32bit IEEE 754: Decimal ↗ Single Precision Floating Point Binary: 1 101 010 000 109 985 Convert the Number to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard, From a Base 10 Decimal System Number

Number 1 101 010 000 109 985(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)

1. 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;
  • 1 101 010 000 109 985 ÷ 2 = 550 505 000 054 992 + 1;
  • 550 505 000 054 992 ÷ 2 = 275 252 500 027 496 + 0;
  • 275 252 500 027 496 ÷ 2 = 137 626 250 013 748 + 0;
  • 137 626 250 013 748 ÷ 2 = 68 813 125 006 874 + 0;
  • 68 813 125 006 874 ÷ 2 = 34 406 562 503 437 + 0;
  • 34 406 562 503 437 ÷ 2 = 17 203 281 251 718 + 1;
  • 17 203 281 251 718 ÷ 2 = 8 601 640 625 859 + 0;
  • 8 601 640 625 859 ÷ 2 = 4 300 820 312 929 + 1;
  • 4 300 820 312 929 ÷ 2 = 2 150 410 156 464 + 1;
  • 2 150 410 156 464 ÷ 2 = 1 075 205 078 232 + 0;
  • 1 075 205 078 232 ÷ 2 = 537 602 539 116 + 0;
  • 537 602 539 116 ÷ 2 = 268 801 269 558 + 0;
  • 268 801 269 558 ÷ 2 = 134 400 634 779 + 0;
  • 134 400 634 779 ÷ 2 = 67 200 317 389 + 1;
  • 67 200 317 389 ÷ 2 = 33 600 158 694 + 1;
  • 33 600 158 694 ÷ 2 = 16 800 079 347 + 0;
  • 16 800 079 347 ÷ 2 = 8 400 039 673 + 1;
  • 8 400 039 673 ÷ 2 = 4 200 019 836 + 1;
  • 4 200 019 836 ÷ 2 = 2 100 009 918 + 0;
  • 2 100 009 918 ÷ 2 = 1 050 004 959 + 0;
  • 1 050 004 959 ÷ 2 = 525 002 479 + 1;
  • 525 002 479 ÷ 2 = 262 501 239 + 1;
  • 262 501 239 ÷ 2 = 131 250 619 + 1;
  • 131 250 619 ÷ 2 = 65 625 309 + 1;
  • 65 625 309 ÷ 2 = 32 812 654 + 1;
  • 32 812 654 ÷ 2 = 16 406 327 + 0;
  • 16 406 327 ÷ 2 = 8 203 163 + 1;
  • 8 203 163 ÷ 2 = 4 101 581 + 1;
  • 4 101 581 ÷ 2 = 2 050 790 + 1;
  • 2 050 790 ÷ 2 = 1 025 395 + 0;
  • 1 025 395 ÷ 2 = 512 697 + 1;
  • 512 697 ÷ 2 = 256 348 + 1;
  • 256 348 ÷ 2 = 128 174 + 0;
  • 128 174 ÷ 2 = 64 087 + 0;
  • 64 087 ÷ 2 = 32 043 + 1;
  • 32 043 ÷ 2 = 16 021 + 1;
  • 16 021 ÷ 2 = 8 010 + 1;
  • 8 010 ÷ 2 = 4 005 + 0;
  • 4 005 ÷ 2 = 2 002 + 1;
  • 2 002 ÷ 2 = 1 001 + 0;
  • 1 001 ÷ 2 = 500 + 1;
  • 500 ÷ 2 = 250 + 0;
  • 250 ÷ 2 = 125 + 0;
  • 125 ÷ 2 = 62 + 1;
  • 62 ÷ 2 = 31 + 0;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

2. Construct the base 2 representation of the positive number.

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


1 101 010 000 109 985(10) =


11 1110 1001 0101 1100 1101 1101 1111 0011 0110 0001 1010 0001(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 49 positions to the left, so that only one non zero digit remains to the left of it:


1 101 010 000 109 985(10) =


11 1110 1001 0101 1100 1101 1101 1111 0011 0110 0001 1010 0001(2) =


11 1110 1001 0101 1100 1101 1101 1111 0011 0110 0001 1010 0001(2) × 20 =


1.1111 0100 1010 1110 0110 1110 1111 1001 1011 0000 1101 0000 1(2) × 249


4. 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 0 (a positive number)


Exponent (unadjusted): 49


Mantissa (not normalized):
1.1111 0100 1010 1110 0110 1110 1111 1001 1011 0000 1101 0000 1


5. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


49 + 2(8-1) - 1 =


(49 + 127)(10) =


176(10)


6. 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;
  • 176 ÷ 2 = 88 + 0;
  • 88 ÷ 2 = 44 + 0;
  • 44 ÷ 2 = 22 + 0;
  • 22 ÷ 2 = 11 + 0;
  • 11 ÷ 2 = 5 + 1;
  • 5 ÷ 2 = 2 + 1;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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

