-17.783 247 610 922 3 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -17.783 247 610 922 3(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
-17.783 247 610 922 3(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:

|-17.783 247 610 922 3| = 17.783 247 610 922 3


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: 0.783 247 610 922 3.

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) 0.783 247 610 922 3 × 2 = 1 + 0.566 495 221 844 6;
  • 2) 0.566 495 221 844 6 × 2 = 1 + 0.132 990 443 689 2;
  • 3) 0.132 990 443 689 2 × 2 = 0 + 0.265 980 887 378 4;
  • 4) 0.265 980 887 378 4 × 2 = 0 + 0.531 961 774 756 8;
  • 5) 0.531 961 774 756 8 × 2 = 1 + 0.063 923 549 513 6;
  • 6) 0.063 923 549 513 6 × 2 = 0 + 0.127 847 099 027 2;
  • 7) 0.127 847 099 027 2 × 2 = 0 + 0.255 694 198 054 4;
  • 8) 0.255 694 198 054 4 × 2 = 0 + 0.511 388 396 108 8;
  • 9) 0.511 388 396 108 8 × 2 = 1 + 0.022 776 792 217 6;
  • 10) 0.022 776 792 217 6 × 2 = 0 + 0.045 553 584 435 2;
  • 11) 0.045 553 584 435 2 × 2 = 0 + 0.091 107 168 870 4;
  • 12) 0.091 107 168 870 4 × 2 = 0 + 0.182 214 337 740 8;
  • 13) 0.182 214 337 740 8 × 2 = 0 + 0.364 428 675 481 6;
  • 14) 0.364 428 675 481 6 × 2 = 0 + 0.728 857 350 963 2;
  • 15) 0.728 857 350 963 2 × 2 = 1 + 0.457 714 701 926 4;
  • 16) 0.457 714 701 926 4 × 2 = 0 + 0.915 429 403 852 8;
  • 17) 0.915 429 403 852 8 × 2 = 1 + 0.830 858 807 705 6;
  • 18) 0.830 858 807 705 6 × 2 = 1 + 0.661 717 615 411 2;
  • 19) 0.661 717 615 411 2 × 2 = 1 + 0.323 435 230 822 4;
  • 20) 0.323 435 230 822 4 × 2 = 0 + 0.646 870 461 644 8;
  • 21) 0.646 870 461 644 8 × 2 = 1 + 0.293 740 923 289 6;
  • 22) 0.293 740 923 289 6 × 2 = 0 + 0.587 481 846 579 2;
  • 23) 0.587 481 846 579 2 × 2 = 1 + 0.174 963 693 158 4;
  • 24) 0.174 963 693 158 4 × 2 = 0 + 0.349 927 386 316 8;
  • 25) 0.349 927 386 316 8 × 2 = 0 + 0.699 854 772 633 6;
  • 26) 0.699 854 772 633 6 × 2 = 1 + 0.399 709 545 267 2;
  • 27) 0.399 709 545 267 2 × 2 = 0 + 0.799 419 090 534 4;
  • 28) 0.799 419 090 534 4 × 2 = 1 + 0.598 838 181 068 8;
  • 29) 0.598 838 181 068 8 × 2 = 1 + 0.197 676 362 137 6;
  • 30) 0.197 676 362 137 6 × 2 = 0 + 0.395 352 724 275 2;
  • 31) 0.395 352 724 275 2 × 2 = 0 + 0.790 705 448 550 4;
  • 32) 0.790 705 448 550 4 × 2 = 1 + 0.581 410 897 100 8;
  • 33) 0.581 410 897 100 8 × 2 = 1 + 0.162 821 794 201 6;
  • 34) 0.162 821 794 201 6 × 2 = 0 + 0.325 643 588 403 2;
  • 35) 0.325 643 588 403 2 × 2 = 0 + 0.651 287 176 806 4;
  • 36) 0.651 287 176 806 4 × 2 = 1 + 0.302 574 353 612 8;
  • 37) 0.302 574 353 612 8 × 2 = 0 + 0.605 148 707 225 6;
  • 38) 0.605 148 707 225 6 × 2 = 1 + 0.210 297 414 451 2;
  • 39) 0.210 297 414 451 2 × 2 = 0 + 0.420 594 828 902 4;
  • 40) 0.420 594 828 902 4 × 2 = 0 + 0.841 189 657 804 8;
  • 41) 0.841 189 657 804 8 × 2 = 1 + 0.682 379 315 609 6;
  • 42) 0.682 379 315 609 6 × 2 = 1 + 0.364 758 631 219 2;
  • 43) 0.364 758 631 219 2 × 2 = 0 + 0.729 517 262 438 4;
  • 44) 0.729 517 262 438 4 × 2 = 1 + 0.459 034 524 876 8;
  • 45) 0.459 034 524 876 8 × 2 = 0 + 0.918 069 049 753 6;
  • 46) 0.918 069 049 753 6 × 2 = 1 + 0.836 138 099 507 2;
  • 47) 0.836 138 099 507 2 × 2 = 1 + 0.672 276 199 014 4;
  • 48) 0.672 276 199 014 4 × 2 = 1 + 0.344 552 398 028 8;
  • 49) 0.344 552 398 028 8 × 2 = 0 + 0.689 104 796 057 6;
  • 50) 0.689 104 796 057 6 × 2 = 1 + 0.378 209 592 115 2;
  • 51) 0.378 209 592 115 2 × 2 = 0 + 0.756 419 184 230 4;
  • 52) 0.756 419 184 230 4 × 2 = 1 + 0.512 838 368 460 8;
  • 53) 0.512 838 368 460 8 × 2 = 1 + 0.025 676 736 921 6;

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:


0.783 247 610 922 3(10) =


0.1100 1000 1000 0010 1110 1010 0101 1001 1001 0100 1101 0111 0101 1(2)

6. Positive number before normalization:

17.783 247 610 922 3(10) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1001 0100 1101 0111 0101 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:


17.783 247 610 922 3(10) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1001 0100 1101 0111 0101 1(2) =


1 0001.1100 1000 1000 0010 1110 1010 0101 1001 1001 0100 1101 0111 0101 1(2) × 20 =


1.0001 1100 1000 1000 0010 1110 1010 0101 1001 1001 0100 1101 0111 0101 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 0100 1101 0111 0101 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 0100 1101 0111 0 1011 =


0001 1100 1000 1000 0010 1110 1010 0101 1001 1001 0100 1101 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 1001 0100 1101 0111


Decimal number -17.783 247 610 922 3 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 0100 1101 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