64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 0.965 925 826 26 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 0.965 925 826 26(10) converted and written in 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. First, convert to binary (in base 2) the integer part: 0.
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;
  • 0 ÷ 2 = 0 + 0;

2. 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.


0(10) =


0(2)


3. Convert to binary (base 2) the fractional part: 0.965 925 826 26.

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) 0.965 925 826 26 × 2 = 1 + 0.931 851 652 52;
  • 2) 0.931 851 652 52 × 2 = 1 + 0.863 703 305 04;
  • 3) 0.863 703 305 04 × 2 = 1 + 0.727 406 610 08;
  • 4) 0.727 406 610 08 × 2 = 1 + 0.454 813 220 16;
  • 5) 0.454 813 220 16 × 2 = 0 + 0.909 626 440 32;
  • 6) 0.909 626 440 32 × 2 = 1 + 0.819 252 880 64;
  • 7) 0.819 252 880 64 × 2 = 1 + 0.638 505 761 28;
  • 8) 0.638 505 761 28 × 2 = 1 + 0.277 011 522 56;
  • 9) 0.277 011 522 56 × 2 = 0 + 0.554 023 045 12;
  • 10) 0.554 023 045 12 × 2 = 1 + 0.108 046 090 24;
  • 11) 0.108 046 090 24 × 2 = 0 + 0.216 092 180 48;
  • 12) 0.216 092 180 48 × 2 = 0 + 0.432 184 360 96;
  • 13) 0.432 184 360 96 × 2 = 0 + 0.864 368 721 92;
  • 14) 0.864 368 721 92 × 2 = 1 + 0.728 737 443 84;
  • 15) 0.728 737 443 84 × 2 = 1 + 0.457 474 887 68;
  • 16) 0.457 474 887 68 × 2 = 0 + 0.914 949 775 36;
  • 17) 0.914 949 775 36 × 2 = 1 + 0.829 899 550 72;
  • 18) 0.829 899 550 72 × 2 = 1 + 0.659 799 101 44;
  • 19) 0.659 799 101 44 × 2 = 1 + 0.319 598 202 88;
  • 20) 0.319 598 202 88 × 2 = 0 + 0.639 196 405 76;
  • 21) 0.639 196 405 76 × 2 = 1 + 0.278 392 811 52;
  • 22) 0.278 392 811 52 × 2 = 0 + 0.556 785 623 04;
  • 23) 0.556 785 623 04 × 2 = 1 + 0.113 571 246 08;
  • 24) 0.113 571 246 08 × 2 = 0 + 0.227 142 492 16;
  • 25) 0.227 142 492 16 × 2 = 0 + 0.454 284 984 32;
  • 26) 0.454 284 984 32 × 2 = 0 + 0.908 569 968 64;
  • 27) 0.908 569 968 64 × 2 = 1 + 0.817 139 937 28;
  • 28) 0.817 139 937 28 × 2 = 1 + 0.634 279 874 56;
  • 29) 0.634 279 874 56 × 2 = 1 + 0.268 559 749 12;
  • 30) 0.268 559 749 12 × 2 = 0 + 0.537 119 498 24;
  • 31) 0.537 119 498 24 × 2 = 1 + 0.074 238 996 48;
  • 32) 0.074 238 996 48 × 2 = 0 + 0.148 477 992 96;
  • 33) 0.148 477 992 96 × 2 = 0 + 0.296 955 985 92;
  • 34) 0.296 955 985 92 × 2 = 0 + 0.593 911 971 84;
  • 35) 0.593 911 971 84 × 2 = 1 + 0.187 823 943 68;
  • 36) 0.187 823 943 68 × 2 = 0 + 0.375 647 887 36;
  • 37) 0.375 647 887 36 × 2 = 0 + 0.751 295 774 72;
  • 38) 0.751 295 774 72 × 2 = 1 + 0.502 591 549 44;
  • 39) 0.502 591 549 44 × 2 = 1 + 0.005 183 098 88;
  • 40) 0.005 183 098 88 × 2 = 0 + 0.010 366 197 76;
  • 41) 0.010 366 197 76 × 2 = 0 + 0.020 732 395 52;
  • 42) 0.020 732 395 52 × 2 = 0 + 0.041 464 791 04;
  • 43) 0.041 464 791 04 × 2 = 0 + 0.082 929 582 08;
  • 44) 0.082 929 582 08 × 2 = 0 + 0.165 859 164 16;
  • 45) 0.165 859 164 16 × 2 = 0 + 0.331 718 328 32;
  • 46) 0.331 718 328 32 × 2 = 0 + 0.663 436 656 64;
  • 47) 0.663 436 656 64 × 2 = 1 + 0.326 873 313 28;
  • 48) 0.326 873 313 28 × 2 = 0 + 0.653 746 626 56;
  • 49) 0.653 746 626 56 × 2 = 1 + 0.307 493 253 12;
  • 50) 0.307 493 253 12 × 2 = 0 + 0.614 986 506 24;
  • 51) 0.614 986 506 24 × 2 = 1 + 0.229 973 012 48;
  • 52) 0.229 973 012 48 × 2 = 0 + 0.459 946 024 96;
  • 53) 0.459 946 024 96 × 2 = 0 + 0.919 892 049 92;

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...)


4. 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:


0.965 925 826 26(10) =


0.1111 0111 0100 0110 1110 1010 0011 1010 0010 0110 0000 0010 1010 0(2)


5. Positive number before normalization:

0.965 925 826 26(10) =


0.1111 0111 0100 0110 1110 1010 0011 1010 0010 0110 0000 0010 1010 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 1 positions to the right, so that only one non zero digit remains to the left of it:


0.965 925 826 26(10) =


0.1111 0111 0100 0110 1110 1010 0011 1010 0010 0110 0000 0010 1010 0(2) =


0.1111 0111 0100 0110 1110 1010 0011 1010 0010 0110 0000 0010 1010 0(2) × 20 =


1.1110 1110 1000 1101 1101 0100 0111 0100 0100 1100 0000 0101 0100(2) × 2-1


7. 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 0 (a positive number)


Exponent (unadjusted): -1


Mantissa (not normalized):
1.1110 1110 1000 1101 1101 0100 0111 0100 0100 1100 0000 0101 0100


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


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


(-1 + 1 023)(10) =


1 022(10)


9. 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;
  • 1 022 ÷ 2 = 511 + 0;
  • 511 ÷ 2 = 255 + 1;
  • 255 ÷ 2 = 127 + 1;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

10. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1022(10) =


011 1111 1110(2)


11. 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, only if necessary (not the case here).


Mantissa (normalized) =


1. 1110 1110 1000 1101 1101 0100 0111 0100 0100 1100 0000 0101 0100 =


1110 1110 1000 1101 1101 0100 0111 0100 0100 1100 0000 0101 0100


12. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
0 (a positive number)


Exponent (11 bits) =
011 1111 1110


Mantissa (52 bits) =
1110 1110 1000 1101 1101 0100 0111 0100 0100 1100 0000 0101 0100


The base ten decimal number 0.965 925 826 26 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 011 1111 1110 - 1110 1110 1000 1101 1101 0100 0111 0100 0100 1100 0000 0101 0100

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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