-17.783 247 610 925 1 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -17.783 247 610 925 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
-17.783 247 610 925 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:

|-17.783 247 610 925 1| = 17.783 247 610 925 1


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: 0.783 247 610 925 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) 0.783 247 610 925 1 × 2 = 1 + 0.566 495 221 850 2;
  • 2) 0.566 495 221 850 2 × 2 = 1 + 0.132 990 443 700 4;
  • 3) 0.132 990 443 700 4 × 2 = 0 + 0.265 980 887 400 8;
  • 4) 0.265 980 887 400 8 × 2 = 0 + 0.531 961 774 801 6;
  • 5) 0.531 961 774 801 6 × 2 = 1 + 0.063 923 549 603 2;
  • 6) 0.063 923 549 603 2 × 2 = 0 + 0.127 847 099 206 4;
  • 7) 0.127 847 099 206 4 × 2 = 0 + 0.255 694 198 412 8;
  • 8) 0.255 694 198 412 8 × 2 = 0 + 0.511 388 396 825 6;
  • 9) 0.511 388 396 825 6 × 2 = 1 + 0.022 776 793 651 2;
  • 10) 0.022 776 793 651 2 × 2 = 0 + 0.045 553 587 302 4;
  • 11) 0.045 553 587 302 4 × 2 = 0 + 0.091 107 174 604 8;
  • 12) 0.091 107 174 604 8 × 2 = 0 + 0.182 214 349 209 6;
  • 13) 0.182 214 349 209 6 × 2 = 0 + 0.364 428 698 419 2;
  • 14) 0.364 428 698 419 2 × 2 = 0 + 0.728 857 396 838 4;
  • 15) 0.728 857 396 838 4 × 2 = 1 + 0.457 714 793 676 8;
  • 16) 0.457 714 793 676 8 × 2 = 0 + 0.915 429 587 353 6;
  • 17) 0.915 429 587 353 6 × 2 = 1 + 0.830 859 174 707 2;
  • 18) 0.830 859 174 707 2 × 2 = 1 + 0.661 718 349 414 4;
  • 19) 0.661 718 349 414 4 × 2 = 1 + 0.323 436 698 828 8;
  • 20) 0.323 436 698 828 8 × 2 = 0 + 0.646 873 397 657 6;
  • 21) 0.646 873 397 657 6 × 2 = 1 + 0.293 746 795 315 2;
  • 22) 0.293 746 795 315 2 × 2 = 0 + 0.587 493 590 630 4;
  • 23) 0.587 493 590 630 4 × 2 = 1 + 0.174 987 181 260 8;
  • 24) 0.174 987 181 260 8 × 2 = 0 + 0.349 974 362 521 6;
  • 25) 0.349 974 362 521 6 × 2 = 0 + 0.699 948 725 043 2;
  • 26) 0.699 948 725 043 2 × 2 = 1 + 0.399 897 450 086 4;
  • 27) 0.399 897 450 086 4 × 2 = 0 + 0.799 794 900 172 8;
  • 28) 0.799 794 900 172 8 × 2 = 1 + 0.599 589 800 345 6;
  • 29) 0.599 589 800 345 6 × 2 = 1 + 0.199 179 600 691 2;
  • 30) 0.199 179 600 691 2 × 2 = 0 + 0.398 359 201 382 4;
  • 31) 0.398 359 201 382 4 × 2 = 0 + 0.796 718 402 764 8;
  • 32) 0.796 718 402 764 8 × 2 = 1 + 0.593 436 805 529 6;
  • 33) 0.593 436 805 529 6 × 2 = 1 + 0.186 873 611 059 2;
  • 34) 0.186 873 611 059 2 × 2 = 0 + 0.373 747 222 118 4;
  • 35) 0.373 747 222 118 4 × 2 = 0 + 0.747 494 444 236 8;
  • 36) 0.747 494 444 236 8 × 2 = 1 + 0.494 988 888 473 6;
  • 37) 0.494 988 888 473 6 × 2 = 0 + 0.989 977 776 947 2;
  • 38) 0.989 977 776 947 2 × 2 = 1 + 0.979 955 553 894 4;
  • 39) 0.979 955 553 894 4 × 2 = 1 + 0.959 911 107 788 8;
  • 40) 0.959 911 107 788 8 × 2 = 1 + 0.919 822 215 577 6;
  • 41) 0.919 822 215 577 6 × 2 = 1 + 0.839 644 431 155 2;
  • 42) 0.839 644 431 155 2 × 2 = 1 + 0.679 288 862 310 4;
  • 43) 0.679 288 862 310 4 × 2 = 1 + 0.358 577 724 620 8;
  • 44) 0.358 577 724 620 8 × 2 = 0 + 0.717 155 449 241 6;
  • 45) 0.717 155 449 241 6 × 2 = 1 + 0.434 310 898 483 2;
  • 46) 0.434 310 898 483 2 × 2 = 0 + 0.868 621 796 966 4;
  • 47) 0.868 621 796 966 4 × 2 = 1 + 0.737 243 593 932 8;
  • 48) 0.737 243 593 932 8 × 2 = 1 + 0.474 487 187 865 6;
  • 49) 0.474 487 187 865 6 × 2 = 0 + 0.948 974 375 731 2;
  • 50) 0.948 974 375 731 2 × 2 = 1 + 0.897 948 751 462 4;
  • 51) 0.897 948 751 462 4 × 2 = 1 + 0.795 897 502 924 8;
  • 52) 0.795 897 502 924 8 × 2 = 1 + 0.591 795 005 849 6;
  • 53) 0.591 795 005 849 6 × 2 = 1 + 0.183 590 011 699 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:


0.783 247 610 925 1(10) =


0.1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1110 1011 0111 1(2)

6. Positive number before normalization:

17.783 247 610 925 1(10) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1110 1011 0111 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:


17.783 247 610 925 1(10) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1110 1011 0111 1(2) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1110 1011 0111 1(2) × 20 =


1.0001 1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1110 1011 0111 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):
1.0001 1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1110 1011 0111 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. 0001 1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1110 1011 0 1111 =


0001 1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1110 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 0011


Mantissa (52 bits) =
0001 1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 1110 1011


Decimal number -17.783 247 610 925 1 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 1001 0111 1110 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