-0.000 348 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 348(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
-0.000 348(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:

|-0.000 348| = 0.000 348


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: 0.000 348.

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) 0.000 348 × 2 = 0 + 0.000 696;
  • 2) 0.000 696 × 2 = 0 + 0.001 392;
  • 3) 0.001 392 × 2 = 0 + 0.002 784;
  • 4) 0.002 784 × 2 = 0 + 0.005 568;
  • 5) 0.005 568 × 2 = 0 + 0.011 136;
  • 6) 0.011 136 × 2 = 0 + 0.022 272;
  • 7) 0.022 272 × 2 = 0 + 0.044 544;
  • 8) 0.044 544 × 2 = 0 + 0.089 088;
  • 9) 0.089 088 × 2 = 0 + 0.178 176;
  • 10) 0.178 176 × 2 = 0 + 0.356 352;
  • 11) 0.356 352 × 2 = 0 + 0.712 704;
  • 12) 0.712 704 × 2 = 1 + 0.425 408;
  • 13) 0.425 408 × 2 = 0 + 0.850 816;
  • 14) 0.850 816 × 2 = 1 + 0.701 632;
  • 15) 0.701 632 × 2 = 1 + 0.403 264;
  • 16) 0.403 264 × 2 = 0 + 0.806 528;
  • 17) 0.806 528 × 2 = 1 + 0.613 056;
  • 18) 0.613 056 × 2 = 1 + 0.226 112;
  • 19) 0.226 112 × 2 = 0 + 0.452 224;
  • 20) 0.452 224 × 2 = 0 + 0.904 448;
  • 21) 0.904 448 × 2 = 1 + 0.808 896;
  • 22) 0.808 896 × 2 = 1 + 0.617 792;
  • 23) 0.617 792 × 2 = 1 + 0.235 584;
  • 24) 0.235 584 × 2 = 0 + 0.471 168;
  • 25) 0.471 168 × 2 = 0 + 0.942 336;
  • 26) 0.942 336 × 2 = 1 + 0.884 672;
  • 27) 0.884 672 × 2 = 1 + 0.769 344;
  • 28) 0.769 344 × 2 = 1 + 0.538 688;
  • 29) 0.538 688 × 2 = 1 + 0.077 376;
  • 30) 0.077 376 × 2 = 0 + 0.154 752;
  • 31) 0.154 752 × 2 = 0 + 0.309 504;
  • 32) 0.309 504 × 2 = 0 + 0.619 008;
  • 33) 0.619 008 × 2 = 1 + 0.238 016;
  • 34) 0.238 016 × 2 = 0 + 0.476 032;
  • 35) 0.476 032 × 2 = 0 + 0.952 064;
  • 36) 0.952 064 × 2 = 1 + 0.904 128;
  • 37) 0.904 128 × 2 = 1 + 0.808 256;
  • 38) 0.808 256 × 2 = 1 + 0.616 512;
  • 39) 0.616 512 × 2 = 1 + 0.233 024;
  • 40) 0.233 024 × 2 = 0 + 0.466 048;
  • 41) 0.466 048 × 2 = 0 + 0.932 096;
  • 42) 0.932 096 × 2 = 1 + 0.864 192;
  • 43) 0.864 192 × 2 = 1 + 0.728 384;
  • 44) 0.728 384 × 2 = 1 + 0.456 768;
  • 45) 0.456 768 × 2 = 0 + 0.913 536;
  • 46) 0.913 536 × 2 = 1 + 0.827 072;
  • 47) 0.827 072 × 2 = 1 + 0.654 144;
  • 48) 0.654 144 × 2 = 1 + 0.308 288;
  • 49) 0.308 288 × 2 = 0 + 0.616 576;
  • 50) 0.616 576 × 2 = 1 + 0.233 152;
  • 51) 0.233 152 × 2 = 0 + 0.466 304;
  • 52) 0.466 304 × 2 = 0 + 0.932 608;
  • 53) 0.932 608 × 2 = 1 + 0.865 216;
  • 54) 0.865 216 × 2 = 1 + 0.730 432;
  • 55) 0.730 432 × 2 = 1 + 0.460 864;
  • 56) 0.460 864 × 2 = 0 + 0.921 728;
  • 57) 0.921 728 × 2 = 1 + 0.843 456;
  • 58) 0.843 456 × 2 = 1 + 0.686 912;
  • 59) 0.686 912 × 2 = 1 + 0.373 824;
  • 60) 0.373 824 × 2 = 0 + 0.747 648;
  • 61) 0.747 648 × 2 = 1 + 0.495 296;
  • 62) 0.495 296 × 2 = 0 + 0.990 592;
  • 63) 0.990 592 × 2 = 1 + 0.981 184;
  • 64) 0.981 184 × 2 = 1 + 0.962 368;

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:


0.000 348(10) =


0.0000 0000 0001 0110 1100 1110 0111 1000 1001 1110 0111 0111 0100 1110 1110 1011(2)

6. Positive number before normalization:

0.000 348(10) =


0.0000 0000 0001 0110 1100 1110 0111 1000 1001 1110 0111 0111 0100 1110 1110 1011(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:


0.000 348(10) =


0.0000 0000 0001 0110 1100 1110 0111 1000 1001 1110 0111 0111 0100 1110 1110 1011(2) =


0.0000 0000 0001 0110 1100 1110 0111 1000 1001 1110 0111 0111 0100 1110 1110 1011(2) × 20 =


1.0110 1100 1110 0111 1000 1001 1110 0111 0111 0100 1110 1110 1011(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):
1.0110 1100 1110 0111 1000 1001 1110 0111 0111 0100 1110 1110 1011


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. 0110 1100 1110 0111 1000 1001 1110 0111 0111 0100 1110 1110 1011 =


0110 1100 1110 0111 1000 1001 1110 0111 0111 0100 1110 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 0011


Mantissa (52 bits) =
0110 1100 1110 0111 1000 1001 1110 0111 0111 0100 1110 1110 1011


Decimal number -0.000 348 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0110 1100 1110 0111 1000 1001 1110 0111 0111 0100 1110 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