-0.105 000 000 006 8 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.105 000 000 006 8(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
-0.105 000 000 006 8(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:

|-0.105 000 000 006 8| = 0.105 000 000 006 8


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: 0.105 000 000 006 8.

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) 0.105 000 000 006 8 × 2 = 0 + 0.210 000 000 013 6;
  • 2) 0.210 000 000 013 6 × 2 = 0 + 0.420 000 000 027 2;
  • 3) 0.420 000 000 027 2 × 2 = 0 + 0.840 000 000 054 4;
  • 4) 0.840 000 000 054 4 × 2 = 1 + 0.680 000 000 108 8;
  • 5) 0.680 000 000 108 8 × 2 = 1 + 0.360 000 000 217 6;
  • 6) 0.360 000 000 217 6 × 2 = 0 + 0.720 000 000 435 2;
  • 7) 0.720 000 000 435 2 × 2 = 1 + 0.440 000 000 870 4;
  • 8) 0.440 000 000 870 4 × 2 = 0 + 0.880 000 001 740 8;
  • 9) 0.880 000 001 740 8 × 2 = 1 + 0.760 000 003 481 6;
  • 10) 0.760 000 003 481 6 × 2 = 1 + 0.520 000 006 963 2;
  • 11) 0.520 000 006 963 2 × 2 = 1 + 0.040 000 013 926 4;
  • 12) 0.040 000 013 926 4 × 2 = 0 + 0.080 000 027 852 8;
  • 13) 0.080 000 027 852 8 × 2 = 0 + 0.160 000 055 705 6;
  • 14) 0.160 000 055 705 6 × 2 = 0 + 0.320 000 111 411 2;
  • 15) 0.320 000 111 411 2 × 2 = 0 + 0.640 000 222 822 4;
  • 16) 0.640 000 222 822 4 × 2 = 1 + 0.280 000 445 644 8;
  • 17) 0.280 000 445 644 8 × 2 = 0 + 0.560 000 891 289 6;
  • 18) 0.560 000 891 289 6 × 2 = 1 + 0.120 001 782 579 2;
  • 19) 0.120 001 782 579 2 × 2 = 0 + 0.240 003 565 158 4;
  • 20) 0.240 003 565 158 4 × 2 = 0 + 0.480 007 130 316 8;
  • 21) 0.480 007 130 316 8 × 2 = 0 + 0.960 014 260 633 6;
  • 22) 0.960 014 260 633 6 × 2 = 1 + 0.920 028 521 267 2;
  • 23) 0.920 028 521 267 2 × 2 = 1 + 0.840 057 042 534 4;
  • 24) 0.840 057 042 534 4 × 2 = 1 + 0.680 114 085 068 8;
  • 25) 0.680 114 085 068 8 × 2 = 1 + 0.360 228 170 137 6;
  • 26) 0.360 228 170 137 6 × 2 = 0 + 0.720 456 340 275 2;
  • 27) 0.720 456 340 275 2 × 2 = 1 + 0.440 912 680 550 4;
  • 28) 0.440 912 680 550 4 × 2 = 0 + 0.881 825 361 100 8;
  • 29) 0.881 825 361 100 8 × 2 = 1 + 0.763 650 722 201 6;
  • 30) 0.763 650 722 201 6 × 2 = 1 + 0.527 301 444 403 2;
  • 31) 0.527 301 444 403 2 × 2 = 1 + 0.054 602 888 806 4;
  • 32) 0.054 602 888 806 4 × 2 = 0 + 0.109 205 777 612 8;
  • 33) 0.109 205 777 612 8 × 2 = 0 + 0.218 411 555 225 6;
  • 34) 0.218 411 555 225 6 × 2 = 0 + 0.436 823 110 451 2;
  • 35) 0.436 823 110 451 2 × 2 = 0 + 0.873 646 220 902 4;
  • 36) 0.873 646 220 902 4 × 2 = 1 + 0.747 292 441 804 8;
  • 37) 0.747 292 441 804 8 × 2 = 1 + 0.494 584 883 609 6;
  • 38) 0.494 584 883 609 6 × 2 = 0 + 0.989 169 767 219 2;
  • 39) 0.989 169 767 219 2 × 2 = 1 + 0.978 339 534 438 4;
  • 40) 0.978 339 534 438 4 × 2 = 1 + 0.956 679 068 876 8;
  • 41) 0.956 679 068 876 8 × 2 = 1 + 0.913 358 137 753 6;
  • 42) 0.913 358 137 753 6 × 2 = 1 + 0.826 716 275 507 2;
  • 43) 0.826 716 275 507 2 × 2 = 1 + 0.653 432 551 014 4;
  • 44) 0.653 432 551 014 4 × 2 = 1 + 0.306 865 102 028 8;
  • 45) 0.306 865 102 028 8 × 2 = 0 + 0.613 730 204 057 6;
  • 46) 0.613 730 204 057 6 × 2 = 1 + 0.227 460 408 115 2;
  • 47) 0.227 460 408 115 2 × 2 = 0 + 0.454 920 816 230 4;
  • 48) 0.454 920 816 230 4 × 2 = 0 + 0.909 841 632 460 8;
  • 49) 0.909 841 632 460 8 × 2 = 1 + 0.819 683 264 921 6;
  • 50) 0.819 683 264 921 6 × 2 = 1 + 0.639 366 529 843 2;
  • 51) 0.639 366 529 843 2 × 2 = 1 + 0.278 733 059 686 4;
  • 52) 0.278 733 059 686 4 × 2 = 0 + 0.557 466 119 372 8;
  • 53) 0.557 466 119 372 8 × 2 = 1 + 0.114 932 238 745 6;
  • 54) 0.114 932 238 745 6 × 2 = 0 + 0.229 864 477 491 2;
  • 55) 0.229 864 477 491 2 × 2 = 0 + 0.459 728 954 982 4;
  • 56) 0.459 728 954 982 4 × 2 = 0 + 0.919 457 909 964 8;

