3.402 823 670 000 000 000 000 000 000 000 000 000 015 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 3.402 823 670 000 000 000 000 000 000 000 000 000 015(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
3.402 823 670 000 000 000 000 000 000 000 000 000 015(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. First, convert to binary (in base 2) the integer part: 3.
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;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

2. 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.

3(10) =


11(2)


3. Convert to binary (base 2) the fractional part: 0.402 823 670 000 000 000 000 000 000 000 000 000 015.

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) 0.402 823 670 000 000 000 000 000 000 000 000 000 015 × 2 = 0 + 0.805 647 340 000 000 000 000 000 000 000 000 000 03;
  • 2) 0.805 647 340 000 000 000 000 000 000 000 000 000 03 × 2 = 1 + 0.611 294 680 000 000 000 000 000 000 000 000 000 06;
  • 3) 0.611 294 680 000 000 000 000 000 000 000 000 000 06 × 2 = 1 + 0.222 589 360 000 000 000 000 000 000 000 000 000 12;
  • 4) 0.222 589 360 000 000 000 000 000 000 000 000 000 12 × 2 = 0 + 0.445 178 720 000 000 000 000 000 000 000 000 000 24;
  • 5) 0.445 178 720 000 000 000 000 000 000 000 000 000 24 × 2 = 0 + 0.890 357 440 000 000 000 000 000 000 000 000 000 48;
  • 6) 0.890 357 440 000 000 000 000 000 000 000 000 000 48 × 2 = 1 + 0.780 714 880 000 000 000 000 000 000 000 000 000 96;
  • 7) 0.780 714 880 000 000 000 000 000 000 000 000 000 96 × 2 = 1 + 0.561 429 760 000 000 000 000 000 000 000 000 001 92;
  • 8) 0.561 429 760 000 000 000 000 000 000 000 000 001 92 × 2 = 1 + 0.122 859 520 000 000 000 000 000 000 000 000 003 84;
  • 9) 0.122 859 520 000 000 000 000 000 000 000 000 003 84 × 2 = 0 + 0.245 719 040 000 000 000 000 000 000 000 000 007 68;
  • 10) 0.245 719 040 000 000 000 000 000 000 000 000 007 68 × 2 = 0 + 0.491 438 080 000 000 000 000 000 000 000 000 015 36;
  • 11) 0.491 438 080 000 000 000 000 000 000 000 000 015 36 × 2 = 0 + 0.982 876 160 000 000 000 000 000 000 000 000 030 72;
  • 12) 0.982 876 160 000 000 000 000 000 000 000 000 030 72 × 2 = 1 + 0.965 752 320 000 000 000 000 000 000 000 000 061 44;
  • 13) 0.965 752 320 000 000 000 000 000 000 000 000 061 44 × 2 = 1 + 0.931 504 640 000 000 000 000 000 000 000 000 122 88;
  • 14) 0.931 504 640 000 000 000 000 000 000 000 000 122 88 × 2 = 1 + 0.863 009 280 000 000 000 000 000 000 000 000 245 76;
  • 15) 0.863 009 280 000 000 000 000 000 000 000 000 245 76 × 2 = 1 + 0.726 018 560 000 000 000 000 000 000 000 000 491 52;
  • 16) 0.726 018 560 000 000 000 000 000 000 000 000 491 52 × 2 = 1 + 0.452 037 120 000 000 000 000 000 000 000 000 983 04;
  • 17) 0.452 037 120 000 000 000 000 000 000 000 000 983 04 × 2 = 0 + 0.904 074 240 000 000 000 000 000 000 000 001 966 08;
  • 18) 0.904 074 240 000 000 000 000 000 000 000 001 966 08 × 2 = 1 + 0.808 148 480 000 000 000 000 000 000 000 003 932 16;
  • 19) 0.808 148 480 000 000 000 000 000 000 000 003 932 16 × 2 = 1 + 0.616 296 960 000 000 000 000 000 000 000 007 864 32;
  • 20) 0.616 296 960 000 000 000 000 000 000 000 007 864 32 × 2 = 1 + 0.232 593 920 000 000 000 000 000 000 000 015 728 64;
  • 21) 0.232 593 920 000 000 000 000 000 000 000 015 728 64 × 2 = 0 + 0.465 187 840 000 000 000 000 000 000 000 031 457 28;
  • 22) 0.465 187 840 000 000 000 000 000 000 000 031 457 28 × 2 = 0 + 0.930 375 680 000 000 000 000 000 000 000 062 914 56;
  • 23) 0.930 375 680 000 000 000 000 000 000 000 062 914 56 × 2 = 1 + 0.860 751 360 000 000 000 000 000 000 000 125 829 12;
  • 24) 0.860 751 360 000 000 000 000 000 000 000 125 829 12 × 2 = 1 + 0.721 502 720 000 000 000 000 000 000 000 251 658 24;

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).


4. 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:


0.402 823 670 000 000 000 000 000 000 000 000 000 015(10) =


0.0110 0111 0001 1111 0111 0011(2)

5. Positive number before normalization:

3.402 823 670 000 000 000 000 000 000 000 000 000 015(10) =


11.0110 0111 0001 1111 0111 0011(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 1 positions to the left, so that only one non zero digit remains to the left of it:


3.402 823 670 000 000 000 000 000 000 000 000 000 015(10) =


11.0110 0111 0001 1111 0111 0011(2) =


11.0110 0111 0001 1111 0111 0011(2) × 20 =


1.1011 0011 1000 1111 1011 1001 1(2) × 21


7. 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): 1


Mantissa (not normalized):
1.1011 0011 1000 1111 1011 1001 1


8. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


1 + 2(8-1) - 1 =


(1 + 127)(10) =


128(10)


9. 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;
  • 128 ÷ 2 = 64 + 0;
  • 64 ÷ 2 = 32 + 0;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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

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


Exponent (adjusted) =


128(10) =


1000 0000(2)


11. 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 1001 1100 0111 1101 1100 11 =


101 1001 1100 0111 1101 1100


12. 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) =
1000 0000


Mantissa (23 bits) =
101 1001 1100 0111 1101 1100


Decimal number 3.402 823 670 000 000 000 000 000 000 000 000 000 015 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1000 0000 - 101 1001 1100 0111 1101 1100

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