-0.000 282 006 288 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 288(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
-0.000 282 006 288(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:

|-0.000 282 006 288| = 0.000 282 006 288


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: 0.000 282 006 288.

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) 0.000 282 006 288 × 2 = 0 + 0.000 564 012 576;
  • 2) 0.000 564 012 576 × 2 = 0 + 0.001 128 025 152;
  • 3) 0.001 128 025 152 × 2 = 0 + 0.002 256 050 304;
  • 4) 0.002 256 050 304 × 2 = 0 + 0.004 512 100 608;
  • 5) 0.004 512 100 608 × 2 = 0 + 0.009 024 201 216;
  • 6) 0.009 024 201 216 × 2 = 0 + 0.018 048 402 432;
  • 7) 0.018 048 402 432 × 2 = 0 + 0.036 096 804 864;
  • 8) 0.036 096 804 864 × 2 = 0 + 0.072 193 609 728;
  • 9) 0.072 193 609 728 × 2 = 0 + 0.144 387 219 456;
  • 10) 0.144 387 219 456 × 2 = 0 + 0.288 774 438 912;
  • 11) 0.288 774 438 912 × 2 = 0 + 0.577 548 877 824;
  • 12) 0.577 548 877 824 × 2 = 1 + 0.155 097 755 648;
  • 13) 0.155 097 755 648 × 2 = 0 + 0.310 195 511 296;
  • 14) 0.310 195 511 296 × 2 = 0 + 0.620 391 022 592;
  • 15) 0.620 391 022 592 × 2 = 1 + 0.240 782 045 184;
  • 16) 0.240 782 045 184 × 2 = 0 + 0.481 564 090 368;
  • 17) 0.481 564 090 368 × 2 = 0 + 0.963 128 180 736;
  • 18) 0.963 128 180 736 × 2 = 1 + 0.926 256 361 472;
  • 19) 0.926 256 361 472 × 2 = 1 + 0.852 512 722 944;
  • 20) 0.852 512 722 944 × 2 = 1 + 0.705 025 445 888;
  • 21) 0.705 025 445 888 × 2 = 1 + 0.410 050 891 776;
  • 22) 0.410 050 891 776 × 2 = 0 + 0.820 101 783 552;
  • 23) 0.820 101 783 552 × 2 = 1 + 0.640 203 567 104;
  • 24) 0.640 203 567 104 × 2 = 1 + 0.280 407 134 208;
  • 25) 0.280 407 134 208 × 2 = 0 + 0.560 814 268 416;
  • 26) 0.560 814 268 416 × 2 = 1 + 0.121 628 536 832;
  • 27) 0.121 628 536 832 × 2 = 0 + 0.243 257 073 664;
  • 28) 0.243 257 073 664 × 2 = 0 + 0.486 514 147 328;
  • 29) 0.486 514 147 328 × 2 = 0 + 0.973 028 294 656;
  • 30) 0.973 028 294 656 × 2 = 1 + 0.946 056 589 312;
  • 31) 0.946 056 589 312 × 2 = 1 + 0.892 113 178 624;
  • 32) 0.892 113 178 624 × 2 = 1 + 0.784 226 357 248;
  • 33) 0.784 226 357 248 × 2 = 1 + 0.568 452 714 496;
  • 34) 0.568 452 714 496 × 2 = 1 + 0.136 905 428 992;
  • 35) 0.136 905 428 992 × 2 = 0 + 0.273 810 857 984;
  • 36) 0.273 810 857 984 × 2 = 0 + 0.547 621 715 968;
  • 37) 0.547 621 715 968 × 2 = 1 + 0.095 243 431 936;
  • 38) 0.095 243 431 936 × 2 = 0 + 0.190 486 863 872;
  • 39) 0.190 486 863 872 × 2 = 0 + 0.380 973 727 744;
  • 40) 0.380 973 727 744 × 2 = 0 + 0.761 947 455 488;
  • 41) 0.761 947 455 488 × 2 = 1 + 0.523 894 910 976;
  • 42) 0.523 894 910 976 × 2 = 1 + 0.047 789 821 952;
  • 43) 0.047 789 821 952 × 2 = 0 + 0.095 579 643 904;
  • 44) 0.095 579 643 904 × 2 = 0 + 0.191 159 287 808;
  • 45) 0.191 159 287 808 × 2 = 0 + 0.382 318 575 616;
  • 46) 0.382 318 575 616 × 2 = 0 + 0.764 637 151 232;
  • 47) 0.764 637 151 232 × 2 = 1 + 0.529 274 302 464;
  • 48) 0.529 274 302 464 × 2 = 1 + 0.058 548 604 928;
  • 49) 0.058 548 604 928 × 2 = 0 + 0.117 097 209 856;
  • 50) 0.117 097 209 856 × 2 = 0 + 0.234 194 419 712;
  • 51) 0.234 194 419 712 × 2 = 0 + 0.468 388 839 424;
  • 52) 0.468 388 839 424 × 2 = 0 + 0.936 777 678 848;
  • 53) 0.936 777 678 848 × 2 = 1 + 0.873 555 357 696;
  • 54) 0.873 555 357 696 × 2 = 1 + 0.747 110 715 392;
  • 55) 0.747 110 715 392 × 2 = 1 + 0.494 221 430 784;
  • 56) 0.494 221 430 784 × 2 = 0 + 0.988 442 861 568;
  • 57) 0.988 442 861 568 × 2 = 1 + 0.976 885 723 136;
  • 58) 0.976 885 723 136 × 2 = 1 + 0.953 771 446 272;
  • 59) 0.953 771 446 272 × 2 = 1 + 0.907 542 892 544;
  • 60) 0.907 542 892 544 × 2 = 1 + 0.815 085 785 088;
  • 61) 0.815 085 785 088 × 2 = 1 + 0.630 171 570 176;
  • 62) 0.630 171 570 176 × 2 = 1 + 0.260 343 140 352;
  • 63) 0.260 343 140 352 × 2 = 0 + 0.520 686 280 704;
  • 64) 0.520 686 280 704 × 2 = 1 + 0.041 372 561 408;

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:


0.000 282 006 288(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1100 1000 1100 0011 0000 1110 1111 1101(2)

6. Positive number before normalization:

0.000 282 006 288(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1100 1000 1100 0011 0000 1110 1111 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:


0.000 282 006 288(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1100 1000 1100 0011 0000 1110 1111 1101(2) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1100 1000 1100 0011 0000 1110 1111 1101(2) × 20 =


1.0010 0111 1011 0100 0111 1100 1000 1100 0011 0000 1110 1111 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 0111 1100 1000 1100 0011 0000 1110 1111 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 0111 1100 1000 1100 0011 0000 1110 1111 1101 =


0010 0111 1011 0100 0111 1100 1000 1100 0011 0000 1110 1111 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 0111 1100 1000 1100 0011 0000 1110 1111 1101


Decimal number -0.000 282 006 288 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0111 1100 1000 1100 0011 0000 1110 1111 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