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:


0.105 000 000 006 8(10) =


0.0001 1010 1110 0001 0100 0111 1010 1110 0001 1011 1111 0100 1110 1000(2)

6. Positive number before normalization:

0.105 000 000 006 8(10) =


0.0001 1010 1110 0001 0100 0111 1010 1110 0001 1011 1111 0100 1110 1000(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 4 positions to the right, so that only one non zero digit remains to the left of it:


0.105 000 000 006 8(10) =


0.0001 1010 1110 0001 0100 0111 1010 1110 0001 1011 1111 0100 1110 1000(2) =


0.0001 1010 1110 0001 0100 0111 1010 1110 0001 1011 1111 0100 1110 1000(2) × 20 =


1.1010 1110 0001 0100 0111 1010 1110 0001 1011 1111 0100 1110 1000(2) × 2-4


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):
1.1010 1110 0001 0100 0111 1010 1110 0001 1011 1111 0100 1110 1000


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-4 + 2(11-1) - 1 =


(-4 + 1 023)(10) =


1 019(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;
  • 1 019 ÷ 2 = 509 + 1;
  • 509 ÷ 2 = 254 + 1;
  • 254 ÷ 2 = 127 + 0;
  • 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) =


1019(10) =


011 1111 1011(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. 1010 1110 0001 0100 0111 1010 1110 0001 1011 1111 0100 1110 1000 =


1010 1110 0001 0100 0111 1010 1110 0001 1011 1111 0100 1110 1000


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 1011


Mantissa (52 bits) =
1010 1110 0001 0100 0111 1010 1110 0001 1011 1111 0100 1110 1000


Decimal number -0.105 000 000 006 8 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1011 - 1010 1110 0001 0100 0111 1010 1110 0001 1011 1111 0100 1110 1000


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