-0.000 282 006 326 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 326(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
-0.000 282 006 326(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:

|-0.000 282 006 326| = 0.000 282 006 326


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: 0.000 282 006 326.

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) 0.000 282 006 326 × 2 = 0 + 0.000 564 012 652;
  • 2) 0.000 564 012 652 × 2 = 0 + 0.001 128 025 304;
  • 3) 0.001 128 025 304 × 2 = 0 + 0.002 256 050 608;
  • 4) 0.002 256 050 608 × 2 = 0 + 0.004 512 101 216;
  • 5) 0.004 512 101 216 × 2 = 0 + 0.009 024 202 432;
  • 6) 0.009 024 202 432 × 2 = 0 + 0.018 048 404 864;
  • 7) 0.018 048 404 864 × 2 = 0 + 0.036 096 809 728;
  • 8) 0.036 096 809 728 × 2 = 0 + 0.072 193 619 456;
  • 9) 0.072 193 619 456 × 2 = 0 + 0.144 387 238 912;
  • 10) 0.144 387 238 912 × 2 = 0 + 0.288 774 477 824;
  • 11) 0.288 774 477 824 × 2 = 0 + 0.577 548 955 648;
  • 12) 0.577 548 955 648 × 2 = 1 + 0.155 097 911 296;
  • 13) 0.155 097 911 296 × 2 = 0 + 0.310 195 822 592;
  • 14) 0.310 195 822 592 × 2 = 0 + 0.620 391 645 184;
  • 15) 0.620 391 645 184 × 2 = 1 + 0.240 783 290 368;
  • 16) 0.240 783 290 368 × 2 = 0 + 0.481 566 580 736;
  • 17) 0.481 566 580 736 × 2 = 0 + 0.963 133 161 472;
  • 18) 0.963 133 161 472 × 2 = 1 + 0.926 266 322 944;
  • 19) 0.926 266 322 944 × 2 = 1 + 0.852 532 645 888;
  • 20) 0.852 532 645 888 × 2 = 1 + 0.705 065 291 776;
  • 21) 0.705 065 291 776 × 2 = 1 + 0.410 130 583 552;
  • 22) 0.410 130 583 552 × 2 = 0 + 0.820 261 167 104;
  • 23) 0.820 261 167 104 × 2 = 1 + 0.640 522 334 208;
  • 24) 0.640 522 334 208 × 2 = 1 + 0.281 044 668 416;
  • 25) 0.281 044 668 416 × 2 = 0 + 0.562 089 336 832;
  • 26) 0.562 089 336 832 × 2 = 1 + 0.124 178 673 664;
  • 27) 0.124 178 673 664 × 2 = 0 + 0.248 357 347 328;
  • 28) 0.248 357 347 328 × 2 = 0 + 0.496 714 694 656;
  • 29) 0.496 714 694 656 × 2 = 0 + 0.993 429 389 312;
  • 30) 0.993 429 389 312 × 2 = 1 + 0.986 858 778 624;
  • 31) 0.986 858 778 624 × 2 = 1 + 0.973 717 557 248;
  • 32) 0.973 717 557 248 × 2 = 1 + 0.947 435 114 496;
  • 33) 0.947 435 114 496 × 2 = 1 + 0.894 870 228 992;
  • 34) 0.894 870 228 992 × 2 = 1 + 0.789 740 457 984;
  • 35) 0.789 740 457 984 × 2 = 1 + 0.579 480 915 968;
  • 36) 0.579 480 915 968 × 2 = 1 + 0.158 961 831 936;
  • 37) 0.158 961 831 936 × 2 = 0 + 0.317 923 663 872;
  • 38) 0.317 923 663 872 × 2 = 0 + 0.635 847 327 744;
  • 39) 0.635 847 327 744 × 2 = 1 + 0.271 694 655 488;
  • 40) 0.271 694 655 488 × 2 = 0 + 0.543 389 310 976;
  • 41) 0.543 389 310 976 × 2 = 1 + 0.086 778 621 952;
  • 42) 0.086 778 621 952 × 2 = 0 + 0.173 557 243 904;
  • 43) 0.173 557 243 904 × 2 = 0 + 0.347 114 487 808;
  • 44) 0.347 114 487 808 × 2 = 0 + 0.694 228 975 616;
  • 45) 0.694 228 975 616 × 2 = 1 + 0.388 457 951 232;
  • 46) 0.388 457 951 232 × 2 = 0 + 0.776 915 902 464;
  • 47) 0.776 915 902 464 × 2 = 1 + 0.553 831 804 928;
  • 48) 0.553 831 804 928 × 2 = 1 + 0.107 663 609 856;
  • 49) 0.107 663 609 856 × 2 = 0 + 0.215 327 219 712;
  • 50) 0.215 327 219 712 × 2 = 0 + 0.430 654 439 424;
  • 51) 0.430 654 439 424 × 2 = 0 + 0.861 308 878 848;
  • 52) 0.861 308 878 848 × 2 = 1 + 0.722 617 757 696;
  • 53) 0.722 617 757 696 × 2 = 1 + 0.445 235 515 392;
  • 54) 0.445 235 515 392 × 2 = 0 + 0.890 471 030 784;
  • 55) 0.890 471 030 784 × 2 = 1 + 0.780 942 061 568;
  • 56) 0.780 942 061 568 × 2 = 1 + 0.561 884 123 136;
  • 57) 0.561 884 123 136 × 2 = 1 + 0.123 768 246 272;
  • 58) 0.123 768 246 272 × 2 = 0 + 0.247 536 492 544;
  • 59) 0.247 536 492 544 × 2 = 0 + 0.495 072 985 088;
  • 60) 0.495 072 985 088 × 2 = 0 + 0.990 145 970 176;
  • 61) 0.990 145 970 176 × 2 = 1 + 0.980 291 940 352;
  • 62) 0.980 291 940 352 × 2 = 1 + 0.960 583 880 704;
  • 63) 0.960 583 880 704 × 2 = 1 + 0.921 167 761 408;
  • 64) 0.921 167 761 408 × 2 = 1 + 0.842 335 522 816;

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:


0.000 282 006 326(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1111 0010 1000 1011 0001 1011 1000 1111(2)

6. Positive number before normalization:

0.000 282 006 326(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1111 0010 1000 1011 0001 1011 1000 1111(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:


0.000 282 006 326(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1111 0010 1000 1011 0001 1011 1000 1111(2) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1111 0010 1000 1011 0001 1011 1000 1111(2) × 20 =


1.0010 0111 1011 0100 0111 1111 0010 1000 1011 0001 1011 1000 1111(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 0111 1111 0010 1000 1011 0001 1011 1000 1111


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 0111 1111 0010 1000 1011 0001 1011 1000 1111 =


0010 0111 1011 0100 0111 1111 0010 1000 1011 0001 1011 1000 1111


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 0111 1111 0010 1000 1011 0001 1011 1000 1111


Decimal number -0.000 282 006 326 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0111 1111 0010 1000 1011 0001 1011 1000 1111


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