-0.000 000 000 742 147 676 646 720 5 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 000 000 742 147 676 646 720 5(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
-0.000 000 000 742 147 676 646 720 5(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:

|-0.000 000 000 742 147 676 646 720 5| = 0.000 000 000 742 147 676 646 720 5


2. First, convert to binary (in base 2) the integer part: 0.
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;
  • 0 ÷ 2 = 0 + 0;

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.

0(10) =


0(2)


4. Convert to binary (base 2) the fractional part: 0.000 000 000 742 147 676 646 720 5.

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) 0.000 000 000 742 147 676 646 720 5 × 2 = 0 + 0.000 000 001 484 295 353 293 441;
  • 2) 0.000 000 001 484 295 353 293 441 × 2 = 0 + 0.000 000 002 968 590 706 586 882;
  • 3) 0.000 000 002 968 590 706 586 882 × 2 = 0 + 0.000 000 005 937 181 413 173 764;
  • 4) 0.000 000 005 937 181 413 173 764 × 2 = 0 + 0.000 000 011 874 362 826 347 528;
  • 5) 0.000 000 011 874 362 826 347 528 × 2 = 0 + 0.000 000 023 748 725 652 695 056;
  • 6) 0.000 000 023 748 725 652 695 056 × 2 = 0 + 0.000 000 047 497 451 305 390 112;
  • 7) 0.000 000 047 497 451 305 390 112 × 2 = 0 + 0.000 000 094 994 902 610 780 224;
  • 8) 0.000 000 094 994 902 610 780 224 × 2 = 0 + 0.000 000 189 989 805 221 560 448;
  • 9) 0.000 000 189 989 805 221 560 448 × 2 = 0 + 0.000 000 379 979 610 443 120 896;
  • 10) 0.000 000 379 979 610 443 120 896 × 2 = 0 + 0.000 000 759 959 220 886 241 792;
  • 11) 0.000 000 759 959 220 886 241 792 × 2 = 0 + 0.000 001 519 918 441 772 483 584;
  • 12) 0.000 001 519 918 441 772 483 584 × 2 = 0 + 0.000 003 039 836 883 544 967 168;
  • 13) 0.000 003 039 836 883 544 967 168 × 2 = 0 + 0.000 006 079 673 767 089 934 336;
  • 14) 0.000 006 079 673 767 089 934 336 × 2 = 0 + 0.000 012 159 347 534 179 868 672;
  • 15) 0.000 012 159 347 534 179 868 672 × 2 = 0 + 0.000 024 318 695 068 359 737 344;
  • 16) 0.000 024 318 695 068 359 737 344 × 2 = 0 + 0.000 048 637 390 136 719 474 688;
  • 17) 0.000 048 637 390 136 719 474 688 × 2 = 0 + 0.000 097 274 780 273 438 949 376;
  • 18) 0.000 097 274 780 273 438 949 376 × 2 = 0 + 0.000 194 549 560 546 877 898 752;
  • 19) 0.000 194 549 560 546 877 898 752 × 2 = 0 + 0.000 389 099 121 093 755 797 504;
  • 20) 0.000 389 099 121 093 755 797 504 × 2 = 0 + 0.000 778 198 242 187 511 595 008;
  • 21) 0.000 778 198 242 187 511 595 008 × 2 = 0 + 0.001 556 396 484 375 023 190 016;
  • 22) 0.001 556 396 484 375 023 190 016 × 2 = 0 + 0.003 112 792 968 750 046 380 032;
  • 23) 0.003 112 792 968 750 046 380 032 × 2 = 0 + 0.006 225 585 937 500 092 760 064;
  • 24) 0.006 225 585 937 500 092 760 064 × 2 = 0 + 0.012 451 171 875 000 185 520 128;
  • 25) 0.012 451 171 875 000 185 520 128 × 2 = 0 + 0.024 902 343 750 000 371 040 256;
  • 26) 0.024 902 343 750 000 371 040 256 × 2 = 0 + 0.049 804 687 500 000 742 080 512;
  • 27) 0.049 804 687 500 000 742 080 512 × 2 = 0 + 0.099 609 375 000 001 484 161 024;
  • 28) 0.099 609 375 000 001 484 161 024 × 2 = 0 + 0.199 218 750 000 002 968 322 048;
  • 29) 0.199 218 750 000 002 968 322 048 × 2 = 0 + 0.398 437 500 000 005 936 644 096;
  • 30) 0.398 437 500 000 005 936 644 096 × 2 = 0 + 0.796 875 000 000 011 873 288 192;
  • 31) 0.796 875 000 000 011 873 288 192 × 2 = 1 + 0.593 750 000 000 023 746 576 384;
  • 32) 0.593 750 000 000 023 746 576 384 × 2 = 1 + 0.187 500 000 000 047 493 152 768;
  • 33) 0.187 500 000 000 047 493 152 768 × 2 = 0 + 0.375 000 000 000 094 986 305 536;
  • 34) 0.375 000 000 000 094 986 305 536 × 2 = 0 + 0.750 000 000 000 189 972 611 072;
  • 35) 0.750 000 000 000 189 972 611 072 × 2 = 1 + 0.500 000 000 000 379 945 222 144;
  • 36) 0.500 000 000 000 379 945 222 144 × 2 = 1 + 0.000 000 000 000 759 890 444 288;
  • 37) 0.000 000 000 000 759 890 444 288 × 2 = 0 + 0.000 000 000 001 519 780 888 576;
  • 38) 0.000 000 000 001 519 780 888 576 × 2 = 0 + 0.000 000 000 003 039 561 777 152;
  • 39) 0.000 000 000 003 039 561 777 152 × 2 = 0 + 0.000 000 000 006 079 123 554 304;
  • 40) 0.000 000 000 006 079 123 554 304 × 2 = 0 + 0.000 000 000 012 158 247 108 608;
  • 41) 0.000 000 000 012 158 247 108 608 × 2 = 0 + 0.000 000 000 024 316 494 217 216;
  • 42) 0.000 000 000 024 316 494 217 216 × 2 = 0 + 0.000 000 000 048 632 988 434 432;
  • 43) 0.000 000 000 048 632 988 434 432 × 2 = 0 + 0.000 000 000 097 265 976 868 864;
  • 44) 0.000 000 000 097 265 976 868 864 × 2 = 0 + 0.000 000 000 194 531 953 737 728;
  • 45) 0.000 000 000 194 531 953 737 728 × 2 = 0 + 0.000 000 000 389 063 907 475 456;
  • 46) 0.000 000 000 389 063 907 475 456 × 2 = 0 + 0.000 000 000 778 127 814 950 912;
  • 47) 0.000 000 000 778 127 814 950 912 × 2 = 0 + 0.000 000 001 556 255 629 901 824;
  • 48) 0.000 000 001 556 255 629 901 824 × 2 = 0 + 0.000 000 003 112 511 259 803 648;
  • 49) 0.000 000 003 112 511 259 803 648 × 2 = 0 + 0.000 000 006 225 022 519 607 296;
  • 50) 0.000 000 006 225 022 519 607 296 × 2 = 0 + 0.000 000 012 450 045 039 214 592;
  • 51) 0.000 000 012 450 045 039 214 592 × 2 = 0 + 0.000 000 024 900 090 078 429 184;
  • 52) 0.000 000 024 900 090 078 429 184 × 2 = 0 + 0.000 000 049 800 180 156 858 368;
  • 53) 0.000 000 049 800 180 156 858 368 × 2 = 0 + 0.000 000 099 600 360 313 716 736;
  • 54) 0.000 000 099 600 360 313 716 736 × 2 = 0 + 0.000 000 199 200 720 627 433 472;

