-0.000 282 005 934 4 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 934 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
-0.000 282 005 934 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:

|-0.000 282 005 934 4| = 0.000 282 005 934 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: 0.000 282 005 934 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) 0.000 282 005 934 4 × 2 = 0 + 0.000 564 011 868 8;
  • 2) 0.000 564 011 868 8 × 2 = 0 + 0.001 128 023 737 6;
  • 3) 0.001 128 023 737 6 × 2 = 0 + 0.002 256 047 475 2;
  • 4) 0.002 256 047 475 2 × 2 = 0 + 0.004 512 094 950 4;
  • 5) 0.004 512 094 950 4 × 2 = 0 + 0.009 024 189 900 8;
  • 6) 0.009 024 189 900 8 × 2 = 0 + 0.018 048 379 801 6;
  • 7) 0.018 048 379 801 6 × 2 = 0 + 0.036 096 759 603 2;
  • 8) 0.036 096 759 603 2 × 2 = 0 + 0.072 193 519 206 4;
  • 9) 0.072 193 519 206 4 × 2 = 0 + 0.144 387 038 412 8;
  • 10) 0.144 387 038 412 8 × 2 = 0 + 0.288 774 076 825 6;
  • 11) 0.288 774 076 825 6 × 2 = 0 + 0.577 548 153 651 2;
  • 12) 0.577 548 153 651 2 × 2 = 1 + 0.155 096 307 302 4;
  • 13) 0.155 096 307 302 4 × 2 = 0 + 0.310 192 614 604 8;
  • 14) 0.310 192 614 604 8 × 2 = 0 + 0.620 385 229 209 6;
  • 15) 0.620 385 229 209 6 × 2 = 1 + 0.240 770 458 419 2;
  • 16) 0.240 770 458 419 2 × 2 = 0 + 0.481 540 916 838 4;
  • 17) 0.481 540 916 838 4 × 2 = 0 + 0.963 081 833 676 8;
  • 18) 0.963 081 833 676 8 × 2 = 1 + 0.926 163 667 353 6;
  • 19) 0.926 163 667 353 6 × 2 = 1 + 0.852 327 334 707 2;
  • 20) 0.852 327 334 707 2 × 2 = 1 + 0.704 654 669 414 4;
  • 21) 0.704 654 669 414 4 × 2 = 1 + 0.409 309 338 828 8;
  • 22) 0.409 309 338 828 8 × 2 = 0 + 0.818 618 677 657 6;
  • 23) 0.818 618 677 657 6 × 2 = 1 + 0.637 237 355 315 2;
  • 24) 0.637 237 355 315 2 × 2 = 1 + 0.274 474 710 630 4;
  • 25) 0.274 474 710 630 4 × 2 = 0 + 0.548 949 421 260 8;
  • 26) 0.548 949 421 260 8 × 2 = 1 + 0.097 898 842 521 6;
  • 27) 0.097 898 842 521 6 × 2 = 0 + 0.195 797 685 043 2;
  • 28) 0.195 797 685 043 2 × 2 = 0 + 0.391 595 370 086 4;
  • 29) 0.391 595 370 086 4 × 2 = 0 + 0.783 190 740 172 8;
  • 30) 0.783 190 740 172 8 × 2 = 1 + 0.566 381 480 345 6;
  • 31) 0.566 381 480 345 6 × 2 = 1 + 0.132 762 960 691 2;
  • 32) 0.132 762 960 691 2 × 2 = 0 + 0.265 525 921 382 4;
  • 33) 0.265 525 921 382 4 × 2 = 0 + 0.531 051 842 764 8;
  • 34) 0.531 051 842 764 8 × 2 = 1 + 0.062 103 685 529 6;
  • 35) 0.062 103 685 529 6 × 2 = 0 + 0.124 207 371 059 2;
  • 36) 0.124 207 371 059 2 × 2 = 0 + 0.248 414 742 118 4;
  • 37) 0.248 414 742 118 4 × 2 = 0 + 0.496 829 484 236 8;
  • 38) 0.496 829 484 236 8 × 2 = 0 + 0.993 658 968 473 6;
  • 39) 0.993 658 968 473 6 × 2 = 1 + 0.987 317 936 947 2;
  • 40) 0.987 317 936 947 2 × 2 = 1 + 0.974 635 873 894 4;
  • 41) 0.974 635 873 894 4 × 2 = 1 + 0.949 271 747 788 8;
  • 42) 0.949 271 747 788 8 × 2 = 1 + 0.898 543 495 577 6;
  • 43) 0.898 543 495 577 6 × 2 = 1 + 0.797 086 991 155 2;
  • 44) 0.797 086 991 155 2 × 2 = 1 + 0.594 173 982 310 4;
  • 45) 0.594 173 982 310 4 × 2 = 1 + 0.188 347 964 620 8;
  • 46) 0.188 347 964 620 8 × 2 = 0 + 0.376 695 929 241 6;
  • 47) 0.376 695 929 241 6 × 2 = 0 + 0.753 391 858 483 2;
  • 48) 0.753 391 858 483 2 × 2 = 1 + 0.506 783 716 966 4;
  • 49) 0.506 783 716 966 4 × 2 = 1 + 0.013 567 433 932 8;
  • 50) 0.013 567 433 932 8 × 2 = 0 + 0.027 134 867 865 6;
  • 51) 0.027 134 867 865 6 × 2 = 0 + 0.054 269 735 731 2;
  • 52) 0.054 269 735 731 2 × 2 = 0 + 0.108 539 471 462 4;
  • 53) 0.108 539 471 462 4 × 2 = 0 + 0.217 078 942 924 8;
  • 54) 0.217 078 942 924 8 × 2 = 0 + 0.434 157 885 849 6;
  • 55) 0.434 157 885 849 6 × 2 = 0 + 0.868 315 771 699 2;
  • 56) 0.868 315 771 699 2 × 2 = 1 + 0.736 631 543 398 4;
  • 57) 0.736 631 543 398 4 × 2 = 1 + 0.473 263 086 796 8;
  • 58) 0.473 263 086 796 8 × 2 = 0 + 0.946 526 173 593 6;
  • 59) 0.946 526 173 593 6 × 2 = 1 + 0.893 052 347 187 2;
  • 60) 0.893 052 347 187 2 × 2 = 1 + 0.786 104 694 374 4;
  • 61) 0.786 104 694 374 4 × 2 = 1 + 0.572 209 388 748 8;
  • 62) 0.572 209 388 748 8 × 2 = 1 + 0.144 418 777 497 6;
  • 63) 0.144 418 777 497 6 × 2 = 0 + 0.288 837 554 995 2;
  • 64) 0.288 837 554 995 2 × 2 = 0 + 0.577 675 109 990 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:


0.000 282 005 934 4(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0100 0011 1111 1001 1000 0001 1011 1100(2)

6. Positive number before normalization:

0.000 282 005 934 4(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0100 0011 1111 1001 1000 0001 1011 1100(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:


0.000 282 005 934 4(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0100 0011 1111 1001 1000 0001 1011 1100(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0100 0011 1111 1001 1000 0001 1011 1100(2) × 20 =


1.0010 0111 1011 0100 0110 0100 0011 1111 1001 1000 0001 1011 1100(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 0110 0100 0011 1111 1001 1000 0001 1011 1100


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 0110 0100 0011 1111 1001 1000 0001 1011 1100 =


0010 0111 1011 0100 0110 0100 0011 1111 1001 1000 0001 1011 1100


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 0110 0100 0011 1111 1001 1000 0001 1011 1100


Decimal number -0.000 282 005 934 4 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0100 0011 1111 1001 1000 0001 1011 1100


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