1 001 111 000 010 009 864 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1 001 111 000 010 009 864(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
1 001 111 000 010 009 864(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;
  • 1 001 111 000 010 009 864 ÷ 2 = 500 555 500 005 004 932 + 0;
  • 500 555 500 005 004 932 ÷ 2 = 250 277 750 002 502 466 + 0;
  • 250 277 750 002 502 466 ÷ 2 = 125 138 875 001 251 233 + 0;
  • 125 138 875 001 251 233 ÷ 2 = 62 569 437 500 625 616 + 1;
  • 62 569 437 500 625 616 ÷ 2 = 31 284 718 750 312 808 + 0;
  • 31 284 718 750 312 808 ÷ 2 = 15 642 359 375 156 404 + 0;
  • 15 642 359 375 156 404 ÷ 2 = 7 821 179 687 578 202 + 0;
  • 7 821 179 687 578 202 ÷ 2 = 3 910 589 843 789 101 + 0;
  • 3 910 589 843 789 101 ÷ 2 = 1 955 294 921 894 550 + 1;
  • 1 955 294 921 894 550 ÷ 2 = 977 647 460 947 275 + 0;
  • 977 647 460 947 275 ÷ 2 = 488 823 730 473 637 + 1;
  • 488 823 730 473 637 ÷ 2 = 244 411 865 236 818 + 1;
  • 244 411 865 236 818 ÷ 2 = 122 205 932 618 409 + 0;
  • 122 205 932 618 409 ÷ 2 = 61 102 966 309 204 + 1;
  • 61 102 966 309 204 ÷ 2 = 30 551 483 154 602 + 0;
  • 30 551 483 154 602 ÷ 2 = 15 275 741 577 301 + 0;
  • 15 275 741 577 301 ÷ 2 = 7 637 870 788 650 + 1;
  • 7 637 870 788 650 ÷ 2 = 3 818 935 394 325 + 0;
  • 3 818 935 394 325 ÷ 2 = 1 909 467 697 162 + 1;
  • 1 909 467 697 162 ÷ 2 = 954 733 848 581 + 0;
  • 954 733 848 581 ÷ 2 = 477 366 924 290 + 1;
  • 477 366 924 290 ÷ 2 = 238 683 462 145 + 0;
  • 238 683 462 145 ÷ 2 = 119 341 731 072 + 1;
  • 119 341 731 072 ÷ 2 = 59 670 865 536 + 0;
  • 59 670 865 536 ÷ 2 = 29 835 432 768 + 0;
  • 29 835 432 768 ÷ 2 = 14 917 716 384 + 0;
  • 14 917 716 384 ÷ 2 = 7 458 858 192 + 0;
  • 7 458 858 192 ÷ 2 = 3 729 429 096 + 0;
  • 3 729 429 096 ÷ 2 = 1 864 714 548 + 0;
  • 1 864 714 548 ÷ 2 = 932 357 274 + 0;
  • 932 357 274 ÷ 2 = 466 178 637 + 0;
  • 466 178 637 ÷ 2 = 233 089 318 + 1;
  • 233 089 318 ÷ 2 = 116 544 659 + 0;
  • 116 544 659 ÷ 2 = 58 272 329 + 1;
  • 58 272 329 ÷ 2 = 29 136 164 + 1;
  • 29 136 164 ÷ 2 = 14 568 082 + 0;
  • 14 568 082 ÷ 2 = 7 284 041 + 0;
  • 7 284 041 ÷ 2 = 3 642 020 + 1;
  • 3 642 020 ÷ 2 = 1 821 010 + 0;
  • 1 821 010 ÷ 2 = 910 505 + 0;
  • 910 505 ÷ 2 = 455 252 + 1;
  • 455 252 ÷ 2 = 227 626 + 0;
  • 227 626 ÷ 2 = 113 813 + 0;
  • 113 813 ÷ 2 = 56 906 + 1;
  • 56 906 ÷ 2 = 28 453 + 0;
  • 28 453 ÷ 2 = 14 226 + 1;
  • 14 226 ÷ 2 = 7 113 + 0;
  • 7 113 ÷ 2 = 3 556 + 1;
  • 3 556 ÷ 2 = 1 778 + 0;
  • 1 778 ÷ 2 = 889 + 0;
  • 889 ÷ 2 = 444 + 1;
  • 444 ÷ 2 = 222 + 0;
  • 222 ÷ 2 = 111 + 0;
  • 111 ÷ 2 = 55 + 1;
  • 55 ÷ 2 = 27 + 1;
  • 27 ÷ 2 = 13 + 1;
  • 13 ÷ 2 = 6 + 1;
  • 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.

1 001 111 000 010 009 864(10) =


1101 1110 0100 1010 1001 0010 0110 1000 0000 0101 0101 0010 1101 0000 1000(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 59 positions to the left, so that only one non zero digit remains to the left of it:


1 001 111 000 010 009 864(10) =


1101 1110 0100 1010 1001 0010 0110 1000 0000 0101 0101 0010 1101 0000 1000(2) =


1101 1110 0100 1010 1001 0010 0110 1000 0000 0101 0101 0010 1101 0000 1000(2) × 20 =


1.1011 1100 1001 0101 0010 0100 1101 0000 0000 1010 1010 0101 1010 0001 000(2) × 259


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): 59


Mantissa (not normalized):
1.1011 1100 1001 0101 0010 0100 1101 0000 0000 1010 1010 0101 1010 0001 000


5. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


59 + 2(8-1) - 1 =


(59 + 127)(10) =


186(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;
  • 186 ÷ 2 = 93 + 0;
  • 93 ÷ 2 = 46 + 1;
  • 46 ÷ 2 = 23 + 0;
  • 23 ÷ 2 = 11 + 1;
  • 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) =


186(10) =


1011 1010(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. 101 1110 0100 1010 1001 0010 0110 1000 0000 0101 0101 0010 1101 0000 1000 =


101 1110 0100 1010 1001 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 1010


Mantissa (23 bits) =
101 1110 0100 1010 1001 0010


Decimal number 1 001 111 000 010 009 864 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1011 1010 - 101 1110 0100 1010 1001 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