-24.901 900 000 000 004 5 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -24.901 900 000 000 004 5(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 5(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 5| = 24.901 900 000 000 004 5


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 5.

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 5 × 2 = 1 + 0.803 800 000 000 009;
  • 2) 0.803 800 000 000 009 × 2 = 1 + 0.607 600 000 000 018;
  • 3) 0.607 600 000 000 018 × 2 = 1 + 0.215 200 000 000 036;
  • 4) 0.215 200 000 000 036 × 2 = 0 + 0.430 400 000 000 072;
  • 5) 0.430 400 000 000 072 × 2 = 0 + 0.860 800 000 000 144;
  • 6) 0.860 800 000 000 144 × 2 = 1 + 0.721 600 000 000 288;
  • 7) 0.721 600 000 000 288 × 2 = 1 + 0.443 200 000 000 576;
  • 8) 0.443 200 000 000 576 × 2 = 0 + 0.886 400 000 001 152;
  • 9) 0.886 400 000 001 152 × 2 = 1 + 0.772 800 000 002 304;
  • 10) 0.772 800 000 002 304 × 2 = 1 + 0.545 600 000 004 608;
  • 11) 0.545 600 000 004 608 × 2 = 1 + 0.091 200 000 009 216;
  • 12) 0.091 200 000 009 216 × 2 = 0 + 0.182 400 000 018 432;
  • 13) 0.182 400 000 018 432 × 2 = 0 + 0.364 800 000 036 864;
  • 14) 0.364 800 000 036 864 × 2 = 0 + 0.729 600 000 073 728;
  • 15) 0.729 600 000 073 728 × 2 = 1 + 0.459 200 000 147 456;
  • 16) 0.459 200 000 147 456 × 2 = 0 + 0.918 400 000 294 912;
  • 17) 0.918 400 000 294 912 × 2 = 1 + 0.836 800 000 589 824;
  • 18) 0.836 800 000 589 824 × 2 = 1 + 0.673 600 001 179 648;
  • 19) 0.673 600 001 179 648 × 2 = 1 + 0.347 200 002 359 296;
  • 20) 0.347 200 002 359 296 × 2 = 0 + 0.694 400 004 718 592;
  • 21) 0.694 400 004 718 592 × 2 = 1 + 0.388 800 009 437 184;
  • 22) 0.388 800 009 437 184 × 2 = 0 + 0.777 600 018 874 368;
  • 23) 0.777 600 018 874 368 × 2 = 1 + 0.555 200 037 748 736;
  • 24) 0.555 200 037 748 736 × 2 = 1 + 0.110 400 075 497 472;
  • 25) 0.110 400 075 497 472 × 2 = 0 + 0.220 800 150 994 944;
  • 26) 0.220 800 150 994 944 × 2 = 0 + 0.441 600 301 989 888;
  • 27) 0.441 600 301 989 888 × 2 = 0 + 0.883 200 603 979 776;
  • 28) 0.883 200 603 979 776 × 2 = 1 + 0.766 401 207 959 552;
  • 29) 0.766 401 207 959 552 × 2 = 1 + 0.532 802 415 919 104;
  • 30) 0.532 802 415 919 104 × 2 = 1 + 0.065 604 831 838 208;
  • 31) 0.065 604 831 838 208 × 2 = 0 + 0.131 209 663 676 416;
  • 32) 0.131 209 663 676 416 × 2 = 0 + 0.262 419 327 352 832;
  • 33) 0.262 419 327 352 832 × 2 = 0 + 0.524 838 654 705 664;
  • 34) 0.524 838 654 705 664 × 2 = 1 + 0.049 677 309 411 328;
  • 35) 0.049 677 309 411 328 × 2 = 0 + 0.099 354 618 822 656;
  • 36) 0.099 354 618 822 656 × 2 = 0 + 0.198 709 237 645 312;
  • 37) 0.198 709 237 645 312 × 2 = 0 + 0.397 418 475 290 624;
  • 38) 0.397 418 475 290 624 × 2 = 0 + 0.794 836 950 581 248;
  • 39) 0.794 836 950 581 248 × 2 = 1 + 0.589 673 901 162 496;
  • 40) 0.589 673 901 162 496 × 2 = 1 + 0.179 347 802 324 992;
  • 41) 0.179 347 802 324 992 × 2 = 0 + 0.358 695 604 649 984;
  • 42) 0.358 695 604 649 984 × 2 = 0 + 0.717 391 209 299 968;
  • 43) 0.717 391 209 299 968 × 2 = 1 + 0.434 782 418 599 936;
  • 44) 0.434 782 418 599 936 × 2 = 0 + 0.869 564 837 199 872;
  • 45) 0.869 564 837 199 872 × 2 = 1 + 0.739 129 674 399 744;
  • 46) 0.739 129 674 399 744 × 2 = 1 + 0.478 259 348 799 488;
  • 47) 0.478 259 348 799 488 × 2 = 0 + 0.956 518 697 598 976;
  • 48) 0.956 518 697 598 976 × 2 = 1 + 0.913 037 395 197 952;
  • 49) 0.913 037 395 197 952 × 2 = 1 + 0.826 074 790 395 904;
  • 50) 0.826 074 790 395 904 × 2 = 1 + 0.652 149 580 791 808;
  • 51) 0.652 149 580 791 808 × 2 = 1 + 0.304 299 161 583 616;
  • 52) 0.304 299 161 583 616 × 2 = 0 + 0.608 598 323 167 232;
  • 53) 0.608 598 323 167 232 × 2 = 1 + 0.217 196 646 334 464;

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 5(10) =


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

6. Positive number before normalization:

24.901 900 000 000 004 5(10) =


1 1000.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1101 1110 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 5(10) =


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


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


1.1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1101 1110 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 1110 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 1101 =


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 5 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