842 883 781 014 585 978 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 842 883 781 014 585 978(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
842 883 781 014 585 978(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;
  • 842 883 781 014 585 978 ÷ 2 = 421 441 890 507 292 989 + 0;
  • 421 441 890 507 292 989 ÷ 2 = 210 720 945 253 646 494 + 1;
  • 210 720 945 253 646 494 ÷ 2 = 105 360 472 626 823 247 + 0;
  • 105 360 472 626 823 247 ÷ 2 = 52 680 236 313 411 623 + 1;
  • 52 680 236 313 411 623 ÷ 2 = 26 340 118 156 705 811 + 1;
  • 26 340 118 156 705 811 ÷ 2 = 13 170 059 078 352 905 + 1;
  • 13 170 059 078 352 905 ÷ 2 = 6 585 029 539 176 452 + 1;
  • 6 585 029 539 176 452 ÷ 2 = 3 292 514 769 588 226 + 0;
  • 3 292 514 769 588 226 ÷ 2 = 1 646 257 384 794 113 + 0;
  • 1 646 257 384 794 113 ÷ 2 = 823 128 692 397 056 + 1;
  • 823 128 692 397 056 ÷ 2 = 411 564 346 198 528 + 0;
  • 411 564 346 198 528 ÷ 2 = 205 782 173 099 264 + 0;
  • 205 782 173 099 264 ÷ 2 = 102 891 086 549 632 + 0;
  • 102 891 086 549 632 ÷ 2 = 51 445 543 274 816 + 0;
  • 51 445 543 274 816 ÷ 2 = 25 722 771 637 408 + 0;
  • 25 722 771 637 408 ÷ 2 = 12 861 385 818 704 + 0;
  • 12 861 385 818 704 ÷ 2 = 6 430 692 909 352 + 0;
  • 6 430 692 909 352 ÷ 2 = 3 215 346 454 676 + 0;
  • 3 215 346 454 676 ÷ 2 = 1 607 673 227 338 + 0;
  • 1 607 673 227 338 ÷ 2 = 803 836 613 669 + 0;
  • 803 836 613 669 ÷ 2 = 401 918 306 834 + 1;
  • 401 918 306 834 ÷ 2 = 200 959 153 417 + 0;
  • 200 959 153 417 ÷ 2 = 100 479 576 708 + 1;
  • 100 479 576 708 ÷ 2 = 50 239 788 354 + 0;
  • 50 239 788 354 ÷ 2 = 25 119 894 177 + 0;
  • 25 119 894 177 ÷ 2 = 12 559 947 088 + 1;
  • 12 559 947 088 ÷ 2 = 6 279 973 544 + 0;
  • 6 279 973 544 ÷ 2 = 3 139 986 772 + 0;
  • 3 139 986 772 ÷ 2 = 1 569 993 386 + 0;
  • 1 569 993 386 ÷ 2 = 784 996 693 + 0;
  • 784 996 693 ÷ 2 = 392 498 346 + 1;
  • 392 498 346 ÷ 2 = 196 249 173 + 0;
  • 196 249 173 ÷ 2 = 98 124 586 + 1;
  • 98 124 586 ÷ 2 = 49 062 293 + 0;
  • 49 062 293 ÷ 2 = 24 531 146 + 1;
  • 24 531 146 ÷ 2 = 12 265 573 + 0;
  • 12 265 573 ÷ 2 = 6 132 786 + 1;
  • 6 132 786 ÷ 2 = 3 066 393 + 0;
  • 3 066 393 ÷ 2 = 1 533 196 + 1;
  • 1 533 196 ÷ 2 = 766 598 + 0;
  • 766 598 ÷ 2 = 383 299 + 0;
  • 383 299 ÷ 2 = 191 649 + 1;
  • 191 649 ÷ 2 = 95 824 + 1;
  • 95 824 ÷ 2 = 47 912 + 0;
  • 47 912 ÷ 2 = 23 956 + 0;
  • 23 956 ÷ 2 = 11 978 + 0;
  • 11 978 ÷ 2 = 5 989 + 0;
  • 5 989 ÷ 2 = 2 994 + 1;
  • 2 994 ÷ 2 = 1 497 + 0;
  • 1 497 ÷ 2 = 748 + 1;
  • 748 ÷ 2 = 374 + 0;
  • 374 ÷ 2 = 187 + 0;
  • 187 ÷ 2 = 93 + 1;
  • 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;

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

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

842 883 781 014 585 978(10) =


1011 1011 0010 1000 0110 0101 0101 0100 0010 0101 0000 0000 0010 0111 1010(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:


842 883 781 014 585 978(10) =


1011 1011 0010 1000 0110 0101 0101 0100 0010 0101 0000 0000 0010 0111 1010(2) =


1011 1011 0010 1000 0110 0101 0101 0100 0010 0101 0000 0000 0010 0111 1010(2) × 20 =


1.0111 0110 0101 0000 1100 1010 1010 1000 0100 1010 0000 0000 0100 1111 010(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):
1.0111 0110 0101 0000 1100 1010 1010 1000 0100 1010 0000 0000 0100 1111 010


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. 011 1011 0010 1000 0110 0101 0101 0100 0010 0101 0000 0000 0010 0111 1010 =


011 1011 0010 1000 0110 0101


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) =
011 1011 0010 1000 0110 0101


Decimal number 842 883 781 014 585 978 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1011 1010 - 011 1011 0010 1000 0110 0101


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