-24.901 900 000 000 004 1 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -24.901 900 000 000 004 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
-24.901 900 000 000 004 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. Start with the positive version of the number:

|-24.901 900 000 000 004 1| = 24.901 900 000 000 004 1


2. First, convert to binary (in base 2) the integer part: 24.
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;
  • 24 ÷ 2 = 12 + 0;
  • 12 ÷ 2 = 6 + 0;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 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.

24(10) =


1 1000(2)


4. Convert to binary (base 2) the fractional part: 0.901 900 000 000 004 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) 0.901 900 000 000 004 1 × 2 = 1 + 0.803 800 000 000 008 2;
  • 2) 0.803 800 000 000 008 2 × 2 = 1 + 0.607 600 000 000 016 4;
  • 3) 0.607 600 000 000 016 4 × 2 = 1 + 0.215 200 000 000 032 8;
  • 4) 0.215 200 000 000 032 8 × 2 = 0 + 0.430 400 000 000 065 6;
  • 5) 0.430 400 000 000 065 6 × 2 = 0 + 0.860 800 000 000 131 2;
  • 6) 0.860 800 000 000 131 2 × 2 = 1 + 0.721 600 000 000 262 4;
  • 7) 0.721 600 000 000 262 4 × 2 = 1 + 0.443 200 000 000 524 8;
  • 8) 0.443 200 000 000 524 8 × 2 = 0 + 0.886 400 000 001 049 6;
  • 9) 0.886 400 000 001 049 6 × 2 = 1 + 0.772 800 000 002 099 2;
  • 10) 0.772 800 000 002 099 2 × 2 = 1 + 0.545 600 000 004 198 4;
  • 11) 0.545 600 000 004 198 4 × 2 = 1 + 0.091 200 000 008 396 8;
  • 12) 0.091 200 000 008 396 8 × 2 = 0 + 0.182 400 000 016 793 6;
  • 13) 0.182 400 000 016 793 6 × 2 = 0 + 0.364 800 000 033 587 2;
  • 14) 0.364 800 000 033 587 2 × 2 = 0 + 0.729 600 000 067 174 4;
  • 15) 0.729 600 000 067 174 4 × 2 = 1 + 0.459 200 000 134 348 8;
  • 16) 0.459 200 000 134 348 8 × 2 = 0 + 0.918 400 000 268 697 6;
  • 17) 0.918 400 000 268 697 6 × 2 = 1 + 0.836 800 000 537 395 2;
  • 18) 0.836 800 000 537 395 2 × 2 = 1 + 0.673 600 001 074 790 4;
  • 19) 0.673 600 001 074 790 4 × 2 = 1 + 0.347 200 002 149 580 8;
  • 20) 0.347 200 002 149 580 8 × 2 = 0 + 0.694 400 004 299 161 6;
  • 21) 0.694 400 004 299 161 6 × 2 = 1 + 0.388 800 008 598 323 2;
  • 22) 0.388 800 008 598 323 2 × 2 = 0 + 0.777 600 017 196 646 4;
  • 23) 0.777 600 017 196 646 4 × 2 = 1 + 0.555 200 034 393 292 8;
  • 24) 0.555 200 034 393 292 8 × 2 = 1 + 0.110 400 068 786 585 6;
  • 25) 0.110 400 068 786 585 6 × 2 = 0 + 0.220 800 137 573 171 2;
  • 26) 0.220 800 137 573 171 2 × 2 = 0 + 0.441 600 275 146 342 4;
  • 27) 0.441 600 275 146 342 4 × 2 = 0 + 0.883 200 550 292 684 8;
  • 28) 0.883 200 550 292 684 8 × 2 = 1 + 0.766 401 100 585 369 6;
  • 29) 0.766 401 100 585 369 6 × 2 = 1 + 0.532 802 201 170 739 2;
  • 30) 0.532 802 201 170 739 2 × 2 = 1 + 0.065 604 402 341 478 4;
  • 31) 0.065 604 402 341 478 4 × 2 = 0 + 0.131 208 804 682 956 8;
  • 32) 0.131 208 804 682 956 8 × 2 = 0 + 0.262 417 609 365 913 6;
  • 33) 0.262 417 609 365 913 6 × 2 = 0 + 0.524 835 218 731 827 2;
  • 34) 0.524 835 218 731 827 2 × 2 = 1 + 0.049 670 437 463 654 4;
  • 35) 0.049 670 437 463 654 4 × 2 = 0 + 0.099 340 874 927 308 8;
  • 36) 0.099 340 874 927 308 8 × 2 = 0 + 0.198 681 749 854 617 6;
  • 37) 0.198 681 749 854 617 6 × 2 = 0 + 0.397 363 499 709 235 2;
  • 38) 0.397 363 499 709 235 2 × 2 = 0 + 0.794 726 999 418 470 4;
  • 39) 0.794 726 999 418 470 4 × 2 = 1 + 0.589 453 998 836 940 8;
  • 40) 0.589 453 998 836 940 8 × 2 = 1 + 0.178 907 997 673 881 6;
  • 41) 0.178 907 997 673 881 6 × 2 = 0 + 0.357 815 995 347 763 2;
  • 42) 0.357 815 995 347 763 2 × 2 = 0 + 0.715 631 990 695 526 4;
  • 43) 0.715 631 990 695 526 4 × 2 = 1 + 0.431 263 981 391 052 8;
  • 44) 0.431 263 981 391 052 8 × 2 = 0 + 0.862 527 962 782 105 6;
  • 45) 0.862 527 962 782 105 6 × 2 = 1 + 0.725 055 925 564 211 2;
  • 46) 0.725 055 925 564 211 2 × 2 = 1 + 0.450 111 851 128 422 4;
  • 47) 0.450 111 851 128 422 4 × 2 = 0 + 0.900 223 702 256 844 8;
  • 48) 0.900 223 702 256 844 8 × 2 = 1 + 0.800 447 404 513 689 6;
  • 49) 0.800 447 404 513 689 6 × 2 = 1 + 0.600 894 809 027 379 2;
  • 50) 0.600 894 809 027 379 2 × 2 = 1 + 0.201 789 618 054 758 4;
  • 51) 0.201 789 618 054 758 4 × 2 = 0 + 0.403 579 236 109 516 8;
  • 52) 0.403 579 236 109 516 8 × 2 = 0 + 0.807 158 472 219 033 6;
  • 53) 0.807 158 472 219 033 6 × 2 = 1 + 0.614 316 944 438 067 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:


0.901 900 000 000 004 1(10) =


0.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1101 1100 1(2)

6. Positive number before normalization:

24.901 900 000 000 004 1(10) =


1 1000.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1101 1100 1(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 4 positions to the left, so that only one non zero digit remains to the left of it:


24.901 900 000 000 004 1(10) =


1 1000.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1101 1100 1(2) =


1 1000.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1101 1100 1(2) × 20 =


1.1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1101 1100 1(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):
1.1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1101 1100 1


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


4 + 2(11-1) - 1 =


(4 + 1 023)(10) =


1 027(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;
  • 1 027 ÷ 2 = 513 + 1;
  • 513 ÷ 2 = 256 + 1;
  • 256 ÷ 2 = 128 + 0;
  • 128 ÷ 2 = 64 + 0;
  • 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) =


1027(10) =


100 0000 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, 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. 1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1101 1 1001 =


1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1101


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 0011


Mantissa (52 bits) =
1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1101


Decimal number -24.901 900 000 000 004 1 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 0011 - 1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1101


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