-0.000 282 005 951 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 951 2(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
-0.000 282 005 951 2(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:

|-0.000 282 005 951 2| = 0.000 282 005 951 2


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: 0.000 282 005 951 2.

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) 0.000 282 005 951 2 × 2 = 0 + 0.000 564 011 902 4;
  • 2) 0.000 564 011 902 4 × 2 = 0 + 0.001 128 023 804 8;
  • 3) 0.001 128 023 804 8 × 2 = 0 + 0.002 256 047 609 6;
  • 4) 0.002 256 047 609 6 × 2 = 0 + 0.004 512 095 219 2;
  • 5) 0.004 512 095 219 2 × 2 = 0 + 0.009 024 190 438 4;
  • 6) 0.009 024 190 438 4 × 2 = 0 + 0.018 048 380 876 8;
  • 7) 0.018 048 380 876 8 × 2 = 0 + 0.036 096 761 753 6;
  • 8) 0.036 096 761 753 6 × 2 = 0 + 0.072 193 523 507 2;
  • 9) 0.072 193 523 507 2 × 2 = 0 + 0.144 387 047 014 4;
  • 10) 0.144 387 047 014 4 × 2 = 0 + 0.288 774 094 028 8;
  • 11) 0.288 774 094 028 8 × 2 = 0 + 0.577 548 188 057 6;
  • 12) 0.577 548 188 057 6 × 2 = 1 + 0.155 096 376 115 2;
  • 13) 0.155 096 376 115 2 × 2 = 0 + 0.310 192 752 230 4;
  • 14) 0.310 192 752 230 4 × 2 = 0 + 0.620 385 504 460 8;
  • 15) 0.620 385 504 460 8 × 2 = 1 + 0.240 771 008 921 6;
  • 16) 0.240 771 008 921 6 × 2 = 0 + 0.481 542 017 843 2;
  • 17) 0.481 542 017 843 2 × 2 = 0 + 0.963 084 035 686 4;
  • 18) 0.963 084 035 686 4 × 2 = 1 + 0.926 168 071 372 8;
  • 19) 0.926 168 071 372 8 × 2 = 1 + 0.852 336 142 745 6;
  • 20) 0.852 336 142 745 6 × 2 = 1 + 0.704 672 285 491 2;
  • 21) 0.704 672 285 491 2 × 2 = 1 + 0.409 344 570 982 4;
  • 22) 0.409 344 570 982 4 × 2 = 0 + 0.818 689 141 964 8;
  • 23) 0.818 689 141 964 8 × 2 = 1 + 0.637 378 283 929 6;
  • 24) 0.637 378 283 929 6 × 2 = 1 + 0.274 756 567 859 2;
  • 25) 0.274 756 567 859 2 × 2 = 0 + 0.549 513 135 718 4;
  • 26) 0.549 513 135 718 4 × 2 = 1 + 0.099 026 271 436 8;
  • 27) 0.099 026 271 436 8 × 2 = 0 + 0.198 052 542 873 6;
  • 28) 0.198 052 542 873 6 × 2 = 0 + 0.396 105 085 747 2;
  • 29) 0.396 105 085 747 2 × 2 = 0 + 0.792 210 171 494 4;
  • 30) 0.792 210 171 494 4 × 2 = 1 + 0.584 420 342 988 8;
  • 31) 0.584 420 342 988 8 × 2 = 1 + 0.168 840 685 977 6;
  • 32) 0.168 840 685 977 6 × 2 = 0 + 0.337 681 371 955 2;
  • 33) 0.337 681 371 955 2 × 2 = 0 + 0.675 362 743 910 4;
  • 34) 0.675 362 743 910 4 × 2 = 1 + 0.350 725 487 820 8;
  • 35) 0.350 725 487 820 8 × 2 = 0 + 0.701 450 975 641 6;
  • 36) 0.701 450 975 641 6 × 2 = 1 + 0.402 901 951 283 2;
  • 37) 0.402 901 951 283 2 × 2 = 0 + 0.805 803 902 566 4;
  • 38) 0.805 803 902 566 4 × 2 = 1 + 0.611 607 805 132 8;
  • 39) 0.611 607 805 132 8 × 2 = 1 + 0.223 215 610 265 6;
  • 40) 0.223 215 610 265 6 × 2 = 0 + 0.446 431 220 531 2;
  • 41) 0.446 431 220 531 2 × 2 = 0 + 0.892 862 441 062 4;
  • 42) 0.892 862 441 062 4 × 2 = 1 + 0.785 724 882 124 8;
  • 43) 0.785 724 882 124 8 × 2 = 1 + 0.571 449 764 249 6;
  • 44) 0.571 449 764 249 6 × 2 = 1 + 0.142 899 528 499 2;
  • 45) 0.142 899 528 499 2 × 2 = 0 + 0.285 799 056 998 4;
  • 46) 0.285 799 056 998 4 × 2 = 0 + 0.571 598 113 996 8;
  • 47) 0.571 598 113 996 8 × 2 = 1 + 0.143 196 227 993 6;
  • 48) 0.143 196 227 993 6 × 2 = 0 + 0.286 392 455 987 2;
  • 49) 0.286 392 455 987 2 × 2 = 0 + 0.572 784 911 974 4;
  • 50) 0.572 784 911 974 4 × 2 = 1 + 0.145 569 823 948 8;
  • 51) 0.145 569 823 948 8 × 2 = 0 + 0.291 139 647 897 6;
  • 52) 0.291 139 647 897 6 × 2 = 0 + 0.582 279 295 795 2;
  • 53) 0.582 279 295 795 2 × 2 = 1 + 0.164 558 591 590 4;
  • 54) 0.164 558 591 590 4 × 2 = 0 + 0.329 117 183 180 8;
  • 55) 0.329 117 183 180 8 × 2 = 0 + 0.658 234 366 361 6;
  • 56) 0.658 234 366 361 6 × 2 = 1 + 0.316 468 732 723 2;
  • 57) 0.316 468 732 723 2 × 2 = 0 + 0.632 937 465 446 4;
  • 58) 0.632 937 465 446 4 × 2 = 1 + 0.265 874 930 892 8;
  • 59) 0.265 874 930 892 8 × 2 = 0 + 0.531 749 861 785 6;
  • 60) 0.531 749 861 785 6 × 2 = 1 + 0.063 499 723 571 2;
  • 61) 0.063 499 723 571 2 × 2 = 0 + 0.126 999 447 142 4;
  • 62) 0.126 999 447 142 4 × 2 = 0 + 0.253 998 894 284 8;
  • 63) 0.253 998 894 284 8 × 2 = 0 + 0.507 997 788 569 6;
  • 64) 0.507 997 788 569 6 × 2 = 1 + 0.015 995 577 139 2;

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:


0.000 282 005 951 2(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0101 0110 0111 0010 0100 1001 0101 0001(2)

6. Positive number before normalization:

0.000 282 005 951 2(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0101 0110 0111 0010 0100 1001 0101 0001(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:


0.000 282 005 951 2(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0101 0110 0111 0010 0100 1001 0101 0001(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0101 0110 0111 0010 0100 1001 0101 0001(2) × 20 =


1.0010 0111 1011 0100 0110 0101 0110 0111 0010 0100 1001 0101 0001(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 0101 0110 0111 0010 0100 1001 0101 0001


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 0101 0110 0111 0010 0100 1001 0101 0001 =


0010 0111 1011 0100 0110 0101 0110 0111 0010 0100 1001 0101 0001


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 0101 0110 0111 0010 0100 1001 0101 0001


Decimal number -0.000 282 005 951 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0101 0110 0111 0010 0100 1001 0101 0001


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