = 266 + 0;
  • 266 ÷ 2 = 133 + 0;
  • 133 ÷ 2 = 66 + 1;
  • 66 ÷ 2 = 33 + 0;
  • 33 ÷ 2 = 16 + 1;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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.

532(10) =


10 0001 0100(2)


4. Convert to binary (base 2) the fractional part: 0.234 275 078 342 3.

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) 0.234 275 078 342 3 × 2 = 0 + 0.468 550 156 684 6;
  • 2) 0.468 550 156 684 6 × 2 = 0 + 0.937 100 313 369 2;
  • 3) 0.937 100 313 369 2 × 2 = 1 + 0.874 200 626 738 4;
  • 4) 0.874 200 626 738 4 × 2 = 1 + 0.748 401 253 476 8;
  • 5) 0.748 401 253 476 8 × 2 = 1 + 0.496 802 506 953 6;
  • 6) 0.496 802 506 953 6 × 2 = 0 + 0.993 605 013 907 2;
  • 7) 0.993 605 013 907 2 × 2 = 1 + 0.987 210 027 814 4;
  • 8) 0.987 210 027 814 4 × 2 = 1 + 0.974 420 055 628 8;
  • 9) 0.974 420 055 628 8 × 2 = 1 + 0.948 840 111 257 6;
  • 10) 0.948 840 111 257 6 × 2 = 1 + 0.897 680 222 515 2;
  • 11) 0.897 680 222 515 2 × 2 = 1 + 0.795 360 445 030 4;
  • 12) 0.795 360 445 030 4 × 2 = 1 + 0.590 720 890 060 8;
  • 13) 0.590 720 890 060 8 × 2 = 1 + 0.181 441 780 121 6;
  • 14) 0.181 441 780 121 6 × 2 = 0 + 0.362 883 560 243 2;
  • 15) 0.362 883 560 243 2 × 2 = 0 + 0.725 767 120 486 4;
  • 16) 0.725 767 120 486 4 × 2 = 1 + 0.451 534 240 972 8;
  • 17) 0.451 534 240 972 8 × 2 = 0 + 0.903 068 481 945 6;
  • 18) 0.903 068 481 945 6 × 2 = 1 + 0.806 136 963 891 2;
  • 19) 0.806 136 963 891 2 × 2 = 1 + 0.612 273 927 782 4;
  • 20) 0.612 273 927 782 4 × 2 = 1 + 0.224 547 855 564 8;
  • 21) 0.224 547 855 564 8 × 2 = 0 + 0.449 095 711 129 6;
  • 22) 0.449 095 711 129 6 × 2 = 0 + 0.898 191 422 259 2;
  • 23) 0.898 191 422 259 2 × 2 = 1 + 0.796 382 844 518 4;
  • 24) 0.796 382 844 518 4 × 2 = 1 + 0.592 765 689 036 8;
  • 25) 0.592 765 689 036 8 × 2 = 1 + 0.185 531 378 073 6;
  • 26) 0.185 531 378 073 6 × 2 = 0 + 0.371 062 756 147 2;
  • 27) 0.371 062 756 147 2 × 2 = 0 + 0.742 125 512 294 4;
  • 28) 0.742 125 512 294 4 × 2 = 1 + 0.484 251 024 588 8;
  • 29) 0.484 251 024 588 8 × 2 = 0 + 0.968 502 049 177 6;
  • 30) 0.968 502 049 177 6 × 2 = 1 + 0.937 004 098 355 2;
  • 31) 0.937 004 098 355 2 × 2 = 1 + 0.874 008 196 710 4;
  • 32) 0.874 008 196 710 4 × 2 = 1 + 0.748 016 393 420 8;
  • 33) 0.748 016 393 420 8 × 2 = 1 + 0.496 032 786 841 6;
  • 34) 0.496 032 786 841 6 × 2 = 0 + 0.992 065 573 683 2;
  • 35) 0.992 065 573 683 2 × 2 = 1 + 0.984 131 147 366 4;
  • 36) 0.984 131 147 366 4 × 2 = 1 + 0.968 262 294 732 8;
  • 37) 0.968 262 294 732 8 × 2 = 1 + 0.936 524 589 465 6;
  • 38) 0.936 524 589 465 6 × 2 = 1 + 0.873 049 178 931 2;
  • 39) 0.873 049 178 931 2 × 2 = 1 + 0.746 098 357 862 4;
  • 40) 0.746 098 357 862 4 × 2 = 1 + 0.492 196 715 724 8;
  • 41) 0.492 196 715 724 8 × 2 = 0 + 0.984 393 431 449 6;
  • 42) 0.984 393 431 449 6 × 2 = 1 + 0.968 786 862 899 2;
  • 43) 0.968 786 862 899 2 × 2 = 1 + 0.937 573 725 798 4;
  • 44) 0.937 573 725 798 4 × 2 = 1 + 0.875 147 451 596 8;
  • 45) 0.875 147 451 596 8 × 2 = 1 + 0.750 294 903 193 6;
  • 46) 0.750 294 903 193 6 × 2 = 1 + 0.500 589 806 387 2;
  • 47) 0.500 589 806 387 2 × 2 = 1 + 0.001 179 612 774 4;
  • 48) 0.001 179 612 774 4 × 2 = 0 + 0.002 359 225 548 8;
  • 49) 0.002 359 225 548 8 × 2 = 0 + 0.004 718 451 097 6;
  • 50) 0.004 718 451 097 6 × 2 = 0 + 0.009 436 902 195 2;
  • 51) 0.009 436 902 195 2 × 2 = 0 + 0.018 873 804 390 4;
  • 52) 0.018 873 804 390 4 × 2 = 0 + 0.037 747 608 780 8;
  • 53) 0.037 747 608 780 8 × 2 = 0 + 0.075 495 217 561 6;

