-0.000 282 005 894 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 894(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
-0.000 282 005 894(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:

|-0.000 282 005 894| = 0.000 282 005 894


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: 0.000 282 005 894.

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) 0.000 282 005 894 × 2 = 0 + 0.000 564 011 788;
  • 2) 0.000 564 011 788 × 2 = 0 + 0.001 128 023 576;
  • 3) 0.001 128 023 576 × 2 = 0 + 0.002 256 047 152;
  • 4) 0.002 256 047 152 × 2 = 0 + 0.004 512 094 304;
  • 5) 0.004 512 094 304 × 2 = 0 + 0.009 024 188 608;
  • 6) 0.009 024 188 608 × 2 = 0 + 0.018 048 377 216;
  • 7) 0.018 048 377 216 × 2 = 0 + 0.036 096 754 432;
  • 8) 0.036 096 754 432 × 2 = 0 + 0.072 193 508 864;
  • 9) 0.072 193 508 864 × 2 = 0 + 0.144 387 017 728;
  • 10) 0.144 387 017 728 × 2 = 0 + 0.288 774 035 456;
  • 11) 0.288 774 035 456 × 2 = 0 + 0.577 548 070 912;
  • 12) 0.577 548 070 912 × 2 = 1 + 0.155 096 141 824;
  • 13) 0.155 096 141 824 × 2 = 0 + 0.310 192 283 648;
  • 14) 0.310 192 283 648 × 2 = 0 + 0.620 384 567 296;
  • 15) 0.620 384 567 296 × 2 = 1 + 0.240 769 134 592;
  • 16) 0.240 769 134 592 × 2 = 0 + 0.481 538 269 184;
  • 17) 0.481 538 269 184 × 2 = 0 + 0.963 076 538 368;
  • 18) 0.963 076 538 368 × 2 = 1 + 0.926 153 076 736;
  • 19) 0.926 153 076 736 × 2 = 1 + 0.852 306 153 472;
  • 20) 0.852 306 153 472 × 2 = 1 + 0.704 612 306 944;
  • 21) 0.704 612 306 944 × 2 = 1 + 0.409 224 613 888;
  • 22) 0.409 224 613 888 × 2 = 0 + 0.818 449 227 776;
  • 23) 0.818 449 227 776 × 2 = 1 + 0.636 898 455 552;
  • 24) 0.636 898 455 552 × 2 = 1 + 0.273 796 911 104;
  • 25) 0.273 796 911 104 × 2 = 0 + 0.547 593 822 208;
  • 26) 0.547 593 822 208 × 2 = 1 + 0.095 187 644 416;
  • 27) 0.095 187 644 416 × 2 = 0 + 0.190 375 288 832;
  • 28) 0.190 375 288 832 × 2 = 0 + 0.380 750 577 664;
  • 29) 0.380 750 577 664 × 2 = 0 + 0.761 501 155 328;
  • 30) 0.761 501 155 328 × 2 = 1 + 0.523 002 310 656;
  • 31) 0.523 002 310 656 × 2 = 1 + 0.046 004 621 312;
  • 32) 0.046 004 621 312 × 2 = 0 + 0.092 009 242 624;
  • 33) 0.092 009 242 624 × 2 = 0 + 0.184 018 485 248;
  • 34) 0.184 018 485 248 × 2 = 0 + 0.368 036 970 496;
  • 35) 0.368 036 970 496 × 2 = 0 + 0.736 073 940 992;
  • 36) 0.736 073 940 992 × 2 = 1 + 0.472 147 881 984;
  • 37) 0.472 147 881 984 × 2 = 0 + 0.944 295 763 968;
  • 38) 0.944 295 763 968 × 2 = 1 + 0.888 591 527 936;
  • 39) 0.888 591 527 936 × 2 = 1 + 0.777 183 055 872;
  • 40) 0.777 183 055 872 × 2 = 1 + 0.554 366 111 744;
  • 41) 0.554 366 111 744 × 2 = 1 + 0.108 732 223 488;
  • 42) 0.108 732 223 488 × 2 = 0 + 0.217 464 446 976;
  • 43) 0.217 464 446 976 × 2 = 0 + 0.434 928 893 952;
  • 44) 0.434 928 893 952 × 2 = 0 + 0.869 857 787 904;
  • 45) 0.869 857 787 904 × 2 = 1 + 0.739 715 575 808;
  • 46) 0.739 715 575 808 × 2 = 1 + 0.479 431 151 616;
  • 47) 0.479 431 151 616 × 2 = 0 + 0.958 862 303 232;
  • 48) 0.958 862 303 232 × 2 = 1 + 0.917 724 606 464;
  • 49) 0.917 724 606 464 × 2 = 1 + 0.835 449 212 928;
  • 50) 0.835 449 212 928 × 2 = 1 + 0.670 898 425 856;
  • 51) 0.670 898 425 856 × 2 = 1 + 0.341 796 851 712;
  • 52) 0.341 796 851 712 × 2 = 0 + 0.683 593 703 424;
  • 53) 0.683 593 703 424 × 2 = 1 + 0.367 187 406 848;
  • 54) 0.367 187 406 848 × 2 = 0 + 0.734 374 813 696;
  • 55) 0.734 374 813 696 × 2 = 1 + 0.468 749 627 392;
  • 56) 0.468 749 627 392 × 2 = 0 + 0.937 499 254 784;
  • 57) 0.937 499 254 784 × 2 = 1 + 0.874 998 509 568;
  • 58) 0.874 998 509 568 × 2 = 1 + 0.749 997 019 136;
  • 59) 0.749 997 019 136 × 2 = 1 + 0.499 994 038 272;
  • 60) 0.499 994 038 272 × 2 = 0 + 0.999 988 076 544;
  • 61) 0.999 988 076 544 × 2 = 1 + 0.999 976 153 088;
  • 62) 0.999 976 153 088 × 2 = 1 + 0.999 952 306 176;
  • 63) 0.999 952 306 176 × 2 = 1 + 0.999 904 612 352;
  • 64) 0.999 904 612 352 × 2 = 1 + 0.999 809 224 704;

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:


0.000 282 005 894(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0001 0111 1000 1101 1110 1010 1110 1111(2)

6. Positive number before normalization:

0.000 282 005 894(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0001 0111 1000 1101 1110 1010 1110 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:


0.000 282 005 894(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0001 0111 1000 1101 1110 1010 1110 1111(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0001 0111 1000 1101 1110 1010 1110 1111(2) × 20 =


1.0010 0111 1011 0100 0110 0001 0111 1000 1101 1110 1010 1110 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 0110 0001 0111 1000 1101 1110 1010 1110 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 0110 0001 0111 1000 1101 1110 1010 1110 1111 =


0010 0111 1011 0100 0110 0001 0111 1000 1101 1110 1010 1110 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 0110 0001 0111 1000 1101 1110 1010 1110 1111


Decimal number -0.000 282 005 894 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0001 0111 1000 1101 1110 1010 1110 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