-0.000 282 005 893 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 893(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
-0.000 282 005 893(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:

|-0.000 282 005 893| = 0.000 282 005 893


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: 0.000 282 005 893.

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) 0.000 282 005 893 × 2 = 0 + 0.000 564 011 786;
  • 2) 0.000 564 011 786 × 2 = 0 + 0.001 128 023 572;
  • 3) 0.001 128 023 572 × 2 = 0 + 0.002 256 047 144;
  • 4) 0.002 256 047 144 × 2 = 0 + 0.004 512 094 288;
  • 5) 0.004 512 094 288 × 2 = 0 + 0.009 024 188 576;
  • 6) 0.009 024 188 576 × 2 = 0 + 0.018 048 377 152;
  • 7) 0.018 048 377 152 × 2 = 0 + 0.036 096 754 304;
  • 8) 0.036 096 754 304 × 2 = 0 + 0.072 193 508 608;
  • 9) 0.072 193 508 608 × 2 = 0 + 0.144 387 017 216;
  • 10) 0.144 387 017 216 × 2 = 0 + 0.288 774 034 432;
  • 11) 0.288 774 034 432 × 2 = 0 + 0.577 548 068 864;
  • 12) 0.577 548 068 864 × 2 = 1 + 0.155 096 137 728;
  • 13) 0.155 096 137 728 × 2 = 0 + 0.310 192 275 456;
  • 14) 0.310 192 275 456 × 2 = 0 + 0.620 384 550 912;
  • 15) 0.620 384 550 912 × 2 = 1 + 0.240 769 101 824;
  • 16) 0.240 769 101 824 × 2 = 0 + 0.481 538 203 648;
  • 17) 0.481 538 203 648 × 2 = 0 + 0.963 076 407 296;
  • 18) 0.963 076 407 296 × 2 = 1 + 0.926 152 814 592;
  • 19) 0.926 152 814 592 × 2 = 1 + 0.852 305 629 184;
  • 20) 0.852 305 629 184 × 2 = 1 + 0.704 611 258 368;
  • 21) 0.704 611 258 368 × 2 = 1 + 0.409 222 516 736;
  • 22) 0.409 222 516 736 × 2 = 0 + 0.818 445 033 472;
  • 23) 0.818 445 033 472 × 2 = 1 + 0.636 890 066 944;
  • 24) 0.636 890 066 944 × 2 = 1 + 0.273 780 133 888;
  • 25) 0.273 780 133 888 × 2 = 0 + 0.547 560 267 776;
  • 26) 0.547 560 267 776 × 2 = 1 + 0.095 120 535 552;
  • 27) 0.095 120 535 552 × 2 = 0 + 0.190 241 071 104;
  • 28) 0.190 241 071 104 × 2 = 0 + 0.380 482 142 208;
  • 29) 0.380 482 142 208 × 2 = 0 + 0.760 964 284 416;
  • 30) 0.760 964 284 416 × 2 = 1 + 0.521 928 568 832;
  • 31) 0.521 928 568 832 × 2 = 1 + 0.043 857 137 664;
  • 32) 0.043 857 137 664 × 2 = 0 + 0.087 714 275 328;
  • 33) 0.087 714 275 328 × 2 = 0 + 0.175 428 550 656;
  • 34) 0.175 428 550 656 × 2 = 0 + 0.350 857 101 312;
  • 35) 0.350 857 101 312 × 2 = 0 + 0.701 714 202 624;
  • 36) 0.701 714 202 624 × 2 = 1 + 0.403 428 405 248;
  • 37) 0.403 428 405 248 × 2 = 0 + 0.806 856 810 496;
  • 38) 0.806 856 810 496 × 2 = 1 + 0.613 713 620 992;
  • 39) 0.613 713 620 992 × 2 = 1 + 0.227 427 241 984;
  • 40) 0.227 427 241 984 × 2 = 0 + 0.454 854 483 968;
  • 41) 0.454 854 483 968 × 2 = 0 + 0.909 708 967 936;
  • 42) 0.909 708 967 936 × 2 = 1 + 0.819 417 935 872;
  • 43) 0.819 417 935 872 × 2 = 1 + 0.638 835 871 744;
  • 44) 0.638 835 871 744 × 2 = 1 + 0.277 671 743 488;
  • 45) 0.277 671 743 488 × 2 = 0 + 0.555 343 486 976;
  • 46) 0.555 343 486 976 × 2 = 1 + 0.110 686 973 952;
  • 47) 0.110 686 973 952 × 2 = 0 + 0.221 373 947 904;
  • 48) 0.221 373 947 904 × 2 = 0 + 0.442 747 895 808;
  • 49) 0.442 747 895 808 × 2 = 0 + 0.885 495 791 616;
  • 50) 0.885 495 791 616 × 2 = 1 + 0.770 991 583 232;
  • 51) 0.770 991 583 232 × 2 = 1 + 0.541 983 166 464;
  • 52) 0.541 983 166 464 × 2 = 1 + 0.083 966 332 928;
  • 53) 0.083 966 332 928 × 2 = 0 + 0.167 932 665 856;
  • 54) 0.167 932 665 856 × 2 = 0 + 0.335 865 331 712;
  • 55) 0.335 865 331 712 × 2 = 0 + 0.671 730 663 424;
  • 56) 0.671 730 663 424 × 2 = 1 + 0.343 461 326 848;
  • 57) 0.343 461 326 848 × 2 = 0 + 0.686 922 653 696;
  • 58) 0.686 922 653 696 × 2 = 1 + 0.373 845 307 392;
  • 59) 0.373 845 307 392 × 2 = 0 + 0.747 690 614 784;
  • 60) 0.747 690 614 784 × 2 = 1 + 0.495 381 229 568;
  • 61) 0.495 381 229 568 × 2 = 0 + 0.990 762 459 136;
  • 62) 0.990 762 459 136 × 2 = 1 + 0.981 524 918 272;
  • 63) 0.981 524 918 272 × 2 = 1 + 0.963 049 836 544;
  • 64) 0.963 049 836 544 × 2 = 1 + 0.926 099 673 088;

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:


0.000 282 005 893(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0001 0110 0111 0100 0111 0001 0101 0111(2)

6. Positive number before normalization:

0.000 282 005 893(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0001 0110 0111 0100 0111 0001 0101 0111(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:


0.000 282 005 893(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0001 0110 0111 0100 0111 0001 0101 0111(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0001 0110 0111 0100 0111 0001 0101 0111(2) × 20 =


1.0010 0111 1011 0100 0110 0001 0110 0111 0100 0111 0001 0101 0111(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 0001 0110 0111 0100 0111 0001 0101 0111


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 0001 0110 0111 0100 0111 0001 0101 0111 =


0010 0111 1011 0100 0110 0001 0110 0111 0100 0111 0001 0101 0111


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 0001 0110 0111 0100 0111 0001 0101 0111


Decimal number -0.000 282 005 893 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0001 0110 0111 0100 0111 0001 0101 0111


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