-4 022 121 121 121 190.9 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -4 022 121 121 121 190.9(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
-4 022 121 121 121 190.9(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. Start with the positive version of the number:

|-4 022 121 121 121 190.9| = 4 022 121 121 121 190.9


2. First, convert to binary (in base 2) the integer part: 4 022 121 121 121 190.
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;
  • 4 022 121 121 121 190 ÷ 2 = 2 011 060 560 560 595 + 0;
  • 2 011 060 560 560 595 ÷ 2 = 1 005 530 280 280 297 + 1;
  • 1 005 530 280 280 297 ÷ 2 = 502 765 140 140 148 + 1;
  • 502 765 140 140 148 ÷ 2 = 251 382 570 070 074 + 0;
  • 251 382 570 070 074 ÷ 2 = 125 691 285 035 037 + 0;
  • 125 691 285 035 037 ÷ 2 = 62 845 642 517 518 + 1;
  • 62 845 642 517 518 ÷ 2 = 31 422 821 258 759 + 0;
  • 31 422 821 258 759 ÷ 2 = 15 711 410 629 379 + 1;
  • 15 711 410 629 379 ÷ 2 = 7 855 705 314 689 + 1;
  • 7 855 705 314 689 ÷ 2 = 3 927 852 657 344 + 1;
  • 3 927 852 657 344 ÷ 2 = 1 963 926 328 672 + 0;
  • 1 963 926 328 672 ÷ 2 = 981 963 164 336 + 0;
  • 981 963 164 336 ÷ 2 = 490 981 582 168 + 0;
  • 490 981 582 168 ÷ 2 = 245 490 791 084 + 0;
  • 245 490 791 084 ÷ 2 = 122 745 395 542 + 0;
  • 122 745 395 542 ÷ 2 = 61 372 697 771 + 0;
  • 61 372 697 771 ÷ 2 = 30 686 348 885 + 1;
  • 30 686 348 885 ÷ 2 = 15 343 174 442 + 1;
  • 15 343 174 442 ÷ 2 = 7 671 587 221 + 0;
  • 7 671 587 221 ÷ 2 = 3 835 793 610 + 1;
  • 3 835 793 610 ÷ 2 = 1 917 896 805 + 0;
  • 1 917 896 805 ÷ 2 = 958 948 402 + 1;
  • 958 948 402 ÷ 2 = 479 474 201 + 0;
  • 479 474 201 ÷ 2 = 239 737 100 + 1;
  • 239 737 100 ÷ 2 = 119 868 550 + 0;
  • 119 868 550 ÷ 2 = 59 934 275 + 0;
  • 59 934 275 ÷ 2 = 29 967 137 + 1;
  • 29 967 137 ÷ 2 = 14 983 568 + 1;
  • 14 983 568 ÷ 2 = 7 491 784 + 0;
  • 7 491 784 ÷ 2 = 3 745 892 + 0;
  • 3 745 892 ÷ 2 = 1 872 946 + 0;
  • 1 872 946 ÷ 2 = 936 473 + 0;
  • 936 473 ÷ 2 = 468 236 + 1;
  • 468 236 ÷ 2 = 234 118 + 0;
  • 234 118 ÷ 2 = 117 059 + 0;
  • 117 059 ÷ 2 = 58 529 + 1;
  • 58 529 ÷ 2 = 29 264 + 1;
  • 29 264 ÷ 2 = 14 632 + 0;
  • 14 632 ÷ 2 = 7 316 + 0;
  • 7 316 ÷ 2 = 3 658 + 0;
  • 3 658 ÷ 2 = 1 829 + 0;
  • 1 829 ÷ 2 = 914 + 1;
  • 914 ÷ 2 = 457 + 0;
  • 457 ÷ 2 = 228 + 1;
  • 228 ÷ 2 = 114 + 0;
  • 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;

3. Construct the base 2 representation of the integer part of the number.

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

4 022 121 121 121 190(10) =


1110 0100 1010 0001 1001 0000 1100 1010 1011 0000 0011 1010 0110(2)


4. Convert to binary (base 2) the fractional part: 0.9.

Multiply it repeatedly by 2.


Keep track of each integer part of the results.


Stop when we get a fractional part that is equal to zero.