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


Exponent (adjusted) =


176(10) =


1011 0000(2)


8. 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. 111 1010 0101 0111 0011 0111 01 1111 0011 0110 0001 1010 0001 =


111 1010 0101 0111 0011 0111


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

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


Exponent (8 bits) =
1011 0000


Mantissa (23 bits) =
111 1010 0101 0111 0011 0111


The base ten decimal number 1 101 010 000 109 985 converted and written in 32 bit single precision IEEE 754 binary floating point representation:
0 - 1011 0000 - 111 1010 0101 0111 0011 0111

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How to convert decimal numbers from base ten to 32 bit single precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 32 bit single 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 base ten 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 of the previous dividing 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 previous multiplying operations, starting from the top of the constructed list 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, by shifting the decimal point (or if you prefer, the decimal mark) "n" positions either to the left or to the right, so that only one non zero digit remains to the left of the decimal point.
  • 7. Adjust the exponent in 8 bit excess/bias notation and then convert it from decimal (base 10) to 8 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(8-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign if the case) and adjust its length to 23 bits, either by removing the excess bits from the right (losing precision...) or by adding extra '0' bits 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 -25.347 from decimal system (base ten) to 32 bit single precision IEEE 754 binary floating point:

  • 1. Start with the positive version of the number:

    |-25.347| = 25.347

  • 2. First convert the integer part, 25. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 25 ÷ 2 = 12 + 1;
    • 12 ÷ 2 = 6 + 0;
    • 6 ÷ 2 = 3 + 0;
    • 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:

    25(10) = 1 1001(2)

  • 4. Then convert the fractional part, 0.347. 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) 0.347 × 2 = 0 + 0.694;
    • 2) 0.694 × 2 = 1 + 0.388;
    • 3) 0.388 × 2 = 0 + 0.776;
    • 4) 0.776 × 2 = 1 + 0.552;
    • 5) 0.552 × 2 = 1 + 0.104;
    • 6) 0.104 × 2 = 0 + 0.208;
    • 7) 0.208 × 2 = 0 + 0.416;
    • 8) 0.416 × 2 = 0 + 0.832;
    • 9) 0.832 × 2 = 1 + 0.664;
    • 10) 0.664 × 2 = 1 + 0.328;
    • 11) 0.328 × 2 = 0 + 0.656;
    • 12) 0.656 × 2 = 1 + 0.312;
    • 13) 0.312 × 2 = 0 + 0.624;
    • 14) 0.624 × 2 = 1 + 0.248;
    • 15) 0.248 × 2 = 0 + 0.496;
    • 16) 0.496 × 2 = 0 + 0.992;
    • 17) 0.992 × 2 = 1 + 0.984;
    • 18) 0.984 × 2 = 1 + 0.968;
    • 19) 0.968 × 2 = 1 + 0.936;
    • 20) 0.936 × 2 = 1 + 0.872;
    • 21) 0.872 × 2 = 1 + 0.744;
    • 22) 0.744 × 2 = 1 + 0.488;
    • 23) 0.488 × 2 = 0 + 0.976;
    • 24) 0.976 × 2 = 1 + 0.952;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 23) 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:

    0.347(10) = 0.0101 1000 1101 0100 1111 1101(2)

  • 6. Summarizing - the positive number before normalization:

    25.347(10) = 1 1001.0101 1000 1101 0100 1111 1101(2)

  • 7. Normalize the binary representation of the number, shifting the decimal point 4 positions to the left so that only one non-zero digit stays to the left of the decimal point:

    25.347(10) =
    1 1001.0101 1000 1101 0100 1111 1101(2) =
    1 1001.0101 1000 1101 0100 1111 1101(2) × 20 =
    1.1001 0101 1000 1101 0100 1111 1101(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:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1001 0101 1000 1101 0100 1111 1101

  • 9. Adjust the exponent in 8 bit excess/bias notation and then convert it from decimal (base 10) to 8 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as already demonstrated above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(8-1) - 1 = (4 + 127)(10) = 131(10) =
    1000 0011(2)

  • 10. Normalize the mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal point) and adjust its length to 23 bits, by removing the excess bits from the right (losing precision...):

    Mantissa (not-normalized): 1.1001 0101 1000 1101 0100 1111 1101

    Mantissa (normalized): 100 1010 1100 0110 1010 0111

  • Conclusion:

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

    Exponent (8 bits) = 1000 0011

    Mantissa (23 bits) = 100 1010 1100 0110 1010 0111

  • Number -25.347, converted from the decimal system (base 10) to 32 bit single precision IEEE 754 binary floating point =
    1 - 1000 0011 - 100 1010 1100 0110 1010 0111