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:


0.234 275 078 342 3(10) =


0.0011 1011 1111 1001 0111 0011 1001 0111 1011 1111 0111 1110 0000 0(2)

6. Positive number before normalization:

532.234 275 078 342 3(10) =


10 0001 0100.0011 1011 1111 1001 0111 0011 1001 0111 1011 1111 0111 1110 0000 0(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 9 positions to the left, so that only one non zero digit remains to the left of it:


532.234 275 078 342 3(10) =


10 0001 0100.0011 1011 1111 1001 0111 0011 1001 0111 1011 1111 0111 1110 0000 0(2) =


10 0001 0100.0011 1011 1111 1001 0111 0011 1001 0111 1011 1111 0111 1110 0000 0(2) × 20 =


1.0000 1010 0001 1101 1111 1100 1011 1001 1100 1011 1101 1111 1011 1111 0000 00(2) × 29


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): 9


Mantissa (not normalized):
1.0000 1010 0001 1101 1111 1100 1011 1001 1100 1011 1101 1111 1011 1111 0000 00


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


9 + 2(11-1) - 1 =


(9 + 1 023)(10) =


1 032(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;
  • 1 032 ÷ 2 = 516 + 0;
  • 516 ÷ 2 = 258 + 0;
  • 258 ÷ 2 = 129 + 0;
  • 129 ÷ 2 = 64 + 1;
  • 64 ÷ 2 = 32 + 0;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 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) =


1032(10) =


100 0000 1000(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, 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. 0000 1010 0001 1101 1111 1100 1011 1001 1100 1011 1101 1111 1011 11 1100 0000 =


0000 1010 0001 1101 1111 1100 1011 1001 1100 1011 1101 1111 1011


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) =
100 0000 1000


Mantissa (52 bits) =
0000 1010 0001 1101 1111 1100 1011 1001 1100 1011 1101 1111 1011


Decimal number -532.234 275 078 342 3 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 1000 - 0000 1010 0001 1101 1111 1100 1011 1001 1100 1011 1101 1111 1011


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