-0.000 282 005 914 245 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 914 245(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
-0.000 282 005 914 245(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:

|-0.000 282 005 914 245| = 0.000 282 005 914 245


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: 0.000 282 005 914 245.

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) 0.000 282 005 914 245 × 2 = 0 + 0.000 564 011 828 49;
  • 2) 0.000 564 011 828 49 × 2 = 0 + 0.001 128 023 656 98;
  • 3) 0.001 128 023 656 98 × 2 = 0 + 0.002 256 047 313 96;
  • 4) 0.002 256 047 313 96 × 2 = 0 + 0.004 512 094 627 92;
  • 5) 0.004 512 094 627 92 × 2 = 0 + 0.009 024 189 255 84;
  • 6) 0.009 024 189 255 84 × 2 = 0 + 0.018 048 378 511 68;
  • 7) 0.018 048 378 511 68 × 2 = 0 + 0.036 096 757 023 36;
  • 8) 0.036 096 757 023 36 × 2 = 0 + 0.072 193 514 046 72;
  • 9) 0.072 193 514 046 72 × 2 = 0 + 0.144 387 028 093 44;
  • 10) 0.144 387 028 093 44 × 2 = 0 + 0.288 774 056 186 88;
  • 11) 0.288 774 056 186 88 × 2 = 0 + 0.577 548 112 373 76;
  • 12) 0.577 548 112 373 76 × 2 = 1 + 0.155 096 224 747 52;
  • 13) 0.155 096 224 747 52 × 2 = 0 + 0.310 192 449 495 04;
  • 14) 0.310 192 449 495 04 × 2 = 0 + 0.620 384 898 990 08;
  • 15) 0.620 384 898 990 08 × 2 = 1 + 0.240 769 797 980 16;
  • 16) 0.240 769 797 980 16 × 2 = 0 + 0.481 539 595 960 32;
  • 17) 0.481 539 595 960 32 × 2 = 0 + 0.963 079 191 920 64;
  • 18) 0.963 079 191 920 64 × 2 = 1 + 0.926 158 383 841 28;
  • 19) 0.926 158 383 841 28 × 2 = 1 + 0.852 316 767 682 56;
  • 20) 0.852 316 767 682 56 × 2 = 1 + 0.704 633 535 365 12;
  • 21) 0.704 633 535 365 12 × 2 = 1 + 0.409 267 070 730 24;
  • 22) 0.409 267 070 730 24 × 2 = 0 + 0.818 534 141 460 48;
  • 23) 0.818 534 141 460 48 × 2 = 1 + 0.637 068 282 920 96;
  • 24) 0.637 068 282 920 96 × 2 = 1 + 0.274 136 565 841 92;
  • 25) 0.274 136 565 841 92 × 2 = 0 + 0.548 273 131 683 84;
  • 26) 0.548 273 131 683 84 × 2 = 1 + 0.096 546 263 367 68;
  • 27) 0.096 546 263 367 68 × 2 = 0 + 0.193 092 526 735 36;
  • 28) 0.193 092 526 735 36 × 2 = 0 + 0.386 185 053 470 72;
  • 29) 0.386 185 053 470 72 × 2 = 0 + 0.772 370 106 941 44;
  • 30) 0.772 370 106 941 44 × 2 = 1 + 0.544 740 213 882 88;
  • 31) 0.544 740 213 882 88 × 2 = 1 + 0.089 480 427 765 76;
  • 32) 0.089 480 427 765 76 × 2 = 0 + 0.178 960 855 531 52;
  • 33) 0.178 960 855 531 52 × 2 = 0 + 0.357 921 711 063 04;
  • 34) 0.357 921 711 063 04 × 2 = 0 + 0.715 843 422 126 08;
  • 35) 0.715 843 422 126 08 × 2 = 1 + 0.431 686 844 252 16;
  • 36) 0.431 686 844 252 16 × 2 = 0 + 0.863 373 688 504 32;
  • 37) 0.863 373 688 504 32 × 2 = 1 + 0.726 747 377 008 64;
  • 38) 0.726 747 377 008 64 × 2 = 1 + 0.453 494 754 017 28;
  • 39) 0.453 494 754 017 28 × 2 = 0 + 0.906 989 508 034 56;
  • 40) 0.906 989 508 034 56 × 2 = 1 + 0.813 979 016 069 12;
  • 41) 0.813 979 016 069 12 × 2 = 1 + 0.627 958 032 138 24;
  • 42) 0.627 958 032 138 24 × 2 = 1 + 0.255 916 064 276 48;
  • 43) 0.255 916 064 276 48 × 2 = 0 + 0.511 832 128 552 96;
  • 44) 0.511 832 128 552 96 × 2 = 1 + 0.023 664 257 105 92;
  • 45) 0.023 664 257 105 92 × 2 = 0 + 0.047 328 514 211 84;
  • 46) 0.047 328 514 211 84 × 2 = 0 + 0.094 657 028 423 68;
  • 47) 0.094 657 028 423 68 × 2 = 0 + 0.189 314 056 847 36;
  • 48) 0.189 314 056 847 36 × 2 = 0 + 0.378 628 113 694 72;
  • 49) 0.378 628 113 694 72 × 2 = 0 + 0.757 256 227 389 44;
  • 50) 0.757 256 227 389 44 × 2 = 1 + 0.514 512 454 778 88;
  • 51) 0.514 512 454 778 88 × 2 = 1 + 0.029 024 909 557 76;
  • 52) 0.029 024 909 557 76 × 2 = 0 + 0.058 049 819 115 52;
  • 53) 0.058 049 819 115 52 × 2 = 0 + 0.116 099 638 231 04;
  • 54) 0.116 099 638 231 04 × 2 = 0 + 0.232 199 276 462 08;
  • 55) 0.232 199 276 462 08 × 2 = 0 + 0.464 398 552 924 16;
  • 56) 0.464 398 552 924 16 × 2 = 0 + 0.928 797 105 848 32;
  • 57) 0.928 797 105 848 32 × 2 = 1 + 0.857 594 211 696 64;
  • 58) 0.857 594 211 696 64 × 2 = 1 + 0.715 188 423 393 28;
  • 59) 0.715 188 423 393 28 × 2 = 1 + 0.430 376 846 786 56;
  • 60) 0.430 376 846 786 56 × 2 = 0 + 0.860 753 693 573 12;
  • 61) 0.860 753 693 573 12 × 2 = 1 + 0.721 507 387 146 24;
  • 62) 0.721 507 387 146 24 × 2 = 1 + 0.443 014 774 292 48;
  • 63) 0.443 014 774 292 48 × 2 = 0 + 0.886 029 548 584 96;
  • 64) 0.886 029 548 584 96 × 2 = 1 + 0.772 059 097 169 92;

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:


0.000 282 005 914 245(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1101 0000 0110 0000 1110 1101(2)

6. Positive number before normalization:

0.000 282 005 914 245(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1101 0000 0110 0000 1110 1101(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:


0.000 282 005 914 245(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1101 0000 0110 0000 1110 1101(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1101 0000 0110 0000 1110 1101(2) × 20 =


1.0010 0111 1011 0100 0110 0010 1101 1101 0000 0110 0000 1110 1101(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 0010 1101 1101 0000 0110 0000 1110 1101


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 0010 1101 1101 0000 0110 0000 1110 1101 =


0010 0111 1011 0100 0110 0010 1101 1101 0000 0110 0000 1110 1101


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 0010 1101 1101 0000 0110 0000 1110 1101


Decimal number -0.000 282 005 914 245 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0010 1101 1101 0000 0110 0000 1110 1101


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