-0.140 000 000 000 54 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.140 000 000 000 54(10) to 64 bit double precision IEEE 754 binary floating point representation standard (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

What are the steps to convert decimal number
-0.140 000 000 000 54(10) to 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. Start with the positive version of the number:

|-0.140 000 000 000 54| = 0.140 000 000 000 54


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: 0.140 000 000 000 54.

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) 0.140 000 000 000 54 × 2 = 0 + 0.280 000 000 001 08;
  • 2) 0.280 000 000 001 08 × 2 = 0 + 0.560 000 000 002 16;
  • 3) 0.560 000 000 002 16 × 2 = 1 + 0.120 000 000 004 32;
  • 4) 0.120 000 000 004 32 × 2 = 0 + 0.240 000 000 008 64;
  • 5) 0.240 000 000 008 64 × 2 = 0 + 0.480 000 000 017 28;
  • 6) 0.480 000 000 017 28 × 2 = 0 + 0.960 000 000 034 56;
  • 7) 0.960 000 000 034 56 × 2 = 1 + 0.920 000 000 069 12;
  • 8) 0.920 000 000 069 12 × 2 = 1 + 0.840 000 000 138 24;
  • 9) 0.840 000 000 138 24 × 2 = 1 + 0.680 000 000 276 48;
  • 10) 0.680 000 000 276 48 × 2 = 1 + 0.360 000 000 552 96;
  • 11) 0.360 000 000 552 96 × 2 = 0 + 0.720 000 001 105 92;
  • 12) 0.720 000 001 105 92 × 2 = 1 + 0.440 000 002 211 84;
  • 13) 0.440 000 002 211 84 × 2 = 0 + 0.880 000 004 423 68;
  • 14) 0.880 000 004 423 68 × 2 = 1 + 0.760 000 008 847 36;
  • 15) 0.760 000 008 847 36 × 2 = 1 + 0.520 000 017 694 72;
  • 16) 0.520 000 017 694 72 × 2 = 1 + 0.040 000 035 389 44;
  • 17) 0.040 000 035 389 44 × 2 = 0 + 0.080 000 070 778 88;
  • 18) 0.080 000 070 778 88 × 2 = 0 + 0.160 000 141 557 76;
  • 19) 0.160 000 141 557 76 × 2 = 0 + 0.320 000 283 115 52;
  • 20) 0.320 000 283 115 52 × 2 = 0 + 0.640 000 566 231 04;
  • 21) 0.640 000 566 231 04 × 2 = 1 + 0.280 001 132 462 08;
  • 22) 0.280 001 132 462 08 × 2 = 0 + 0.560 002 264 924 16;
  • 23) 0.560 002 264 924 16 × 2 = 1 + 0.120 004 529 848 32;
  • 24) 0.120 004 529 848 32 × 2 = 0 + 0.240 009 059 696 64;
  • 25) 0.240 009 059 696 64 × 2 = 0 + 0.480 018 119 393 28;
  • 26) 0.480 018 119 393 28 × 2 = 0 + 0.960 036 238 786 56;
  • 27) 0.960 036 238 786 56 × 2 = 1 + 0.920 072 477 573 12;
  • 28) 0.920 072 477 573 12 × 2 = 1 + 0.840 144 955 146 24;
  • 29) 0.840 144 955 146 24 × 2 = 1 + 0.680 289 910 292 48;
  • 30) 0.680 289 910 292 48 × 2 = 1 + 0.360 579 820 584 96;
  • 31) 0.360 579 820 584 96 × 2 = 0 + 0.721 159 641 169 92;
  • 32) 0.721 159 641 169 92 × 2 = 1 + 0.442 319 282 339 84;
  • 33) 0.442 319 282 339 84 × 2 = 0 + 0.884 638 564 679 68;
  • 34) 0.884 638 564 679 68 × 2 = 1 + 0.769 277 129 359 36;
  • 35) 0.769 277 129 359 36 × 2 = 1 + 0.538 554 258 718 72;
  • 36) 0.538 554 258 718 72 × 2 = 1 + 0.077 108 517 437 44;
  • 37) 0.077 108 517 437 44 × 2 = 0 + 0.154 217 034 874 88;
  • 38) 0.154 217 034 874 88 × 2 = 0 + 0.308 434 069 749 76;
  • 39) 0.308 434 069 749 76 × 2 = 0 + 0.616 868 139 499 52;
  • 40) 0.616 868 139 499 52 × 2 = 1 + 0.233 736 278 999 04;
  • 41) 0.233 736 278 999 04 × 2 = 0 + 0.467 472 557 998 08;
  • 42) 0.467 472 557 998 08 × 2 = 0 + 0.934 945 115 996 16;
  • 43) 0.934 945 115 996 16 × 2 = 1 + 0.869 890 231 992 32;
  • 44) 0.869 890 231 992 32 × 2 = 1 + 0.739 780 463 984 64;
  • 45) 0.739 780 463 984 64 × 2 = 1 + 0.479 560 927 969 28;
  • 46) 0.479 560 927 969 28 × 2 = 0 + 0.959 121 855 938 56;
  • 47) 0.959 121 855 938 56 × 2 = 1 + 0.918 243 711 877 12;
  • 48) 0.918 243 711 877 12 × 2 = 1 + 0.836 487 423 754 24;
  • 49) 0.836 487 423 754 24 × 2 = 1 + 0.672 974 847 508 48;
  • 50) 0.672 974 847 508 48 × 2 = 1 + 0.345 949 695 016 96;
  • 51) 0.345 949 695 016 96 × 2 = 0 + 0.691 899 390 033 92;
  • 52) 0.691 899 390 033 92 × 2 = 1 + 0.383 798 780 067 84;
  • 53) 0.383 798 780 067 84 × 2 = 0 + 0.767 597 560 135 68;
  • 54) 0.767 597 560 135 68 × 2 = 1 + 0.535 195 120 271 36;
  • 55) 0.535 195 120 271 36 × 2 = 1 + 0.070 390 240 542 72;

