-7.769 489 691 003 28 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -7.769 489 691 003 28(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
-7.769 489 691 003 28(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:

|-7.769 489 691 003 28| = 7.769 489 691 003 28


2. First, convert to binary (in base 2) the integer part: 7.
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;
  • 7 ÷ 2 = 3 + 1;
  • 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.

7(10) =


111(2)


4. Convert to binary (base 2) the fractional part: 0.769 489 691 003 28.

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) 0.769 489 691 003 28 × 2 = 1 + 0.538 979 382 006 56;
  • 2) 0.538 979 382 006 56 × 2 = 1 + 0.077 958 764 013 12;
  • 3) 0.077 958 764 013 12 × 2 = 0 + 0.155 917 528 026 24;
  • 4) 0.155 917 528 026 24 × 2 = 0 + 0.311 835 056 052 48;
  • 5) 0.311 835 056 052 48 × 2 = 0 + 0.623 670 112 104 96;
  • 6) 0.623 670 112 104 96 × 2 = 1 + 0.247 340 224 209 92;
  • 7) 0.247 340 224 209 92 × 2 = 0 + 0.494 680 448 419 84;
  • 8) 0.494 680 448 419 84 × 2 = 0 + 0.989 360 896 839 68;
  • 9) 0.989 360 896 839 68 × 2 = 1 + 0.978 721 793 679 36;
  • 10) 0.978 721 793 679 36 × 2 = 1 + 0.957 443 587 358 72;
  • 11) 0.957 443 587 358 72 × 2 = 1 + 0.914 887 174 717 44;
  • 12) 0.914 887 174 717 44 × 2 = 1 + 0.829 774 349 434 88;
  • 13) 0.829 774 349 434 88 × 2 = 1 + 0.659 548 698 869 76;
  • 14) 0.659 548 698 869 76 × 2 = 1 + 0.319 097 397 739 52;
  • 15) 0.319 097 397 739 52 × 2 = 0 + 0.638 194 795 479 04;
  • 16) 0.638 194 795 479 04 × 2 = 1 + 0.276 389 590 958 08;
  • 17) 0.276 389 590 958 08 × 2 = 0 + 0.552 779 181 916 16;
  • 18) 0.552 779 181 916 16 × 2 = 1 + 0.105 558 363 832 32;
  • 19) 0.105 558 363 832 32 × 2 = 0 + 0.211 116 727 664 64;
  • 20) 0.211 116 727 664 64 × 2 = 0 + 0.422 233 455 329 28;
  • 21) 0.422 233 455 329 28 × 2 = 0 + 0.844 466 910 658 56;
  • 22) 0.844 466 910 658 56 × 2 = 1 + 0.688 933 821 317 12;
  • 23) 0.688 933 821 317 12 × 2 = 1 + 0.377 867 642 634 24;
  • 24) 0.377 867 642 634 24 × 2 = 0 + 0.755 735 285 268 48;
  • 25) 0.755 735 285 268 48 × 2 = 1 + 0.511 470 570 536 96;
  • 26) 0.511 470 570 536 96 × 2 = 1 + 0.022 941 141 073 92;
  • 27) 0.022 941 141 073 92 × 2 = 0 + 0.045 882 282 147 84;
  • 28) 0.045 882 282 147 84 × 2 = 0 + 0.091 764 564 295 68;
  • 29) 0.091 764 564 295 68 × 2 = 0 + 0.183 529 128 591 36;
  • 30) 0.183 529 128 591 36 × 2 = 0 + 0.367 058 257 182 72;
  • 31) 0.367 058 257 182 72 × 2 = 0 + 0.734 116 514 365 44;
  • 32) 0.734 116 514 365 44 × 2 = 1 + 0.468 233 028 730 88;
  • 33) 0.468 233 028 730 88 × 2 = 0 + 0.936 466 057 461 76;
  • 34) 0.936 466 057 461 76 × 2 = 1 + 0.872 932 114 923 52;
  • 35) 0.872 932 114 923 52 × 2 = 1 + 0.745 864 229 847 04;
  • 36) 0.745 864 229 847 04 × 2 = 1 + 0.491 728 459 694 08;
  • 37) 0.491 728 459 694 08 × 2 = 0 + 0.983 456 919 388 16;
  • 38) 0.983 456 919 388 16 × 2 = 1 + 0.966 913 838 776 32;
  • 39) 0.966 913 838 776 32 × 2 = 1 + 0.933 827 677 552 64;
  • 40) 0.933 827 677 552 64 × 2 = 1 + 0.867 655 355 105 28;
  • 41) 0.867 655 355 105 28 × 2 = 1 + 0.735 310 710 210 56;
  • 42) 0.735 310 710 210 56 × 2 = 1 + 0.470 621 420 421 12;
  • 43) 0.470 621 420 421 12 × 2 = 0 + 0.941 242 840 842 24;
  • 44) 0.941 242 840 842 24 × 2 = 1 + 0.882 485 681 684 48;
  • 45) 0.882 485 681 684 48 × 2 = 1 + 0.764 971 363 368 96;
  • 46) 0.764 971 363 368 96 × 2 = 1 + 0.529 942 726 737 92;
  • 47) 0.529 942 726 737 92 × 2 = 1 + 0.059 885 453 475 84;
  • 48) 0.059 885 453 475 84 × 2 = 0 + 0.119 770 906 951 68;
  • 49) 0.119 770 906 951 68 × 2 = 0 + 0.239 541 813 903 36;
  • 50) 0.239 541 813 903 36 × 2 = 0 + 0.479 083 627 806 72;
  • 51) 0.479 083 627 806 72 × 2 = 0 + 0.958 167 255 613 44;
  • 52) 0.958 167 255 613 44 × 2 = 1 + 0.916 334 511 226 88;
  • 53) 0.916 334 511 226 88 × 2 = 1 + 0.832 669 022 453 76;

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:


0.769 489 691 003 28(10) =


0.1100 0100 1111 1101 0100 0110 1100 0001 0111 0111 1101 1110 0001 1(2)

6. Positive number before normalization:

7.769 489 691 003 28(10) =


111.1100 0100 1111 1101 0100 0110 1100 0001 0111 0111 1101 1110 0001 1(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 2 positions to the left, so that only one non zero digit remains to the left of it:


7.769 489 691 003 28(10) =


111.1100 0100 1111 1101 0100 0110 1100 0001 0111 0111 1101 1110 0001 1(2) =


111.1100 0100 1111 1101 0100 0110 1100 0001 0111 0111 1101 1110 0001 1(2) × 20 =


1.1111 0001 0011 1111 0101 0001 1011 0000 0101 1101 1111 0111 1000 011(2) × 22


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): 2


Mantissa (not normalized):
1.1111 0001 0011 1111 0101 0001 1011 0000 0101 1101 1111 0111 1000 011


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


2 + 2(11-1) - 1 =


(2 + 1 023)(10) =


1 025(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;
  • 1 025 ÷ 2 = 512 + 1;
  • 512 ÷ 2 = 256 + 0;
  • 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) =


1025(10) =


100 0000 0001(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. 1111 0001 0011 1111 0101 0001 1011 0000 0101 1101 1111 0111 1000 011 =


1111 0001 0011 1111 0101 0001 1011 0000 0101 1101 1111 0111 1000


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 0001


Mantissa (52 bits) =
1111 0001 0011 1111 0101 0001 1011 0000 0101 1101 1111 0111 1000


Decimal number -7.769 489 691 003 28 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 0001 - 1111 0001 0011 1111 0101 0001 1011 0000 0101 1101 1111 0111 1000

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