-0.000 279 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 279(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
-0.000 279(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:

|-0.000 279| = 0.000 279


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: 0.000 279.

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) 0.000 279 × 2 = 0 + 0.000 558;
  • 2) 0.000 558 × 2 = 0 + 0.001 116;
  • 3) 0.001 116 × 2 = 0 + 0.002 232;
  • 4) 0.002 232 × 2 = 0 + 0.004 464;
  • 5) 0.004 464 × 2 = 0 + 0.008 928;
  • 6) 0.008 928 × 2 = 0 + 0.017 856;
  • 7) 0.017 856 × 2 = 0 + 0.035 712;
  • 8) 0.035 712 × 2 = 0 + 0.071 424;
  • 9) 0.071 424 × 2 = 0 + 0.142 848;
  • 10) 0.142 848 × 2 = 0 + 0.285 696;
  • 11) 0.285 696 × 2 = 0 + 0.571 392;
  • 12) 0.571 392 × 2 = 1 + 0.142 784;
  • 13) 0.142 784 × 2 = 0 + 0.285 568;
  • 14) 0.285 568 × 2 = 0 + 0.571 136;
  • 15) 0.571 136 × 2 = 1 + 0.142 272;
  • 16) 0.142 272 × 2 = 0 + 0.284 544;
  • 17) 0.284 544 × 2 = 0 + 0.569 088;
  • 18) 0.569 088 × 2 = 1 + 0.138 176;
  • 19) 0.138 176 × 2 = 0 + 0.276 352;
  • 20) 0.276 352 × 2 = 0 + 0.552 704;
  • 21) 0.552 704 × 2 = 1 + 0.105 408;
  • 22) 0.105 408 × 2 = 0 + 0.210 816;
  • 23) 0.210 816 × 2 = 0 + 0.421 632;
  • 24) 0.421 632 × 2 = 0 + 0.843 264;
  • 25) 0.843 264 × 2 = 1 + 0.686 528;
  • 26) 0.686 528 × 2 = 1 + 0.373 056;
  • 27) 0.373 056 × 2 = 0 + 0.746 112;
  • 28) 0.746 112 × 2 = 1 + 0.492 224;
  • 29) 0.492 224 × 2 = 0 + 0.984 448;
  • 30) 0.984 448 × 2 = 1 + 0.968 896;
  • 31) 0.968 896 × 2 = 1 + 0.937 792;
  • 32) 0.937 792 × 2 = 1 + 0.875 584;
  • 33) 0.875 584 × 2 = 1 + 0.751 168;
  • 34) 0.751 168 × 2 = 1 + 0.502 336;
  • 35) 0.502 336 × 2 = 1 + 0.004 672;
  • 36) 0.004 672 × 2 = 0 + 0.009 344;
  • 37) 0.009 344 × 2 = 0 + 0.018 688;
  • 38) 0.018 688 × 2 = 0 + 0.037 376;
  • 39) 0.037 376 × 2 = 0 + 0.074 752;
  • 40) 0.074 752 × 2 = 0 + 0.149 504;
  • 41) 0.149 504 × 2 = 0 + 0.299 008;
  • 42) 0.299 008 × 2 = 0 + 0.598 016;
  • 43) 0.598 016 × 2 = 1 + 0.196 032;
  • 44) 0.196 032 × 2 = 0 + 0.392 064;
  • 45) 0.392 064 × 2 = 0 + 0.784 128;
  • 46) 0.784 128 × 2 = 1 + 0.568 256;
  • 47) 0.568 256 × 2 = 1 + 0.136 512;
  • 48) 0.136 512 × 2 = 0 + 0.273 024;
  • 49) 0.273 024 × 2 = 0 + 0.546 048;
  • 50) 0.546 048 × 2 = 1 + 0.092 096;
  • 51) 0.092 096 × 2 = 0 + 0.184 192;
  • 52) 0.184 192 × 2 = 0 + 0.368 384;
  • 53) 0.368 384 × 2 = 0 + 0.736 768;
  • 54) 0.736 768 × 2 = 1 + 0.473 536;
  • 55) 0.473 536 × 2 = 0 + 0.947 072;
  • 56) 0.947 072 × 2 = 1 + 0.894 144;
  • 57) 0.894 144 × 2 = 1 + 0.788 288;
  • 58) 0.788 288 × 2 = 1 + 0.576 576;
  • 59) 0.576 576 × 2 = 1 + 0.153 152;
  • 60) 0.153 152 × 2 = 0 + 0.306 304;
  • 61) 0.306 304 × 2 = 0 + 0.612 608;
  • 62) 0.612 608 × 2 = 1 + 0.225 216;
  • 63) 0.225 216 × 2 = 0 + 0.450 432;
  • 64) 0.450 432 × 2 = 0 + 0.900 864;

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:


0.000 279(10) =


0.0000 0000 0001 0010 0100 1000 1101 0111 1110 0000 0010 0110 0100 0101 1110 0100(2)

6. Positive number before normalization:

0.000 279(10) =


0.0000 0000 0001 0010 0100 1000 1101 0111 1110 0000 0010 0110 0100 0101 1110 0100(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 12 positions to the right, so that only one non zero digit remains to the left of it:


0.000 279(10) =


0.0000 0000 0001 0010 0100 1000 1101 0111 1110 0000 0010 0110 0100 0101 1110 0100(2) =


0.0000 0000 0001 0010 0100 1000 1101 0111 1110 0000 0010 0110 0100 0101 1110 0100(2) × 20 =


1.0010 0100 1000 1101 0111 1110 0000 0010 0110 0100 0101 1110 0100(2) × 2-12


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): -12


Mantissa (not normalized):
1.0010 0100 1000 1101 0111 1110 0000 0010 0110 0100 0101 1110 0100


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-12 + 2(11-1) - 1 =


(-12 + 1 023)(10) =


1 011(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;
  • 1 011 ÷ 2 = 505 + 1;
  • 505 ÷ 2 = 252 + 1;
  • 252 ÷ 2 = 126 + 0;
  • 126 ÷ 2 = 63 + 0;
  • 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) =


1011(10) =


011 1111 0011(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. 0010 0100 1000 1101 0111 1110 0000 0010 0110 0100 0101 1110 0100 =


0010 0100 1000 1101 0111 1110 0000 0010 0110 0100 0101 1110 0100


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 0011


Mantissa (52 bits) =
0010 0100 1000 1101 0111 1110 0000 0010 0110 0100 0101 1110 0100


Decimal number -0.000 279 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0100 1000 1101 0111 1110 0000 0010 0110 0100 0101 1110 0100


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