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:


0.140 000 000 000 54(10) =


0.0010 0011 1101 0111 0000 1010 0011 1101 0111 0001 0011 1011 1101 011(2)

6. Positive number before normalization:

0.140 000 000 000 54(10) =


0.0010 0011 1101 0111 0000 1010 0011 1101 0111 0001 0011 1011 1101 011(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 3 positions to the right, so that only one non zero digit remains to the left of it:


0.140 000 000 000 54(10) =


0.0010 0011 1101 0111 0000 1010 0011 1101 0111 0001 0011 1011 1101 011(2) =


0.0010 0011 1101 0111 0000 1010 0011 1101 0111 0001 0011 1011 1101 011(2) × 20 =


1.0001 1110 1011 1000 0101 0001 1110 1011 1000 1001 1101 1110 1011(2) × 2-3


8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

Sign 1 (a negative number)


Exponent (unadjusted): -3


Mantissa (not normalized):
1.0001 1110 1011 1000 0101 0001 1110 1011 1000 1001 1101 1110 1011


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


-3 + 2(11-1) - 1 =


(-3 + 1 023)(10) =


1 020(10)


10. Convert the adjusted exponent from the decimal (base 10) to 11 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 1 020 ÷ 2 = 510 + 0;
  • 510 ÷ 2 = 255 + 0;
  • 255 ÷ 2 = 127 + 1;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 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) =


1020(10) =


011 1111 1100(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 52 bits, only if necessary (not the case here).


Mantissa (normalized) =


1. 0001 1110 1011 1000 0101 0001 1110 1011 1000 1001 1101 1110 1011 =


0001 1110 1011 1000 0101 0001 1110 1011 1000 1001 1101 1110 1011


13. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

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


Exponent (11 bits) =
011 1111 1100


Mantissa (52 bits) =
0001 1110 1011 1000 0101 0001 1110 1011 1000 1001 1101 1110 1011


Decimal number -0.140 000 000 000 54 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1100 - 0001 1110 1011 1000 0101 0001 1110 1011 1000 1001 1101 1110 1011


How to convert numbers from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 64 bit double 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 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 from the previous 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 multiplying operations, starting from the top of the list constructed 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, shifting the decimal mark (the decimal point) "n" positions either to the left, or to the right, so that only one non zero digit remains to the left of the decimal mark.
  • 7. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal mark, if the case) and adjust its length to 52 bits, either by removing the excess bits from the right (losing precision...) or by adding extra bits set on '0' 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 -31.640 215 from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point:

  • 1. Start with the positive version of the number:

    |-31.640 215| = 31.640 215

  • 2. First convert the integer part, 31. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 31 ÷ 2 = 15 + 1;
    • 15 ÷ 2 = 7 + 1;
    • 7 ÷ 2 = 3 + 1;
    • 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:

    31(10) = 1 1111(2)