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:


0.000 000 000 742 147 676 646 720 5(10) =


0.0000 0000 0000 0000 0000 0000 0000 0011 0011 0000 0000 0000 0000 00(2)

6. Positive number before normalization:

0.000 000 000 742 147 676 646 720 5(10) =


0.0000 0000 0000 0000 0000 0000 0000 0011 0011 0000 0000 0000 0000 00(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 31 positions to the right, so that only one non zero digit remains to the left of it:


0.000 000 000 742 147 676 646 720 5(10) =


0.0000 0000 0000 0000 0000 0000 0000 0011 0011 0000 0000 0000 0000 00(2) =


0.0000 0000 0000 0000 0000 0000 0000 0011 0011 0000 0000 0000 0000 00(2) × 20 =


1.1001 1000 0000 0000 0000 000(2) × 2-31


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): -31


Mantissa (not normalized):
1.1001 1000 0000 0000 0000 000


9. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


-31 + 2(8-1) - 1 =


(-31 + 127)(10) =


96(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;
  • 96 ÷ 2 = 48 + 0;
  • 48 ÷ 2 = 24 + 0;
  • 24 ÷ 2 = 12 + 0;
  • 12 ÷ 2 = 6 + 0;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


96(10) =


0110 0000(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, only if necessary (not the case here).


Mantissa (normalized) =


1. 100 1100 0000 0000 0000 0000 =


100 1100 0000 0000 0000 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) =
0110 0000


Mantissa (23 bits) =
100 1100 0000 0000 0000 0000


Decimal number -0.000 000 000 742 147 676 646 720 5 converted to 32 bit single precision IEEE 754 binary floating point representation:

1 - 0110 0000 - 100 1100 0000 0000 0000 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