-0.000 282 005 868 4 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 868 4(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
-0.000 282 005 868 4(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:

|-0.000 282 005 868 4| = 0.000 282 005 868 4


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: 0.000 282 005 868 4.

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) 0.000 282 005 868 4 × 2 = 0 + 0.000 564 011 736 8;
  • 2) 0.000 564 011 736 8 × 2 = 0 + 0.001 128 023 473 6;
  • 3) 0.001 128 023 473 6 × 2 = 0 + 0.002 256 046 947 2;
  • 4) 0.002 256 046 947 2 × 2 = 0 + 0.004 512 093 894 4;
  • 5) 0.004 512 093 894 4 × 2 = 0 + 0.009 024 187 788 8;
  • 6) 0.009 024 187 788 8 × 2 = 0 + 0.018 048 375 577 6;
  • 7) 0.018 048 375 577 6 × 2 = 0 + 0.036 096 751 155 2;
  • 8) 0.036 096 751 155 2 × 2 = 0 + 0.072 193 502 310 4;
  • 9) 0.072 193 502 310 4 × 2 = 0 + 0.144 387 004 620 8;
  • 10) 0.144 387 004 620 8 × 2 = 0 + 0.288 774 009 241 6;
  • 11) 0.288 774 009 241 6 × 2 = 0 + 0.577 548 018 483 2;
  • 12) 0.577 548 018 483 2 × 2 = 1 + 0.155 096 036 966 4;
  • 13) 0.155 096 036 966 4 × 2 = 0 + 0.310 192 073 932 8;
  • 14) 0.310 192 073 932 8 × 2 = 0 + 0.620 384 147 865 6;
  • 15) 0.620 384 147 865 6 × 2 = 1 + 0.240 768 295 731 2;
  • 16) 0.240 768 295 731 2 × 2 = 0 + 0.481 536 591 462 4;
  • 17) 0.481 536 591 462 4 × 2 = 0 + 0.963 073 182 924 8;
  • 18) 0.963 073 182 924 8 × 2 = 1 + 0.926 146 365 849 6;
  • 19) 0.926 146 365 849 6 × 2 = 1 + 0.852 292 731 699 2;
  • 20) 0.852 292 731 699 2 × 2 = 1 + 0.704 585 463 398 4;
  • 21) 0.704 585 463 398 4 × 2 = 1 + 0.409 170 926 796 8;
  • 22) 0.409 170 926 796 8 × 2 = 0 + 0.818 341 853 593 6;
  • 23) 0.818 341 853 593 6 × 2 = 1 + 0.636 683 707 187 2;
  • 24) 0.636 683 707 187 2 × 2 = 1 + 0.273 367 414 374 4;
  • 25) 0.273 367 414 374 4 × 2 = 0 + 0.546 734 828 748 8;
  • 26) 0.546 734 828 748 8 × 2 = 1 + 0.093 469 657 497 6;
  • 27) 0.093 469 657 497 6 × 2 = 0 + 0.186 939 314 995 2;
  • 28) 0.186 939 314 995 2 × 2 = 0 + 0.373 878 629 990 4;
  • 29) 0.373 878 629 990 4 × 2 = 0 + 0.747 757 259 980 8;
  • 30) 0.747 757 259 980 8 × 2 = 1 + 0.495 514 519 961 6;
  • 31) 0.495 514 519 961 6 × 2 = 0 + 0.991 029 039 923 2;
  • 32) 0.991 029 039 923 2 × 2 = 1 + 0.982 058 079 846 4;
  • 33) 0.982 058 079 846 4 × 2 = 1 + 0.964 116 159 692 8;
  • 34) 0.964 116 159 692 8 × 2 = 1 + 0.928 232 319 385 6;
  • 35) 0.928 232 319 385 6 × 2 = 1 + 0.856 464 638 771 2;
  • 36) 0.856 464 638 771 2 × 2 = 1 + 0.712 929 277 542 4;
  • 37) 0.712 929 277 542 4 × 2 = 1 + 0.425 858 555 084 8;
  • 38) 0.425 858 555 084 8 × 2 = 0 + 0.851 717 110 169 6;
  • 39) 0.851 717 110 169 6 × 2 = 1 + 0.703 434 220 339 2;
  • 40) 0.703 434 220 339 2 × 2 = 1 + 0.406 868 440 678 4;
