-17.783 247 610 924 7 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -17.783 247 610 924 7(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
-17.783 247 610 924 7(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:

|-17.783 247 610 924 7| = 17.783 247 610 924 7


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: 0.783 247 610 924 7.

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) 0.783 247 610 924 7 × 2 = 1 + 0.566 495 221 849 4;
  • 2) 0.566 495 221 849 4 × 2 = 1 + 0.132 990 443 698 8;
  • 3) 0.132 990 443 698 8 × 2 = 0 + 0.265 980 887 397 6;
  • 4) 0.265 980 887 397 6 × 2 = 0 + 0.531 961 774 795 2;
  • 5) 0.531 961 774 795 2 × 2 = 1 + 0.063 923 549 590 4;
  • 6) 0.063 923 549 590 4 × 2 = 0 + 0.127 847 099 180 8;
  • 7) 0.127 847 099 180 8 × 2 = 0 + 0.255 694 198 361 6;
  • 8) 0.255 694 198 361 6 × 2 = 0 + 0.511 388 396 723 2;
  • 9) 0.511 388 396 723 2 × 2 = 1 + 0.022 776 793 446 4;
  • 10) 0.022 776 793 446 4 × 2 = 0 + 0.045 553 586 892 8;
  • 11) 0.045 553 586 892 8 × 2 = 0 + 0.091 107 173 785 6;
  • 12) 0.091 107 173 785 6 × 2 = 0 + 0.182 214 347 571 2;
  • 13) 0.182 214 347 571 2 × 2 = 0 + 0.364 428 695 142 4;
  • 14) 0.364 428 695 142 4 × 2 = 0 + 0.728 857 390 284 8;
  • 15) 0.728 857 390 284 8 × 2 = 1 + 0.457 714 780 569 6;
  • 16) 0.457 714 780 569 6 × 2 = 0 + 0.915 429 561 139 2;
  • 17) 0.915 429 561 139 2 × 2 = 1 + 0.830 859 122 278 4;
  • 18) 0.830 859 122 278 4 × 2 = 1 + 0.661 718 244 556 8;
  • 19) 0.661 718 244 556 8 × 2 = 1 + 0.323 436 489 113 6;
  • 20) 0.323 436 489 113 6 × 2 = 0 + 0.646 872 978 227 2;
  • 21) 0.646 872 978 227 2 × 2 = 1 + 0.293 745 956 454 4;
  • 22) 0.293 745 956 454 4 × 2 = 0 + 0.587 491 912 908 8;
  • 23) 0.587 491 912 908 8 × 2 = 1 + 0.174 983 825 817 6;
  • 24) 0.174 983 825 817 6 × 2 = 0 + 0.349 967 651 635 2;
  • 25) 0.349 967 651 635 2 × 2 = 0 + 0.699 935 303 270 4;
  • 26) 0.699 935 303 270 4 × 2 = 1 + 0.399 870 606 540 8;
  • 27) 0.399 870 606 540 8 × 2 = 0 + 0.799 741 213 081 6;
  • 28) 0.799 741 213 081 6 × 2 = 1 + 0.599 482 426 163 2;
  • 29) 0.599 482 426 163 2 × 2 = 1 + 0.198 964 852 326 4;
  • 30) 0.198 964 852 326 4 × 2 = 0 + 0.397 929 704 652 8;
  • 31) 0.397 929 704 652 8 × 2 = 0 + 0.795 859 409 305 6;
  • 32) 0.795 859 409 305 6 × 2 = 1 + 0.591 718 818 611 2;
  • 33) 0.591 718 818 611 2 × 2 = 1 + 0.183 437 637 222 4;
  • 34) 0.183 437 637 222 4 × 2 = 0 + 0.366 875 274 444 8;
  • 35) 0.366 875 274 444 8 × 2 = 0 + 0.733 750 548 889 6;
  • 36) 0.733 750 548 889 6 × 2 = 1 + 0.467 501 097 779 2;
  • 37) 0.467 501 097 779 2 × 2 = 0 + 0.935 002 195 558 4;
  • 38) 0.935 002 195 558 4 × 2 = 1 + 0.870 004 391 116 8;
  • 39) 0.870 004 391 116 8 × 2 = 1 + 0.740 008 782 233 6;
  • 40) 0.740 008 782 233 6 × 2 = 1 + 0.480 017 564 467 2;
  • 41) 0.480 017 564 467 2 × 2 = 0 + 0.960 035 128 934 4;
  • 42) 0.960 035 128 934 4 × 2 = 1 + 0.920 070 257 868 8;
  • 43) 0.920 070 257 868 8 × 2 = 1 + 0.840 140 515 737 6;
  • 44) 0.840 140 515 737 6 × 2 = 1 + 0.680 281 031 475 2;
  • 45) 0.680 281 031 475 2 × 2 = 1 + 0.360 562 062 950 4;
  • 46) 0.360 562 062 950 4 × 2 = 0 + 0.721 124 125 900 8;
  • 47) 0.721 124 125 900 8 × 2 = 1 + 0.442 248 251 801 6;
  • 48) 0.442 248 251 801 6 × 2 = 0 + 0.884 496 503 603 2;
  • 49) 0.884 496 503 603 2 × 2 = 1 + 0.768 993 007 206 4;
  • 50) 0.768 993 007 206 4 × 2 = 1 + 0.537 986 014 412 8;
  • 51) 0.537 986 014 412 8 × 2 = 1 + 0.075 972 028 825 6;
  • 52) 0.075 972 028 825 6 × 2 = 0 + 0.151 944 057 651 2;
  • 53) 0.151 944 057 651 2 × 2 = 0 + 0.303 888 115 302 4;

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:


0.783 247 610 924 7(10) =


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

6. Positive number before normalization:

17.783 247 610 924 7(10) =


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


17.783 247 610 924 7(10) =


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


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


1.0001 1100 1000 1000 0010 1110 1010 0101 1001 1001 0111 0111 1010 1110 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 1001 0111 0111 1010 1110 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 1001 0111 0111 1010 1 1100 =


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


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 0111 1010


Decimal number -17.783 247 610 924 7 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 0111 1010


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