-0.235 000 000 027 6 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.235 000 000 027 6(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
-0.235 000 000 027 6(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:

|-0.235 000 000 027 6| = 0.235 000 000 027 6


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: 0.235 000 000 027 6.

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) 0.235 000 000 027 6 × 2 = 0 + 0.470 000 000 055 2;
  • 2) 0.470 000 000 055 2 × 2 = 0 + 0.940 000 000 110 4;
  • 3) 0.940 000 000 110 4 × 2 = 1 + 0.880 000 000 220 8;
  • 4) 0.880 000 000 220 8 × 2 = 1 + 0.760 000 000 441 6;
  • 5) 0.760 000 000 441 6 × 2 = 1 + 0.520 000 000 883 2;
  • 6) 0.520 000 000 883 2 × 2 = 1 + 0.040 000 001 766 4;
  • 7) 0.040 000 001 766 4 × 2 = 0 + 0.080 000 003 532 8;
  • 8) 0.080 000 003 532 8 × 2 = 0 + 0.160 000 007 065 6;
  • 9) 0.160 000 007 065 6 × 2 = 0 + 0.320 000 014 131 2;
  • 10) 0.320 000 014 131 2 × 2 = 0 + 0.640 000 028 262 4;
  • 11) 0.640 000 028 262 4 × 2 = 1 + 0.280 000 056 524 8;
  • 12) 0.280 000 056 524 8 × 2 = 0 + 0.560 000 113 049 6;
  • 13) 0.560 000 113 049 6 × 2 = 1 + 0.120 000 226 099 2;
  • 14) 0.120 000 226 099 2 × 2 = 0 + 0.240 000 452 198 4;
  • 15) 0.240 000 452 198 4 × 2 = 0 + 0.480 000 904 396 8;
  • 16) 0.480 000 904 396 8 × 2 = 0 + 0.960 001 808 793 6;
  • 17) 0.960 001 808 793 6 × 2 = 1 + 0.920 003 617 587 2;
  • 18) 0.920 003 617 587 2 × 2 = 1 + 0.840 007 235 174 4;
  • 19) 0.840 007 235 174 4 × 2 = 1 + 0.680 014 470 348 8;
  • 20) 0.680 014 470 348 8 × 2 = 1 + 0.360 028 940 697 6;
  • 21) 0.360 028 940 697 6 × 2 = 0 + 0.720 057 881 395 2;
  • 22) 0.720 057 881 395 2 × 2 = 1 + 0.440 115 762 790 4;
  • 23) 0.440 115 762 790 4 × 2 = 0 + 0.880 231 525 580 8;
  • 24) 0.880 231 525 580 8 × 2 = 1 + 0.760 463 051 161 6;
  • 25) 0.760 463 051 161 6 × 2 = 1 + 0.520 926 102 323 2;
  • 26) 0.520 926 102 323 2 × 2 = 1 + 0.041 852 204 646 4;
  • 27) 0.041 852 204 646 4 × 2 = 0 + 0.083 704 409 292 8;
  • 28) 0.083 704 409 292 8 × 2 = 0 + 0.167 408 818 585 6;
  • 29) 0.167 408 818 585 6 × 2 = 0 + 0.334 817 637 171 2;
  • 30) 0.334 817 637 171 2 × 2 = 0 + 0.669 635 274 342 4;
  • 31) 0.669 635 274 342 4 × 2 = 1 + 0.339 270 548 684 8;
  • 32) 0.339 270 548 684 8 × 2 = 0 + 0.678 541 097 369 6;
  • 33) 0.678 541 097 369 6 × 2 = 1 + 0.357 082 194 739 2;
  • 34) 0.357 082 194 739 2 × 2 = 0 + 0.714 164 389 478 4;
  • 35) 0.714 164 389 478 4 × 2 = 1 + 0.428 328 778 956 8;
  • 36) 0.428 328 778 956 8 × 2 = 0 + 0.856 657 557 913 6;
  • 37) 0.856 657 557 913 6 × 2 = 1 + 0.713 315 115 827 2;
  • 38) 0.713 315 115 827 2 × 2 = 1 + 0.426 630 231 654 4;
  • 39) 0.426 630 231 654 4 × 2 = 0 + 0.853 260 463 308 8;
  • 40) 0.853 260 463 308 8 × 2 = 1 + 0.706 520 926 617 6;
  • 41) 0.706 520 926 617 6 × 2 = 1 + 0.413 041 853 235 2;
  • 42) 0.413 041 853 235 2 × 2 = 0 + 0.826 083 706 470 4;
  • 43) 0.826 083 706 470 4 × 2 = 1 + 0.652 167 412 940 8;
  • 44) 0.652 167 412 940 8 × 2 = 1 + 0.304 334 825 881 6;
  • 45) 0.304 334 825 881 6 × 2 = 0 + 0.608 669 651 763 2;
  • 46) 0.608 669 651 763 2 × 2 = 1 + 0.217 339 303 526 4;
  • 47) 0.217 339 303 526 4 × 2 = 0 + 0.434 678 607 052 8;
  • 48) 0.434 678 607 052 8 × 2 = 0 + 0.869 357 214 105 6;
  • 49) 0.869 357 214 105 6 × 2 = 1 + 0.738 714 428 211 2;
  • 50) 0.738 714 428 211 2 × 2 = 1 + 0.477 428 856 422 4;
  • 51) 0.477 428 856 422 4 × 2 = 0 + 0.954 857 712 844 8;
  • 52) 0.954 857 712 844 8 × 2 = 1 + 0.909 715 425 689 6;
  • 53) 0.909 715 425 689 6 × 2 = 1 + 0.819 430 851 379 2;
  • 54) 0.819 430 851 379 2 × 2 = 1 + 0.638 861 702 758 4;
  • 55) 0.638 861 702 758 4 × 2 = 1 + 0.277 723 405 516 8;

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:


0.235 000 000 027 6(10) =


0.0011 1100 0010 1000 1111 0101 1100 0010 1010 1101 1011 0100 1101 111(2)

6. Positive number before normalization:

0.235 000 000 027 6(10) =


0.0011 1100 0010 1000 1111 0101 1100 0010 1010 1101 1011 0100 1101 111(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 3 positions to the right, so that only one non zero digit remains to the left of it:


0.235 000 000 027 6(10) =


0.0011 1100 0010 1000 1111 0101 1100 0010 1010 1101 1011 0100 1101 111(2) =


0.0011 1100 0010 1000 1111 0101 1100 0010 1010 1101 1011 0100 1101 111(2) × 20 =


1.1110 0001 0100 0111 1010 1110 0001 0101 0110 1101 1010 0110 1111(2) × 2-3


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): -3


Mantissa (not normalized):
1.1110 0001 0100 0111 1010 1110 0001 0101 0110 1101 1010 0110 1111


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-3 + 2(11-1) - 1 =


(-3 + 1 023)(10) =


1 020(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;
  • 1 020 ÷ 2 = 510 + 0;
  • 510 ÷ 2 = 255 + 0;
  • 255 ÷ 2 = 127 + 1;
  • 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;

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) =


1020(10) =


011 1111 1100(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. 1110 0001 0100 0111 1010 1110 0001 0101 0110 1101 1010 0110 1111 =


1110 0001 0100 0111 1010 1110 0001 0101 0110 1101 1010 0110 1111


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 1100


Mantissa (52 bits) =
1110 0001 0100 0111 1010 1110 0001 0101 0110 1101 1010 0110 1111


Decimal number -0.235 000 000 027 6 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1100 - 1110 0001 0100 0111 1010 1110 0001 0101 0110 1101 1010 0110 1111

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