  • 41) 0.406 868 440 678 4 × 2 = 0 + 0.813 736 881 356 8;
  • 42) 0.813 736 881 356 8 × 2 = 1 + 0.627 473 762 713 6;
  • 43) 0.627 473 762 713 6 × 2 = 1 + 0.254 947 525 427 2;
  • 44) 0.254 947 525 427 2 × 2 = 0 + 0.509 895 050 854 4;
  • 45) 0.509 895 050 854 4 × 2 = 1 + 0.019 790 101 708 8;
  • 46) 0.019 790 101 708 8 × 2 = 0 + 0.039 580 203 417 6;
  • 47) 0.039 580 203 417 6 × 2 = 0 + 0.079 160 406 835 2;
  • 48) 0.079 160 406 835 2 × 2 = 0 + 0.158 320 813 670 4;
  • 49) 0.158 320 813 670 4 × 2 = 0 + 0.316 641 627 340 8;
  • 50) 0.316 641 627 340 8 × 2 = 0 + 0.633 283 254 681 6;
  • 51) 0.633 283 254 681 6 × 2 = 1 + 0.266 566 509 363 2;
  • 52) 0.266 566 509 363 2 × 2 = 0 + 0.533 133 018 726 4;
  • 53) 0.533 133 018 726 4 × 2 = 1 + 0.066 266 037 452 8;
  • 54) 0.066 266 037 452 8 × 2 = 0 + 0.132 532 074 905 6;
  • 55) 0.132 532 074 905 6 × 2 = 0 + 0.265 064 149 811 2;
  • 56) 0.265 064 149 811 2 × 2 = 0 + 0.530 128 299 622 4;
  • 57) 0.530 128 299 622 4 × 2 = 1 + 0.060 256 599 244 8;
  • 58) 0.060 256 599 244 8 × 2 = 0 + 0.120 513 198 489 6;
  • 59) 0.120 513 198 489 6 × 2 = 0 + 0.241 026 396 979 2;
  • 60) 0.241 026 396 979 2 × 2 = 0 + 0.482 052 793 958 4;
  • 61) 0.482 052 793 958 4 × 2 = 0 + 0.964 105 587 916 8;
  • 62) 0.964 105 587 916 8 × 2 = 1 + 0.928 211 175 833 6;
  • 63) 0.928 211 175 833 6 × 2 = 1 + 0.856 422 351 667 2;
  • 64) 0.856 422 351 667 2 × 2 = 1 + 0.712 844 703 334 4;

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:


0.000 282 005 868 4(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1111 1011 0110 1000 0010 1000 1000 0111(2)

6. Positive number before normalization:

0.000 282 005 868 4(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1111 1011 0110 1000 0010 1000 1000 0111(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:


0.000 282 005 868 4(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1111 1011 0110 1000 0010 1000 1000 0111(2) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1111 1011 0110 1000 0010 1000 1000 0111(2) × 20 =


1.0010 0111 1011 0100 0101 1111 1011 0110 1000 0010 1000 1000 0111(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 0111 1011 0100 0101 1111 1011 0110 1000 0010 1000 1000 0111


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 0111 1011 0100 0101 1111 1011 0110 1000 0010 1000 1000 0111 =


0010 0111 1011 0100 0101 1111 1011 0110 1000 0010 1000 1000 0111


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 0111 1011 0100 0101 1111 1011 0110 1000 0010 1000 1000 0111


Decimal number -0.000 282 005 868 4 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0101 1111 1011 0110 1000 0010 1000 1000 0111


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