64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: -34.932 999 14 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number -34.932 999 14(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. Start with the positive version of the number:

|-34.932 999 14| = 34.932 999 14

2. First, convert to binary (in base 2) the integer part: 34.
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;
  • 34 ÷ 2 = 17 + 0;
  • 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.


34(10) =


10 0010(2)


4. Convert to binary (base 2) the fractional part: 0.932 999 14.

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) 0.932 999 14 × 2 = 1 + 0.865 998 28;
  • 2) 0.865 998 28 × 2 = 1 + 0.731 996 56;
  • 3) 0.731 996 56 × 2 = 1 + 0.463 993 12;
  • 4) 0.463 993 12 × 2 = 0 + 0.927 986 24;
  • 5) 0.927 986 24 × 2 = 1 + 0.855 972 48;
  • 6) 0.855 972 48 × 2 = 1 + 0.711 944 96;
  • 7) 0.711 944 96 × 2 = 1 + 0.423 889 92;
  • 8) 0.423 889 92 × 2 = 0 + 0.847 779 84;
  • 9) 0.847 779 84 × 2 = 1 + 0.695 559 68;
  • 10) 0.695 559 68 × 2 = 1 + 0.391 119 36;
  • 11) 0.391 119 36 × 2 = 0 + 0.782 238 72;
  • 12) 0.782 238 72 × 2 = 1 + 0.564 477 44;
  • 13) 0.564 477 44 × 2 = 1 + 0.128 954 88;
  • 14) 0.128 954 88 × 2 = 0 + 0.257 909 76;
  • 15) 0.257 909 76 × 2 = 0 + 0.515 819 52;
  • 16) 0.515 819 52 × 2 = 1 + 0.031 639 04;
  • 17) 0.031 639 04 × 2 = 0 + 0.063 278 08;
  • 18) 0.063 278 08 × 2 = 0 + 0.126 556 16;
  • 19) 0.126 556 16 × 2 = 0 + 0.253 112 32;
  • 20) 0.253 112 32 × 2 = 0 + 0.506 224 64;
  • 21) 0.506 224 64 × 2 = 1 + 0.012 449 28;
  • 22) 0.012 449 28 × 2 = 0 + 0.024 898 56;
  • 23) 0.024 898 56 × 2 = 0 + 0.049 797 12;
  • 24) 0.049 797 12 × 2 = 0 + 0.099 594 24;
  • 25) 0.099 594 24 × 2 = 0 + 0.199 188 48;
  • 26) 0.199 188 48 × 2 = 0 + 0.398 376 96;
  • 27) 0.398 376 96 × 2 = 0 + 0.796 753 92;
  • 28) 0.796 753 92 × 2 = 1 + 0.593 507 84;
  • 29) 0.593 507 84 × 2 = 1 + 0.187 015 68;
  • 30) 0.187 015 68 × 2 = 0 + 0.374 031 36;
  • 31) 0.374 031 36 × 2 = 0 + 0.748 062 72;
  • 32) 0.748 062 72 × 2 = 1 + 0.496 125 44;
  • 33) 0.496 125 44 × 2 = 0 + 0.992 250 88;
  • 34) 0.992 250 88 × 2 = 1 + 0.984 501 76;
  • 35) 0.984 501 76 × 2 = 1 + 0.969 003 52;
  • 36) 0.969 003 52 × 2 = 1 + 0.938 007 04;
  • 37) 0.938 007 04 × 2 = 1 + 0.876 014 08;
  • 38) 0.876 014 08 × 2 = 1 + 0.752 028 16;
  • 39) 0.752 028 16 × 2 = 1 + 0.504 056 32;
  • 40) 0.504 056 32 × 2 = 1 + 0.008 112 64;
  • 41) 0.008 112 64 × 2 = 0 + 0.016 225 28;
  • 42) 0.016 225 28 × 2 = 0 + 0.032 450 56;
  • 43) 0.032 450 56 × 2 = 0 + 0.064 901 12;
  • 44) 0.064 901 12 × 2 = 0 + 0.129 802 24;
  • 45) 0.129 802 24 × 2 = 0 + 0.259 604 48;
  • 46) 0.259 604 48 × 2 = 0 + 0.519 208 96;
  • 47) 0.519 208 96 × 2 = 1 + 0.038 417 92;
  • 48) 0.038 417 92 × 2 = 0 + 0.076 835 84;
  • 49) 0.076 835 84 × 2 = 0 + 0.153 671 68;
  • 50) 0.153 671 68 × 2 = 0 + 0.307 343 36;
  • 51) 0.307 343 36 × 2 = 0 + 0.614 686 72;
  • 52) 0.614 686 72 × 2 = 1 + 0.229 373 44;
  • 53) 0.229 373 44 × 2 = 0 + 0.458 746 88;

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...)


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:


0.932 999 14(10) =


0.1110 1110 1101 1001 0000 1000 0001 1001 0111 1111 0000 0010 0001 0(2)


6. Positive number before normalization:

34.932 999 14(10) =


10 0010.1110 1110 1101 1001 0000 1000 0001 1001 0111 1111 0000 0010 0001 0(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 5 positions to the left, so that only one non zero digit remains to the left of it:


34.932 999 14(10) =


10 0010.1110 1110 1101 1001 0000 1000 0001 1001 0111 1111 0000 0010 0001 0(2) =


10 0010.1110 1110 1101 1001 0000 1000 0001 1001 0111 1111 0000 0010 0001 0(2) × 20 =


1.0001 0111 0111 0110 1100 1000 0100 0000 1100 1011 1111 1000 0001 0000 10(2) × 25


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): 5


Mantissa (not normalized):
1.0001 0111 0111 0110 1100 1000 0100 0000 1100 1011 1111 1000 0001 0000 10


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


5 + 2(11-1) - 1 =


(5 + 1 023)(10) =


1 028(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;
  • 1 028 ÷ 2 = 514 + 0;
  • 514 ÷ 2 = 257 + 0;
  • 257 ÷ 2 = 128 + 1;
  • 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) =


1028(10) =


100 0000 0100(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 0111 0111 0110 1100 1000 0100 0000 1100 1011 1111 1000 0001 00 0010 =


0001 0111 0111 0110 1100 1000 0100 0000 1100 1011 1111 1000 0001


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 0100


Mantissa (52 bits) =
0001 0111 0111 0110 1100 1000 0100 0000 1100 1011 1111 1000 0001


The base ten decimal number -34.932 999 14 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
1 - 100 0000 0100 - 0001 0111 0111 0110 1100 1000 0100 0000 1100 1011 1111 1000 0001

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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