-0.000 282 005 958 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 958(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
-0.000 282 005 958(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:

|-0.000 282 005 958| = 0.000 282 005 958


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: 0.000 282 005 958.

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) 0.000 282 005 958 × 2 = 0 + 0.000 564 011 916;
  • 2) 0.000 564 011 916 × 2 = 0 + 0.001 128 023 832;
  • 3) 0.001 128 023 832 × 2 = 0 + 0.002 256 047 664;
  • 4) 0.002 256 047 664 × 2 = 0 + 0.004 512 095 328;
  • 5) 0.004 512 095 328 × 2 = 0 + 0.009 024 190 656;
  • 6) 0.009 024 190 656 × 2 = 0 + 0.018 048 381 312;
  • 7) 0.018 048 381 312 × 2 = 0 + 0.036 096 762 624;
  • 8) 0.036 096 762 624 × 2 = 0 + 0.072 193 525 248;
  • 9) 0.072 193 525 248 × 2 = 0 + 0.144 387 050 496;
  • 10) 0.144 387 050 496 × 2 = 0 + 0.288 774 100 992;
  • 11) 0.288 774 100 992 × 2 = 0 + 0.577 548 201 984;
  • 12) 0.577 548 201 984 × 2 = 1 + 0.155 096 403 968;
  • 13) 0.155 096 403 968 × 2 = 0 + 0.310 192 807 936;
  • 14) 0.310 192 807 936 × 2 = 0 + 0.620 385 615 872;
  • 15) 0.620 385 615 872 × 2 = 1 + 0.240 771 231 744;
  • 16) 0.240 771 231 744 × 2 = 0 + 0.481 542 463 488;
  • 17) 0.481 542 463 488 × 2 = 0 + 0.963 084 926 976;
  • 18) 0.963 084 926 976 × 2 = 1 + 0.926 169 853 952;
  • 19) 0.926 169 853 952 × 2 = 1 + 0.852 339 707 904;
  • 20) 0.852 339 707 904 × 2 = 1 + 0.704 679 415 808;
  • 21) 0.704 679 415 808 × 2 = 1 + 0.409 358 831 616;
  • 22) 0.409 358 831 616 × 2 = 0 + 0.818 717 663 232;
  • 23) 0.818 717 663 232 × 2 = 1 + 0.637 435 326 464;
  • 24) 0.637 435 326 464 × 2 = 1 + 0.274 870 652 928;
  • 25) 0.274 870 652 928 × 2 = 0 + 0.549 741 305 856;
  • 26) 0.549 741 305 856 × 2 = 1 + 0.099 482 611 712;
  • 27) 0.099 482 611 712 × 2 = 0 + 0.198 965 223 424;
  • 28) 0.198 965 223 424 × 2 = 0 + 0.397 930 446 848;
  • 29) 0.397 930 446 848 × 2 = 0 + 0.795 860 893 696;
  • 30) 0.795 860 893 696 × 2 = 1 + 0.591 721 787 392;
  • 31) 0.591 721 787 392 × 2 = 1 + 0.183 443 574 784;
  • 32) 0.183 443 574 784 × 2 = 0 + 0.366 887 149 568;
  • 33) 0.366 887 149 568 × 2 = 0 + 0.733 774 299 136;
  • 34) 0.733 774 299 136 × 2 = 1 + 0.467 548 598 272;
  • 35) 0.467 548 598 272 × 2 = 0 + 0.935 097 196 544;
  • 36) 0.935 097 196 544 × 2 = 1 + 0.870 194 393 088;
  • 37) 0.870 194 393 088 × 2 = 1 + 0.740 388 786 176;
  • 38) 0.740 388 786 176 × 2 = 1 + 0.480 777 572 352;
  • 39) 0.480 777 572 352 × 2 = 0 + 0.961 555 144 704;
  • 40) 0.961 555 144 704 × 2 = 1 + 0.923 110 289 408;
  • 41) 0.923 110 289 408 × 2 = 1 + 0.846 220 578 816;
  • 42) 0.846 220 578 816 × 2 = 1 + 0.692 441 157 632;
  • 43) 0.692 441 157 632 × 2 = 1 + 0.384 882 315 264;
  • 44) 0.384 882 315 264 × 2 = 0 + 0.769 764 630 528;
  • 45) 0.769 764 630 528 × 2 = 1 + 0.539 529 261 056;
  • 46) 0.539 529 261 056 × 2 = 1 + 0.079 058 522 112;
  • 47) 0.079 058 522 112 × 2 = 0 + 0.158 117 044 224;
  • 48) 0.158 117 044 224 × 2 = 0 + 0.316 234 088 448;
  • 49) 0.316 234 088 448 × 2 = 0 + 0.632 468 176 896;
  • 50) 0.632 468 176 896 × 2 = 1 + 0.264 936 353 792;
  • 51) 0.264 936 353 792 × 2 = 0 + 0.529 872 707 584;
  • 52) 0.529 872 707 584 × 2 = 1 + 0.059 745 415 168;
  • 53) 0.059 745 415 168 × 2 = 0 + 0.119 490 830 336;
  • 54) 0.119 490 830 336 × 2 = 0 + 0.238 981 660 672;
  • 55) 0.238 981 660 672 × 2 = 0 + 0.477 963 321 344;
  • 56) 0.477 963 321 344 × 2 = 0 + 0.955 926 642 688;
  • 57) 0.955 926 642 688 × 2 = 1 + 0.911 853 285 376;
  • 58) 0.911 853 285 376 × 2 = 1 + 0.823 706 570 752;
  • 59) 0.823 706 570 752 × 2 = 1 + 0.647 413 141 504;
  • 60) 0.647 413 141 504 × 2 = 1 + 0.294 826 283 008;
  • 61) 0.294 826 283 008 × 2 = 0 + 0.589 652 566 016;
  • 62) 0.589 652 566 016 × 2 = 1 + 0.179 305 132 032;
  • 63) 0.179 305 132 032 × 2 = 0 + 0.358 610 264 064;
  • 64) 0.358 610 264 064 × 2 = 0 + 0.717 220 528 128;

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:


0.000 282 005 958(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0101 1101 1110 1100 0101 0000 1111 0100(2)

6. Positive number before normalization:

0.000 282 005 958(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0101 1101 1110 1100 0101 0000 1111 0100(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:


0.000 282 005 958(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0101 1101 1110 1100 0101 0000 1111 0100(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0101 1101 1110 1100 0101 0000 1111 0100(2) × 20 =


1.0010 0111 1011 0100 0110 0101 1101 1110 1100 0101 0000 1111 0100(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 1101 1110 1100 0101 0000 1111 0100


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 1101 1110 1100 0101 0000 1111 0100 =


0010 0111 1011 0100 0110 0101 1101 1110 1100 0101 0000 1111 0100


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 1101 1110 1100 0101 0000 1111 0100


Decimal number -0.000 282 005 958 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0101 1101 1110 1100 0101 0000 1111 0100


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