111 100 001 100 011 970 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 111 100 001 100 011 970(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
111 100 001 100 011 970(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;
  • 111 100 001 100 011 970 ÷ 2 = 55 550 000 550 005 985 + 0;
  • 55 550 000 550 005 985 ÷ 2 = 27 775 000 275 002 992 + 1;
  • 27 775 000 275 002 992 ÷ 2 = 13 887 500 137 501 496 + 0;
  • 13 887 500 137 501 496 ÷ 2 = 6 943 750 068 750 748 + 0;
  • 6 943 750 068 750 748 ÷ 2 = 3 471 875 034 375 374 + 0;
  • 3 471 875 034 375 374 ÷ 2 = 1 735 937 517 187 687 + 0;
  • 1 735 937 517 187 687 ÷ 2 = 867 968 758 593 843 + 1;
  • 867 968 758 593 843 ÷ 2 = 433 984 379 296 921 + 1;
  • 433 984 379 296 921 ÷ 2 = 216 992 189 648 460 + 1;
  • 216 992 189 648 460 ÷ 2 = 108 496 094 824 230 + 0;
  • 108 496 094 824 230 ÷ 2 = 54 248 047 412 115 + 0;
  • 54 248 047 412 115 ÷ 2 = 27 124 023 706 057 + 1;
  • 27 124 023 706 057 ÷ 2 = 13 562 011 853 028 + 1;
  • 13 562 011 853 028 ÷ 2 = 6 781 005 926 514 + 0;
  • 6 781 005 926 514 ÷ 2 = 3 390 502 963 257 + 0;
  • 3 390 502 963 257 ÷ 2 = 1 695 251 481 628 + 1;
  • 1 695 251 481 628 ÷ 2 = 847 625 740 814 + 0;
  • 847 625 740 814 ÷ 2 = 423 812 870 407 + 0;
  • 423 812 870 407 ÷ 2 = 211 906 435 203 + 1;
  • 211 906 435 203 ÷ 2 = 105 953 217 601 + 1;
  • 105 953 217 601 ÷ 2 = 52 976 608 800 + 1;
  • 52 976 608 800 ÷ 2 = 26 488 304 400 + 0;
  • 26 488 304 400 ÷ 2 = 13 244 152 200 + 0;
  • 13 244 152 200 ÷ 2 = 6 622 076 100 + 0;
  • 6 622 076 100 ÷ 2 = 3 311 038 050 + 0;
  • 3 311 038 050 ÷ 2 = 1 655 519 025 + 0;
  • 1 655 519 025 ÷ 2 = 827 759 512 + 1;
  • 827 759 512 ÷ 2 = 413 879 756 + 0;
  • 413 879 756 ÷ 2 = 206 939 878 + 0;
  • 206 939 878 ÷ 2 = 103 469 939 + 0;
  • 103 469 939 ÷ 2 = 51 734 969 + 1;
  • 51 734 969 ÷ 2 = 25 867 484 + 1;
  • 25 867 484 ÷ 2 = 12 933 742 + 0;
  • 12 933 742 ÷ 2 = 6 466 871 + 0;
  • 6 466 871 ÷ 2 = 3 233 435 + 1;
  • 3 233 435 ÷ 2 = 1 616 717 + 1;
  • 1 616 717 ÷ 2 = 808 358 + 1;
  • 808 358 ÷ 2 = 404 179 + 0;
  • 404 179 ÷ 2 = 202 089 + 1;
  • 202 089 ÷ 2 = 101 044 + 1;
  • 101 044 ÷ 2 = 50 522 + 0;
  • 50 522 ÷ 2 = 25 261 + 0;
  • 25 261 ÷ 2 = 12 630 + 1;
  • 12 630 ÷ 2 = 6 315 + 0;
  • 6 315 ÷ 2 = 3 157 + 1;
  • 3 157 ÷ 2 = 1 578 + 1;
  • 1 578 ÷ 2 = 789 + 0;
  • 789 ÷ 2 = 394 + 1;
  • 394 ÷ 2 = 197 + 0;
  • 197 ÷ 2 = 98 + 1;
  • 98 ÷ 2 = 49 + 0;
  • 49 ÷ 2 = 24 + 1;
  • 24 ÷ 2 = 12 + 0;
  • 12 ÷ 2 = 6 + 0;
  • 6 ÷ 2 = 3 + 0;
  • 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.

111 100 001 100 011 970(10) =


1 1000 1010 1011 0100 1101 1100 1100 0100 0001 1100 1001 1001 1100 0010(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 56 positions to the left, so that only one non zero digit remains to the left of it:


111 100 001 100 011 970(10) =


1 1000 1010 1011 0100 1101 1100 1100 0100 0001 1100 1001 1001 1100 0010(2) =


1 1000 1010 1011 0100 1101 1100 1100 0100 0001 1100 1001 1001 1100 0010(2) × 20 =


1.1000 1010 1011 0100 1101 1100 1100 0100 0001 1100 1001 1001 1100 0010(2) × 256


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): 56


Mantissa (not normalized):
1.1000 1010 1011 0100 1101 1100 1100 0100 0001 1100 1001 1001 1100 0010


5. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


56 + 2(8-1) - 1 =


(56 + 127)(10) =


183(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;
  • 183 ÷ 2 = 91 + 1;
  • 91 ÷ 2 = 45 + 1;
  • 45 ÷ 2 = 22 + 1;
  • 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) =


183(10) =


1011 0111(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. 100 0101 0101 1010 0110 1110 0 1100 0100 0001 1100 1001 1001 1100 0010 =


100 0101 0101 1010 0110 1110


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 0111


Mantissa (23 bits) =
100 0101 0101 1010 0110 1110


Decimal number 111 100 001 100 011 970 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1011 0111 - 100 0101 0101 1010 0110 1110


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