10 000 010 111 110 100 110 002 862 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 10 000 010 111 110 100 110 002 862(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
10 000 010 111 110 100 110 002 862(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;
  • 10 000 010 111 110 100 110 002 862 ÷ 2 = 5 000 005 055 555 050 055 001 431 + 0;
  • 5 000 005 055 555 050 055 001 431 ÷ 2 = 2 500 002 527 777 525 027 500 715 + 1;
  • 2 500 002 527 777 525 027 500 715 ÷ 2 = 1 250 001 263 888 762 513 750 357 + 1;
  • 1 250 001 263 888 762 513 750 357 ÷ 2 = 625 000 631 944 381 256 875 178 + 1;
  • 625 000 631 944 381 256 875 178 ÷ 2 = 312 500 315 972 190 628 437 589 + 0;
  • 312 500 315 972 190 628 437 589 ÷ 2 = 156 250 157 986 095 314 218 794 + 1;
  • 156 250 157 986 095 314 218 794 ÷ 2 = 78 125 078 993 047 657 109 397 + 0;
  • 78 125 078 993 047 657 109 397 ÷ 2 = 39 062 539 496 523 828 554 698 + 1;
  • 39 062 539 496 523 828 554 698 ÷ 2 = 19 531 269 748 261 914 277 349 + 0;
  • 19 531 269 748 261 914 277 349 ÷ 2 = 9 765 634 874 130 957 138 674 + 1;
  • 9 765 634 874 130 957 138 674 ÷ 2 = 4 882 817 437 065 478 569 337 + 0;
  • 4 882 817 437 065 478 569 337 ÷ 2 = 2 441 408 718 532 739 284 668 + 1;
  • 2 441 408 718 532 739 284 668 ÷ 2 = 1 220 704 359 266 369 642 334 + 0;
  • 1 220 704 359 266 369 642 334 ÷ 2 = 610 352 179 633 184 821 167 + 0;
  • 610 352 179 633 184 821 167 ÷ 2 = 305 176 089 816 592 410 583 + 1;
  • 305 176 089 816 592 410 583 ÷ 2 = 152 588 044 908 296 205 291 + 1;
  • 152 588 044 908 296 205 291 ÷ 2 = 76 294 022 454 148 102 645 + 1;
  • 76 294 022 454 148 102 645 ÷ 2 = 38 147 011 227 074 051 322 + 1;
  • 38 147 011 227 074 051 322 ÷ 2 = 19 073 505 613 537 025 661 + 0;
  • 19 073 505 613 537 025 661 ÷ 2 = 9 536 752 806 768 512 830 + 1;
  • 9 536 752 806 768 512 830 ÷ 2 = 4 768 376 403 384 256 415 + 0;
  • 4 768 376 403 384 256 415 ÷ 2 = 2 384 188 201 692 128 207 + 1;
  • 2 384 188 201 692 128 207 ÷ 2 = 1 192 094 100 846 064 103 + 1;
  • 1 192 094 100 846 064 103 ÷ 2 = 596 047 050 423 032 051 + 1;
  • 596 047 050 423 032 051 ÷ 2 = 298 023 525 211 516 025 + 1;
  • 298 023 525 211 516 025 ÷ 2 = 149 011 762 605 758 012 + 1;
  • 149 011 762 605 758 012 ÷ 2 = 74 505 881 302 879 006 + 0;
  • 74 505 881 302 879 006 ÷ 2 = 37 252 940 651 439 503 + 0;
  • 37 252 940 651 439 503 ÷ 2 = 18 626 470 325 719 751 + 1;
  • 18 626 470 325 719 751 ÷ 2 = 9 313 235 162 859 875 + 1;
  • 9 313 235 162 859 875 ÷ 2 = 4 656 617 581 429 937 + 1;
  • 4 656 617 581 429 937 ÷ 2 = 2 328 308 790 714 968 + 1;
  • 2 328 308 790 714 968 ÷ 2 = 1 164 154 395 357 484 + 0;
  • 1 164 154 395 357 484 ÷ 2 = 582 077 197 678 742 + 0;
  • 582 077 197 678 742 ÷ 2 = 291 038 598 839 371 + 0;
  • 291 038 598 839 371 ÷ 2 = 145 519 299 419 685 + 1;
  • 145 519 299 419 685 ÷ 2 = 72 759 649 709 842 + 1;
  • 72 759 649 709 842 ÷ 2 = 36 379 824 854 921 + 0;
  • 36 379 824 854 921 ÷ 2 = 18 189 912 427 460 + 1;
  • 18 189 912 427 460 ÷ 2 = 9 094 956 213 730 + 0;
  • 9 094 956 213 730 ÷ 2 = 4 547 478 106 865 + 0;
  • 4 547 478 106 865 ÷ 2 = 2 273 739 053 432 + 1;
  • 2 273 739 053 432 ÷ 2 = 1 136 869 526 716 + 0;
  • 1 136 869 526 716 ÷ 2 = 568 434 763 358 + 0;
  • 568 434 763 358 ÷ 2 = 284 217 381 679 + 0;
  • 284 217 381 679 ÷ 2 = 142 108 690 839 + 1;
  • 142 108 690 839 ÷ 2 = 71 054 345 419 + 1;
  • 71 054 345 419 ÷ 2 = 35 527 172 709 + 1;
  • 35 527 172 709 ÷ 2 = 17 763 586 354 + 1;
  • 17 763 586 354 ÷ 2 = 8 881 793 177 + 0;
  • 8 881 793 177 ÷ 2 = 4 440 896 588 + 1;
  • 4 440 896 588 ÷ 2 = 2 220 448 294 + 0;
  • 2 220 448 294 ÷ 2 = 1 110 224 147 + 0;
  • 1 110 224 147 ÷ 2 = 555 112 073 + 1;
  • 555 112 073 ÷ 2 = 277 556 036 + 1;
  • 277 556 036 ÷ 2 = 138 778 018 + 0;
  • 138 778 018 ÷ 2 = 69 389 009 + 0;
  • 69 389 009 ÷ 2 = 34 694 504 + 1;
  • 34 694 504 ÷ 2 = 17 347 252 + 0;
  • 17 347 252 ÷ 2 = 8 673 626 + 0;
  • 8 673 626 ÷ 2 = 4 336 813 + 0;
  • 4 336 813 ÷ 2 = 2 168 406 + 1;
  • 2 168 406 ÷ 2 = 1 084 203 + 0;
  • 1 084 203 ÷ 2 = 542 101 + 1;
  • 542 101 ÷ 2 = 271 050 + 1;
  • 271 050 ÷ 2 = 135 525 + 0;
  • 135 525 ÷ 2 = 67 762 + 1;
  • 67 762 ÷ 2 = 33 881 + 0;
  • 33 881 ÷ 2 = 16 940 + 1;
  • 16 940 ÷ 2 = 8 470 + 0;
  • 8 470 ÷ 2 = 4 235 + 0;
  • 4 235 ÷ 2 = 2 117 + 1;
  • 2 117 ÷ 2 = 1 058 + 1;
  • 1 058 ÷ 2 = 529 + 0;
  • 529 ÷ 2 = 264 + 1;
  • 264 ÷ 2 = 132 + 0;
  • 132 ÷ 2 = 66 + 0;
  • 66 ÷ 2 = 33 + 0;
  • 33 ÷ 2 = 16 + 1;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 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.