  • #) multiplying = integer + fractional part;
  • 1) 0.9 × 2 = 1 + 0.8;
  • 2) 0.8 × 2 = 1 + 0.6;
  • 3) 0.6 × 2 = 1 + 0.2;
  • 4) 0.2 × 2 = 0 + 0.4;
  • 5) 0.4 × 2 = 0 + 0.8;
  • 6) 0.8 × 2 = 1 + 0.6;
  • 7) 0.6 × 2 = 1 + 0.2;
  • 8) 0.2 × 2 = 0 + 0.4;
  • 9) 0.4 × 2 = 0 + 0.8;
  • 10) 0.8 × 2 = 1 + 0.6;
  • 11) 0.6 × 2 = 1 + 0.2;
  • 12) 0.2 × 2 = 0 + 0.4;
  • 13) 0.4 × 2 = 0 + 0.8;
  • 14) 0.8 × 2 = 1 + 0.6;
  • 15) 0.6 × 2 = 1 + 0.2;
  • 16) 0.2 × 2 = 0 + 0.4;
  • 17) 0.4 × 2 = 0 + 0.8;
  • 18) 0.8 × 2 = 1 + 0.6;
  • 19) 0.6 × 2 = 1 + 0.2;
  • 20) 0.2 × 2 = 0 + 0.4;
  • 21) 0.4 × 2 = 0 + 0.8;
  • 22) 0.8 × 2 = 1 + 0.6;
  • 23) 0.6 × 2 = 1 + 0.2;
  • 24) 0.2 × 2 = 0 + 0.4;

We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit) and at least one integer that was different from zero => FULL STOP (Losing precision - the converted number we get in the end will be just a very good approximation of the initial one).


5. Construct the base 2 representation of the fractional part of the number.

Take all the integer parts of the multiplying operations, starting from the top of the constructed list above:


0.9(10) =


0.1110 0110 0110 0110 0110 0110(2)

6. Positive number before normalization:

4 022 121 121 121 190.9(10) =


1110 0100 1010 0001 1001 0000 1100 1010 1011 0000 0011 1010 0110.1110 0110 0110 0110 0110 0110(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 51 positions to the left, so that only one non zero digit remains to the left of it:


4 022 121 121 121 190.9(10) =


1110 0100 1010 0001 1001 0000 1100 1010 1011 0000 0011 1010 0110.1110 0110 0110 0110 0110 0110(2) =


1110 0100 1010 0001 1001 0000 1100 1010 1011 0000 0011 1010 0110.1110 0110 0110 0110 0110 0110(2) × 20 =


1.1100 1001 0100 0011 0010 0001 1001 0101 0110 0000 0111 0100 1101 1100 1100 1100 1100 1100 110(2) × 251


8. 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 1 (a negative number)


Exponent (unadjusted): 51


Mantissa (not normalized):
1.1100 1001 0100 0011 0010 0001 1001 0101 0110 0000 0111 0100 1101 1100 1100 1100 1100 1100 110


9. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


51 + 2(8-1) - 1 =


(51 + 127)(10) =


178(10)


10. 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;
  • 178 ÷ 2 = 89 + 0;
  • 89 ÷ 2 = 44 + 1;
  • 44 ÷ 2 = 22 + 0;
  • 22 ÷ 2 = 11 + 0;
  • 11 ÷ 2 = 5 + 1;
  • 5 ÷ 2 = 2 + 1;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

11. Construct the base 2 representation of the adjusted exponent.

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


Exponent (adjusted) =


178(10) =


1011 0010(2)


12. 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 0100 1010 0001 1001 0000 1100 1010 1011 0000 0011 1010 0110 1110 0110 0110 0110 0110 0110 =


110 0100 1010 0001 1001 0000


13. The three elements that make up the number's 32 bit single precision IEEE 754 binary floating point representation:

Sign (1 bit) =
1 (a negative number)


Exponent (8 bits) =
1011 0010


Mantissa (23 bits) =
110 0100 1010 0001 1001 0000


Decimal number -4 022 121 121 121 190.9 converted to 32 bit single precision IEEE 754 binary floating point representation:

1 - 1011 0010 - 110 0100 1010 0001 1001 0000


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