-0.000 282 005 513 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 513(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
-0.000 282 005 513(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:

|-0.000 282 005 513| = 0.000 282 005 513


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: 0.000 282 005 513.

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) 0.000 282 005 513 × 2 = 0 + 0.000 564 011 026;
  • 2) 0.000 564 011 026 × 2 = 0 + 0.001 128 022 052;
  • 3) 0.001 128 022 052 × 2 = 0 + 0.002 256 044 104;
  • 4) 0.002 256 044 104 × 2 = 0 + 0.004 512 088 208;
  • 5) 0.004 512 088 208 × 2 = 0 + 0.009 024 176 416;
  • 6) 0.009 024 176 416 × 2 = 0 + 0.018 048 352 832;
  • 7) 0.018 048 352 832 × 2 = 0 + 0.036 096 705 664;
  • 8) 0.036 096 705 664 × 2 = 0 + 0.072 193 411 328;
  • 9) 0.072 193 411 328 × 2 = 0 + 0.144 386 822 656;
  • 10) 0.144 386 822 656 × 2 = 0 + 0.288 773 645 312;
  • 11) 0.288 773 645 312 × 2 = 0 + 0.577 547 290 624;
  • 12) 0.577 547 290 624 × 2 = 1 + 0.155 094 581 248;
  • 13) 0.155 094 581 248 × 2 = 0 + 0.310 189 162 496;
  • 14) 0.310 189 162 496 × 2 = 0 + 0.620 378 324 992;
  • 15) 0.620 378 324 992 × 2 = 1 + 0.240 756 649 984;
  • 16) 0.240 756 649 984 × 2 = 0 + 0.481 513 299 968;
  • 17) 0.481 513 299 968 × 2 = 0 + 0.963 026 599 936;
  • 18) 0.963 026 599 936 × 2 = 1 + 0.926 053 199 872;
  • 19) 0.926 053 199 872 × 2 = 1 + 0.852 106 399 744;
  • 20) 0.852 106 399 744 × 2 = 1 + 0.704 212 799 488;
  • 21) 0.704 212 799 488 × 2 = 1 + 0.408 425 598 976;
  • 22) 0.408 425 598 976 × 2 = 0 + 0.816 851 197 952;
  • 23) 0.816 851 197 952 × 2 = 1 + 0.633 702 395 904;
  • 24) 0.633 702 395 904 × 2 = 1 + 0.267 404 791 808;
  • 25) 0.267 404 791 808 × 2 = 0 + 0.534 809 583 616;
  • 26) 0.534 809 583 616 × 2 = 1 + 0.069 619 167 232;
  • 27) 0.069 619 167 232 × 2 = 0 + 0.139 238 334 464;
  • 28) 0.139 238 334 464 × 2 = 0 + 0.278 476 668 928;
  • 29) 0.278 476 668 928 × 2 = 0 + 0.556 953 337 856;
  • 30) 0.556 953 337 856 × 2 = 1 + 0.113 906 675 712;
  • 31) 0.113 906 675 712 × 2 = 0 + 0.227 813 351 424;
  • 32) 0.227 813 351 424 × 2 = 0 + 0.455 626 702 848;
  • 33) 0.455 626 702 848 × 2 = 0 + 0.911 253 405 696;
  • 34) 0.911 253 405 696 × 2 = 1 + 0.822 506 811 392;
  • 35) 0.822 506 811 392 × 2 = 1 + 0.645 013 622 784;
  • 36) 0.645 013 622 784 × 2 = 1 + 0.290 027 245 568;
  • 37) 0.290 027 245 568 × 2 = 0 + 0.580 054 491 136;
  • 38) 0.580 054 491 136 × 2 = 1 + 0.160 108 982 272;
  • 39) 0.160 108 982 272 × 2 = 0 + 0.320 217 964 544;
  • 40) 0.320 217 964 544 × 2 = 0 + 0.640 435 929 088;
  • 41) 0.640 435 929 088 × 2 = 1 + 0.280 871 858 176;
  • 42) 0.280 871 858 176 × 2 = 0 + 0.561 743 716 352;
  • 43) 0.561 743 716 352 × 2 = 1 + 0.123 487 432 704;
  • 44) 0.123 487 432 704 × 2 = 0 + 0.246 974 865 408;
  • 45) 0.246 974 865 408 × 2 = 0 + 0.493 949 730 816;
  • 46) 0.493 949 730 816 × 2 = 0 + 0.987 899 461 632;
  • 47) 0.987 899 461 632 × 2 = 1 + 0.975 798 923 264;
  • 48) 0.975 798 923 264 × 2 = 1 + 0.951 597 846 528;
  • 49) 0.951 597 846 528 × 2 = 1 + 0.903 195 693 056;
  • 50) 0.903 195 693 056 × 2 = 1 + 0.806 391 386 112;
  • 51) 0.806 391 386 112 × 2 = 1 + 0.612 782 772 224;
  • 52) 0.612 782 772 224 × 2 = 1 + 0.225 565 544 448;
  • 53) 0.225 565 544 448 × 2 = 0 + 0.451 131 088 896;
  • 54) 0.451 131 088 896 × 2 = 0 + 0.902 262 177 792;
  • 55) 0.902 262 177 792 × 2 = 1 + 0.804 524 355 584;
  • 56) 0.804 524 355 584 × 2 = 1 + 0.609 048 711 168;
  • 57) 0.609 048 711 168 × 2 = 1 + 0.218 097 422 336;
  • 58) 0.218 097 422 336 × 2 = 0 + 0.436 194 844 672;
  • 59) 0.436 194 844 672 × 2 = 0 + 0.872 389 689 344;
  • 60) 0.872 389 689 344 × 2 = 1 + 0.744 779 378 688;
  • 61) 0.744 779 378 688 × 2 = 1 + 0.489 558 757 376;
  • 62) 0.489 558 757 376 × 2 = 0 + 0.979 117 514 752;
  • 63) 0.979 117 514 752 × 2 = 1 + 0.958 235 029 504;
  • 64) 0.958 235 029 504 × 2 = 1 + 0.916 470 059 008;

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:


0.000 282 005 513(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 0111 0100 1010 0011 1111 0011 1001 1011(2)

6. Positive number before normalization:

0.000 282 005 513(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 0111 0100 1010 0011 1111 0011 1001 1011(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:


0.000 282 005 513(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 0111 0100 1010 0011 1111 0011 1001 1011(2) =


0.0000 0000 0001 0010 0111 1011 0100 0100 0111 0100 1010 0011 1111 0011 1001 1011(2) × 20 =


1.0010 0111 1011 0100 0100 0111 0100 1010 0011 1111 0011 1001 1011(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 0100 0111 0100 1010 0011 1111 0011 1001 1011


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 0100 0111 0100 1010 0011 1111 0011 1001 1011 =


0010 0111 1011 0100 0100 0111 0100 1010 0011 1111 0011 1001 1011


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 0100 0111 0100 1010 0011 1111 0011 1001 1011


Decimal number -0.000 282 005 513 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0100 0111 0100 1010 0011 1111 0011 1001 1011


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