10 000 010 111 110 100 110 002 862(10) =


1000 0100 0101 1001 0101 1010 0010 0110 0101 1110 0010 0101 1000 1111 0011 1110 1011 1100 1010 1010 1110(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 83 positions to the left, so that only one non zero digit remains to the left of it:


10 000 010 111 110 100 110 002 862(10) =


1000 0100 0101 1001 0101 1010 0010 0110 0101 1110 0010 0101 1000 1111 0011 1110 1011 1100 1010 1010 1110(2) =


1000 0100 0101 1001 0101 1010 0010 0110 0101 1110 0010 0101 1000 1111 0011 1110 1011 1100 1010 1010 1110(2) × 20 =


1.0000 1000 1011 0010 1011 0100 0100 1100 1011 1100 0100 1011 0001 1110 0111 1101 0111 1001 0101 0101 110(2) × 283


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): 83


Mantissa (not normalized):
1.0000 1000 1011 0010 1011 0100 0100 1100 1011 1100 0100 1011 0001 1110 0111 1101 0111 1001 0101 0101 110


5. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


83 + 2(8-1) - 1 =


(83 + 127)(10) =


210(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;
  • 210 ÷ 2 = 105 + 0;
  • 105 ÷ 2 = 52 + 1;
  • 52 ÷ 2 = 26 + 0;
  • 26 ÷ 2 = 13 + 0;
  • 13 ÷ 2 = 6 + 1;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


210(10) =


1101 0010(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. 000 0100 0101 1001 0101 1010 0010 0110 0101 1110 0010 0101 1000 1111 0011 1110 1011 1100 1010 1010 1110 =


000 0100 0101 1001 0101 1010


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) =
1101 0010


Mantissa (23 bits) =
000 0100 0101 1001 0101 1010


Decimal number 10 000 010 111 110 100 110 002 862 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1101 0010 - 000 0100 0101 1001 0101 1010


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