Convert the Number -27.621 to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard, From a Base 10 Decimal System Number. Detailed Explanations

Number -27.621(10) converted and written in 32 bit single precision IEEE 754 binary floating point representation (1 bit for sign, 8 bits for exponent, 23 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. Start with the positive version of the number:

|-27.621| = 27.621

2. First, convert to binary (in base 2) the integer part: 27.
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;
  • 27 ÷ 2 = 13 + 1;
  • 13 ÷ 2 = 6 + 1;
  • 6 ÷ 2 = 3 + 0;
  • 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.


27(10) =


1 1011(2)


4. Convert to binary (base 2) the fractional part: 0.621.

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) 0.621 × 2 = 1 + 0.242;
  • 2) 0.242 × 2 = 0 + 0.484;
  • 3) 0.484 × 2 = 0 + 0.968;
  • 4) 0.968 × 2 = 1 + 0.936;
  • 5) 0.936 × 2 = 1 + 0.872;
  • 6) 0.872 × 2 = 1 + 0.744;
  • 7) 0.744 × 2 = 1 + 0.488;
  • 8) 0.488 × 2 = 0 + 0.976;
  • 9) 0.976 × 2 = 1 + 0.952;
  • 10) 0.952 × 2 = 1 + 0.904;
  • 11) 0.904 × 2 = 1 + 0.808;
  • 12) 0.808 × 2 = 1 + 0.616;
  • 13) 0.616 × 2 = 1 + 0.232;
  • 14) 0.232 × 2 = 0 + 0.464;
  • 15) 0.464 × 2 = 0 + 0.928;
  • 16) 0.928 × 2 = 1 + 0.856;
  • 17) 0.856 × 2 = 1 + 0.712;
  • 18) 0.712 × 2 = 1 + 0.424;
  • 19) 0.424 × 2 = 0 + 0.848;
  • 20) 0.848 × 2 = 1 + 0.696;
  • 21) 0.696 × 2 = 1 + 0.392;
  • 22) 0.392 × 2 = 0 + 0.784;
  • 23) 0.784 × 2 = 1 + 0.568;
  • 24) 0.568 × 2 = 1 + 0.136;

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:


0.621(10) =


0.1001 1110 1111 1001 1101 1011(2)


6. Positive number before normalization:

27.621(10) =


1 1011.1001 1110 1111 1001 1101 1011(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.


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:


27.621(10) =


1 1011.1001 1110 1111 1001 1101 1011(2) =


1 1011.1001 1110 1111 1001 1101 1011(2) × 20 =


1.1011 1001 1110 1111 1001 1101 1011(2) × 24


8. Up to this moment, there are the following elements that would feed into the 32 bit single precision IEEE 754 binary floating point representation:

Sign 1 (a negative number)


Exponent (unadjusted): 4


Mantissa (not normalized):
1.1011 1001 1110 1111 1001 1101 1011


9. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(8-1) - 1 =


4 + 2(8-1) - 1 =


(4 + 127)(10) =


131(10)


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

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 131 ÷ 2 = 65 + 1;
  • 65 ÷ 2 = 32 + 1;
  • 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) =


131(10) =


1000 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 23 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. 101 1100 1111 0111 1100 1110 1 1011 =


101 1100 1111 0111 1100 1110


13. The three elements that make up the number's 32 bit single precision IEEE 754 binary floating point representation:

Sign (1 bit) =
1 (a negative number)


Exponent (8 bits) =
1000 0011


Mantissa (23 bits) =
101 1100 1111 0111 1100 1110


The base ten decimal number -27.621 converted and written in 32 bit single precision IEEE 754 binary floating point representation:
1 - 1000 0011 - 101 1100 1111 0111 1100 1110

(32 bits IEEE 754)

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Example: convert the negative number -25.347 from decimal system (base ten) to 32 bit single precision IEEE 754 binary floating point:

Available Base Conversions Between Decimal and Binary Systems

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