Convert the Number 20.654 343 to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number. Detailed Explanations

Number 20.654 343(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)

The first steps we'll go through to make the conversion:

Convert to binary (to base 2) the integer part of the number.

Convert to binary the fractional part of the number.


1. First, convert to binary (in base 2) the integer part: 20.
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;
  • 20 ÷ 2 = 10 + 0;
  • 10 ÷ 2 = 5 + 0;
  • 5 ÷ 2 = 2 + 1;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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.


20(10) =


1 0100(2)


3. Convert to binary (base 2) the fractional part: 0.654 343.

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) 0.654 343 × 2 = 1 + 0.308 686;
  • 2) 0.308 686 × 2 = 0 + 0.617 372;
  • 3) 0.617 372 × 2 = 1 + 0.234 744;
  • 4) 0.234 744 × 2 = 0 + 0.469 488;
  • 5) 0.469 488 × 2 = 0 + 0.938 976;
  • 6) 0.938 976 × 2 = 1 + 0.877 952;
  • 7) 0.877 952 × 2 = 1 + 0.755 904;
  • 8) 0.755 904 × 2 = 1 + 0.511 808;
  • 9) 0.511 808 × 2 = 1 + 0.023 616;
  • 10) 0.023 616 × 2 = 0 + 0.047 232;
  • 11) 0.047 232 × 2 = 0 + 0.094 464;
  • 12) 0.094 464 × 2 = 0 + 0.188 928;
  • 13) 0.188 928 × 2 = 0 + 0.377 856;
  • 14) 0.377 856 × 2 = 0 + 0.755 712;
  • 15) 0.755 712 × 2 = 1 + 0.511 424;
  • 16) 0.511 424 × 2 = 1 + 0.022 848;
  • 17) 0.022 848 × 2 = 0 + 0.045 696;
  • 18) 0.045 696 × 2 = 0 + 0.091 392;
  • 19) 0.091 392 × 2 = 0 + 0.182 784;
  • 20) 0.182 784 × 2 = 0 + 0.365 568;
  • 21) 0.365 568 × 2 = 0 + 0.731 136;
  • 22) 0.731 136 × 2 = 1 + 0.462 272;
  • 23) 0.462 272 × 2 = 0 + 0.924 544;
  • 24) 0.924 544 × 2 = 1 + 0.849 088;
  • 25) 0.849 088 × 2 = 1 + 0.698 176;
  • 26) 0.698 176 × 2 = 1 + 0.396 352;
  • 27) 0.396 352 × 2 = 0 + 0.792 704;
  • 28) 0.792 704 × 2 = 1 + 0.585 408;
  • 29) 0.585 408 × 2 = 1 + 0.170 816;
  • 30) 0.170 816 × 2 = 0 + 0.341 632;
  • 31) 0.341 632 × 2 = 0 + 0.683 264;
  • 32) 0.683 264 × 2 = 1 + 0.366 528;
  • 33) 0.366 528 × 2 = 0 + 0.733 056;
  • 34) 0.733 056 × 2 = 1 + 0.466 112;
  • 35) 0.466 112 × 2 = 0 + 0.932 224;
  • 36) 0.932 224 × 2 = 1 + 0.864 448;
  • 37) 0.864 448 × 2 = 1 + 0.728 896;
  • 38) 0.728 896 × 2 = 1 + 0.457 792;
  • 39) 0.457 792 × 2 = 0 + 0.915 584;
  • 40) 0.915 584 × 2 = 1 + 0.831 168;
  • 41) 0.831 168 × 2 = 1 + 0.662 336;
  • 42) 0.662 336 × 2 = 1 + 0.324 672;
  • 43) 0.324 672 × 2 = 0 + 0.649 344;
  • 44) 0.649 344 × 2 = 1 + 0.298 688;
  • 45) 0.298 688 × 2 = 0 + 0.597 376;
  • 46) 0.597 376 × 2 = 1 + 0.194 752;
  • 47) 0.194 752 × 2 = 0 + 0.389 504;
  • 48) 0.389 504 × 2 = 0 + 0.779 008;
  • 49) 0.779 008 × 2 = 1 + 0.558 016;
  • 50) 0.558 016 × 2 = 1 + 0.116 032;
  • 51) 0.116 032 × 2 = 0 + 0.232 064;
  • 52) 0.232 064 × 2 = 0 + 0.464 128;
  • 53) 0.464 128 × 2 = 0 + 0.928 256;

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:


0.654 343(10) =


0.1010 0111 1000 0011 0000 0101 1101 1001 0101 1101 1101 0100 1100 0(2)


5. Positive number before normalization:

20.654 343(10) =


1 0100.1010 0111 1000 0011 0000 0101 1101 1001 0101 1101 1101 0100 1100 0(2)


The last steps we'll go through to make the conversion:

Normalize the binary representation of the number.

Adjust the exponent.

Convert the adjusted exponent from the decimal (base 10) to 8 bit binary.

Normalize the mantissa.


6. 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:


20.654 343(10) =


1 0100.1010 0111 1000 0011 0000 0101 1101 1001 0101 1101 1101 0100 1100 0(2) =


1 0100.1010 0111 1000 0011 0000 0101 1101 1001 0101 1101 1101 0100 1100 0(2) × 20 =


1.0100 1010 0111 1000 0011 0000 0101 1101 1001 0101 1101 1101 0100 1100 0(2) × 24


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): 4


Mantissa (not normalized):
1.0100 1010 0111 1000 0011 0000 0101 1101 1001 0101 1101 1101 0100 1100 0


8. 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)


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;
  • 1 027 ÷ 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;

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) =


1027(10) =


100 0000 0011(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, 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. 0100 1010 0111 1000 0011 0000 0101 1101 1001 0101 1101 1101 0100 1 1000 =


0100 1010 0111 1000 0011 0000 0101 1101 1001 0101 1101 1101 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) =
100 0000 0011


Mantissa (52 bits) =
0100 1010 0111 1000 0011 0000 0101 1101 1001 0101 1101 1101 0100


The base ten decimal number 20.654 343 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 100 0000 0011 - 0100 1010 0111 1000 0011 0000 0101 1101 1001 0101 1101 1101 0100

(64 bits IEEE 754)

Number 20.654 342 converted from decimal system (base 10) to 64 bit double precision IEEE 754 binary floating point representation = ?

Number 20.654 344 converted from decimal system (base 10) to 64 bit double precision IEEE 754 binary floating point representation = ?

Convert to 64 bit double precision IEEE 754 binary floating point representation standard

A number in 64 bit double precision IEEE 754 binary floating point standard representation requires three building elements: sign (it takes 1 bit and it's either 0 for positive or 1 for negative numbers), exponent (11 bits), mantissa (52 bits)

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Follow the steps below to convert a base 10 decimal number to 64 bit double precision IEEE 754 binary floating point:

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Available Base Conversions Between Decimal and Binary Systems

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1. Integer -> Binary

2. Decimal -> Binary

3. Binary -> Integer

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