1 011 001 110 000 330 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1 011 001 110 000 330(10) to 32 bit single precision IEEE 754 binary floating point representation standard (1 bit for sign, 8 bits for exponent, 23 bits for mantissa)

What are the steps to convert decimal number
1 011 001 110 000 330(10) to 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;
  • 1 011 001 110 000 330 ÷ 2 = 505 500 555 000 165 + 0;
  • 505 500 555 000 165 ÷ 2 = 252 750 277 500 082 + 1;
  • 252 750 277 500 082 ÷ 2 = 126 375 138 750 041 + 0;
  • 126 375 138 750 041 ÷ 2 = 63 187 569 375 020 + 1;
  • 63 187 569 375 020 ÷ 2 = 31 593 784 687 510 + 0;
  • 31 593 784 687 510 ÷ 2 = 15 796 892 343 755 + 0;
  • 15 796 892 343 755 ÷ 2 = 7 898 446 171 877 + 1;
  • 7 898 446 171 877 ÷ 2 = 3 949 223 085 938 + 1;
  • 3 949 223 085 938 ÷ 2 = 1 974 611 542 969 + 0;
  • 1 974 611 542 969 ÷ 2 = 987 305 771 484 + 1;
  • 987 305 771 484 ÷ 2 = 493 652 885 742 + 0;
  • 493 652 885 742 ÷ 2 = 246 826 442 871 + 0;
  • 246 826 442 871 ÷ 2 = 123 413 221 435 + 1;
  • 123 413 221 435 ÷ 2 = 61 706 610 717 + 1;
  • 61 706 610 717 ÷ 2 = 30 853 305 358 + 1;
  • 30 853 305 358 ÷ 2 = 15 426 652 679 + 0;
  • 15 426 652 679 ÷ 2 = 7 713 326 339 + 1;
  • 7 713 326 339 ÷ 2 = 3 856 663 169 + 1;
  • 3 856 663 169 ÷ 2 = 1 928 331 584 + 1;
  • 1 928 331 584 ÷ 2 = 964 165 792 + 0;
  • 964 165 792 ÷ 2 = 482 082 896 + 0;
  • 482 082 896 ÷ 2 = 241 041 448 + 0;
  • 241 041 448 ÷ 2 = 120 520 724 + 0;
  • 120 520 724 ÷ 2 = 60 260 362 + 0;
  • 60 260 362 ÷ 2 = 30 130 181 + 0;
  • 30 130 181 ÷ 2 = 15 065 090 + 1;
  • 15 065 090 ÷ 2 = 7 532 545 + 0;
  • 7 532 545 ÷ 2 = 3 766 272 + 1;
  • 3 766 272 ÷ 2 = 1 883 136 + 0;
  • 1 883 136 ÷ 2 = 941 568 + 0;
  • 941 568 ÷ 2 = 470 784 + 0;
  • 470 784 ÷ 2 = 235 392 + 0;
  • 235 392 ÷ 2 = 117 696 + 0;
  • 117 696 ÷ 2 = 58 848 + 0;
  • 58 848 ÷ 2 = 29 424 + 0;
  • 29 424 ÷ 2 = 14 712 + 0;
  • 14 712 ÷ 2 = 7 356 + 0;
  • 7 356 ÷ 2 = 3 678 + 0;
  • 3 678 ÷ 2 = 1 839 + 0;
  • 1 839 ÷ 2 = 919 + 1;
  • 919 ÷ 2 = 459 + 1;
  • 459 ÷ 2 = 229 + 1;
  • 229 ÷ 2 = 114 + 1;
  • 114 ÷ 2 = 57 + 0;
  • 57 ÷ 2 = 28 + 1;
  • 28 ÷ 2 = 14 + 0;
  • 14 ÷ 2 = 7 + 0;
  • 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.

1 011 001 110 000 330(10) =


11 1001 0111 1000 0000 0000 1010 0000 0111 0111 0010 1100 1010(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:


1 011 001 110 000 330(10) =


11 1001 0111 1000 0000 0000 1010 0000 0111 0111 0010 1100 1010(2) =


11 1001 0111 1000 0000 0000 1010 0000 0111 0111 0010 1100 1010(2) × 20 =


1.1100 1011 1100 0000 0000 0101 0000 0011 1011 1001 0110 0101 0(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):
1.1100 1011 1100 0000 0000 0101 0000 0011 1011 1001 0110 0101 0


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. 110 0101 1110 0000 0000 0010 10 0000 0111 0111 0010 1100 1010 =


110 0101 1110 0000 0000 0010


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) =
110 0101 1110 0000 0000 0010


Decimal number 1 011 001 110 000 330 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1011 0000 - 110 0101 1110 0000 0000 0010


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