  • 4. Then, convert the fractional part, 0.640 215. 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) 0.640 215 × 2 = 1 + 0.280 43;
    • 2) 0.280 43 × 2 = 0 + 0.560 86;
    • 3) 0.560 86 × 2 = 1 + 0.121 72;
    • 4) 0.121 72 × 2 = 0 + 0.243 44;
    • 5) 0.243 44 × 2 = 0 + 0.486 88;
    • 6) 0.486 88 × 2 = 0 + 0.973 76;
    • 7) 0.973 76 × 2 = 1 + 0.947 52;
    • 8) 0.947 52 × 2 = 1 + 0.895 04;
    • 9) 0.895 04 × 2 = 1 + 0.790 08;
    • 10) 0.790 08 × 2 = 1 + 0.580 16;
    • 11) 0.580 16 × 2 = 1 + 0.160 32;
    • 12) 0.160 32 × 2 = 0 + 0.320 64;
    • 13) 0.320 64 × 2 = 0 + 0.641 28;
    • 14) 0.641 28 × 2 = 1 + 0.282 56;
    • 15) 0.282 56 × 2 = 0 + 0.565 12;
    • 16) 0.565 12 × 2 = 1 + 0.130 24;
    • 17) 0.130 24 × 2 = 0 + 0.260 48;
    • 18) 0.260 48 × 2 = 0 + 0.520 96;
    • 19) 0.520 96 × 2 = 1 + 0.041 92;
    • 20) 0.041 92 × 2 = 0 + 0.083 84;
    • 21) 0.083 84 × 2 = 0 + 0.167 68;
    • 22) 0.167 68 × 2 = 0 + 0.335 36;
    • 23) 0.335 36 × 2 = 0 + 0.670 72;
    • 24) 0.670 72 × 2 = 1 + 0.341 44;
    • 25) 0.341 44 × 2 = 0 + 0.682 88;
    • 26) 0.682 88 × 2 = 1 + 0.365 76;
    • 27) 0.365 76 × 2 = 0 + 0.731 52;
    • 28) 0.731 52 × 2 = 1 + 0.463 04;
    • 29) 0.463 04 × 2 = 0 + 0.926 08;
    • 30) 0.926 08 × 2 = 1 + 0.852 16;
    • 31) 0.852 16 × 2 = 1 + 0.704 32;
    • 32) 0.704 32 × 2 = 1 + 0.408 64;
    • 33) 0.408 64 × 2 = 0 + 0.817 28;
    • 34) 0.817 28 × 2 = 1 + 0.634 56;
    • 35) 0.634 56 × 2 = 1 + 0.269 12;
    • 36) 0.269 12 × 2 = 0 + 0.538 24;
    • 37) 0.538 24 × 2 = 1 + 0.076 48;
    • 38) 0.076 48 × 2 = 0 + 0.152 96;
    • 39) 0.152 96 × 2 = 0 + 0.305 92;
    • 40) 0.305 92 × 2 = 0 + 0.611 84;
    • 41) 0.611 84 × 2 = 1 + 0.223 68;
    • 42) 0.223 68 × 2 = 0 + 0.447 36;
    • 43) 0.447 36 × 2 = 0 + 0.894 72;
    • 44) 0.894 72 × 2 = 1 + 0.789 44;
    • 45) 0.789 44 × 2 = 1 + 0.578 88;
    • 46) 0.578 88 × 2 = 1 + 0.157 76;
    • 47) 0.157 76 × 2 = 0 + 0.315 52;
    • 48) 0.315 52 × 2 = 0 + 0.631 04;
    • 49) 0.631 04 × 2 = 1 + 0.262 08;
    • 50) 0.262 08 × 2 = 0 + 0.524 16;
    • 51) 0.524 16 × 2 = 1 + 0.048 32;
    • 52) 0.048 32 × 2 = 0 + 0.096 64;
    • 53) 0.096 64 × 2 = 0 + 0.193 28;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 52) 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:

    0.640 215(10) = 0.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 6. Summarizing - the positive number before normalization:

    31.640 215(10) = 1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 7. Normalize the binary representation of the number, shifting the decimal mark 4 positions to the left so that only one non-zero digit stays to the left of the decimal mark:

    31.640 215(10) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 20 =
    1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

  • 9. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as shown above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1 = (4 + 1023)(10) = 1027(10) =
    100 0000 0011(2)

  • 10. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign) and adjust its length to 52 bits, by removing the excess bits, from the right (losing precision...):

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

    Mantissa (normalized): 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Conclusion:

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

    Exponent (8 bits) = 100 0000 0011

    Mantissa (52 bits) = 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Number -31.640 215, converted from decimal system (base 10) to 64 bit double precision IEEE 754 binary floating point =
    1 - 100 0000 0011 - 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100