-17.783 247 610 916 9 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -17.783 247 610 916 9(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
-17.783 247 610 916 9(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:

|-17.783 247 610 916 9| = 17.783 247 610 916 9


2. First, convert to binary (in base 2) the integer part: 17.
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;
  • 17 ÷ 2 = 8 + 1;
  • 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.

17(10) =


1 0001(2)


4. Convert to binary (base 2) the fractional part: 0.783 247 610 916 9.

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) 0.783 247 610 916 9 × 2 = 1 + 0.566 495 221 833 8;
  • 2) 0.566 495 221 833 8 × 2 = 1 + 0.132 990 443 667 6;
  • 3) 0.132 990 443 667 6 × 2 = 0 + 0.265 980 887 335 2;
  • 4) 0.265 980 887 335 2 × 2 = 0 + 0.531 961 774 670 4;
  • 5) 0.531 961 774 670 4 × 2 = 1 + 0.063 923 549 340 8;
  • 6) 0.063 923 549 340 8 × 2 = 0 + 0.127 847 098 681 6;
  • 7) 0.127 847 098 681 6 × 2 = 0 + 0.255 694 197 363 2;
  • 8) 0.255 694 197 363 2 × 2 = 0 + 0.511 388 394 726 4;
  • 9) 0.511 388 394 726 4 × 2 = 1 + 0.022 776 789 452 8;
  • 10) 0.022 776 789 452 8 × 2 = 0 + 0.045 553 578 905 6;
  • 11) 0.045 553 578 905 6 × 2 = 0 + 0.091 107 157 811 2;
  • 12) 0.091 107 157 811 2 × 2 = 0 + 0.182 214 315 622 4;
  • 13) 0.182 214 315 622 4 × 2 = 0 + 0.364 428 631 244 8;
  • 14) 0.364 428 631 244 8 × 2 = 0 + 0.728 857 262 489 6;
  • 15) 0.728 857 262 489 6 × 2 = 1 + 0.457 714 524 979 2;
  • 16) 0.457 714 524 979 2 × 2 = 0 + 0.915 429 049 958 4;
  • 17) 0.915 429 049 958 4 × 2 = 1 + 0.830 858 099 916 8;
  • 18) 0.830 858 099 916 8 × 2 = 1 + 0.661 716 199 833 6;
  • 19) 0.661 716 199 833 6 × 2 = 1 + 0.323 432 399 667 2;
  • 20) 0.323 432 399 667 2 × 2 = 0 + 0.646 864 799 334 4;
  • 21) 0.646 864 799 334 4 × 2 = 1 + 0.293 729 598 668 8;
  • 22) 0.293 729 598 668 8 × 2 = 0 + 0.587 459 197 337 6;
  • 23) 0.587 459 197 337 6 × 2 = 1 + 0.174 918 394 675 2;
  • 24) 0.174 918 394 675 2 × 2 = 0 + 0.349 836 789 350 4;
  • 25) 0.349 836 789 350 4 × 2 = 0 + 0.699 673 578 700 8;
  • 26) 0.699 673 578 700 8 × 2 = 1 + 0.399 347 157 401 6;
  • 27) 0.399 347 157 401 6 × 2 = 0 + 0.798 694 314 803 2;
  • 28) 0.798 694 314 803 2 × 2 = 1 + 0.597 388 629 606 4;
  • 29) 0.597 388 629 606 4 × 2 = 1 + 0.194 777 259 212 8;
  • 30) 0.194 777 259 212 8 × 2 = 0 + 0.389 554 518 425 6;
  • 31) 0.389 554 518 425 6 × 2 = 0 + 0.779 109 036 851 2;
  • 32) 0.779 109 036 851 2 × 2 = 1 + 0.558 218 073 702 4;
  • 33) 0.558 218 073 702 4 × 2 = 1 + 0.116 436 147 404 8;
  • 34) 0.116 436 147 404 8 × 2 = 0 + 0.232 872 294 809 6;
  • 35) 0.232 872 294 809 6 × 2 = 0 + 0.465 744 589 619 2;
  • 36) 0.465 744 589 619 2 × 2 = 0 + 0.931 489 179 238 4;
  • 37) 0.931 489 179 238 4 × 2 = 1 + 0.862 978 358 476 8;
  • 38) 0.862 978 358 476 8 × 2 = 1 + 0.725 956 716 953 6;
  • 39) 0.725 956 716 953 6 × 2 = 1 + 0.451 913 433 907 2;
  • 40) 0.451 913 433 907 2 × 2 = 0 + 0.903 826 867 814 4;
  • 41) 0.903 826 867 814 4 × 2 = 1 + 0.807 653 735 628 8;
  • 42) 0.807 653 735 628 8 × 2 = 1 + 0.615 307 471 257 6;
  • 43) 0.615 307 471 257 6 × 2 = 1 + 0.230 614 942 515 2;
  • 44) 0.230 614 942 515 2 × 2 = 0 + 0.461 229 885 030 4;
  • 45) 0.461 229 885 030 4 × 2 = 0 + 0.922 459 770 060 8;
  • 46) 0.922 459 770 060 8 × 2 = 1 + 0.844 919 540 121 6;
  • 47) 0.844 919 540 121 6 × 2 = 1 + 0.689 839 080 243 2;
  • 48) 0.689 839 080 243 2 × 2 = 1 + 0.379 678 160 486 4;
  • 49) 0.379 678 160 486 4 × 2 = 0 + 0.759 356 320 972 8;
  • 50) 0.759 356 320 972 8 × 2 = 1 + 0.518 712 641 945 6;
  • 51) 0.518 712 641 945 6 × 2 = 1 + 0.037 425 283 891 2;
  • 52) 0.037 425 283 891 2 × 2 = 0 + 0.074 850 567 782 4;
  • 53) 0.074 850 567 782 4 × 2 = 0 + 0.149 701 135 564 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:


0.783 247 610 916 9(10) =


0.1100 1000 1000 0010 1110 1010 0101 1001 1000 1110 1110 0111 0110 0(2)

6. Positive number before normalization:

17.783 247 610 916 9(10) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1000 1110 1110 0111 0110 0(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:


17.783 247 610 916 9(10) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1000 1110 1110 0111 0110 0(2) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1000 1110 1110 0111 0110 0(2) × 20 =


1.0001 1100 1000 1000 0010 1110 1010 0101 1001 1000 1110 1110 0111 0110 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):
1.0001 1100 1000 1000 0010 1110 1010 0101 1001 1000 1110 1110 0111 0110 0


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. 0001 1100 1000 1000 0010 1110 1010 0101 1001 1000 1110 1110 0111 0 1100 =


0001 1100 1000 1000 0010 1110 1010 0101 1001 1000 1110 1110 0111


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) =
0001 1100 1000 1000 0010 1110 1010 0101 1001 1000 1110 1110 0111


Decimal number -17.783 247 610 916 9 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 0011 - 0001 1100 1000 1000 0010 1110 1010 0101 1001 1000 1110 1110 0111


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