-0.000 282 005 536 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 536(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
-0.000 282 005 536(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:

|-0.000 282 005 536| = 0.000 282 005 536


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: 0.000 282 005 536.

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) 0.000 282 005 536 × 2 = 0 + 0.000 564 011 072;
  • 2) 0.000 564 011 072 × 2 = 0 + 0.001 128 022 144;
  • 3) 0.001 128 022 144 × 2 = 0 + 0.002 256 044 288;
  • 4) 0.002 256 044 288 × 2 = 0 + 0.004 512 088 576;
  • 5) 0.004 512 088 576 × 2 = 0 + 0.009 024 177 152;
  • 6) 0.009 024 177 152 × 2 = 0 + 0.018 048 354 304;
  • 7) 0.018 048 354 304 × 2 = 0 + 0.036 096 708 608;
  • 8) 0.036 096 708 608 × 2 = 0 + 0.072 193 417 216;
  • 9) 0.072 193 417 216 × 2 = 0 + 0.144 386 834 432;
  • 10) 0.144 386 834 432 × 2 = 0 + 0.288 773 668 864;
  • 11) 0.288 773 668 864 × 2 = 0 + 0.577 547 337 728;
  • 12) 0.577 547 337 728 × 2 = 1 + 0.155 094 675 456;
  • 13) 0.155 094 675 456 × 2 = 0 + 0.310 189 350 912;
  • 14) 0.310 189 350 912 × 2 = 0 + 0.620 378 701 824;
  • 15) 0.620 378 701 824 × 2 = 1 + 0.240 757 403 648;
  • 16) 0.240 757 403 648 × 2 = 0 + 0.481 514 807 296;
  • 17) 0.481 514 807 296 × 2 = 0 + 0.963 029 614 592;
  • 18) 0.963 029 614 592 × 2 = 1 + 0.926 059 229 184;
  • 19) 0.926 059 229 184 × 2 = 1 + 0.852 118 458 368;
  • 20) 0.852 118 458 368 × 2 = 1 + 0.704 236 916 736;
  • 21) 0.704 236 916 736 × 2 = 1 + 0.408 473 833 472;
  • 22) 0.408 473 833 472 × 2 = 0 + 0.816 947 666 944;
  • 23) 0.816 947 666 944 × 2 = 1 + 0.633 895 333 888;
  • 24) 0.633 895 333 888 × 2 = 1 + 0.267 790 667 776;
  • 25) 0.267 790 667 776 × 2 = 0 + 0.535 581 335 552;
  • 26) 0.535 581 335 552 × 2 = 1 + 0.071 162 671 104;
  • 27) 0.071 162 671 104 × 2 = 0 + 0.142 325 342 208;
  • 28) 0.142 325 342 208 × 2 = 0 + 0.284 650 684 416;
  • 29) 0.284 650 684 416 × 2 = 0 + 0.569 301 368 832;
  • 30) 0.569 301 368 832 × 2 = 1 + 0.138 602 737 664;
  • 31) 0.138 602 737 664 × 2 = 0 + 0.277 205 475 328;
  • 32) 0.277 205 475 328 × 2 = 0 + 0.554 410 950 656;
  • 33) 0.554 410 950 656 × 2 = 1 + 0.108 821 901 312;
  • 34) 0.108 821 901 312 × 2 = 0 + 0.217 643 802 624;
  • 35) 0.217 643 802 624 × 2 = 0 + 0.435 287 605 248;
  • 36) 0.435 287 605 248 × 2 = 0 + 0.870 575 210 496;
  • 37) 0.870 575 210 496 × 2 = 1 + 0.741 150 420 992;
  • 38) 0.741 150 420 992 × 2 = 1 + 0.482 300 841 984;
  • 39) 0.482 300 841 984 × 2 = 0 + 0.964 601 683 968;
  • 40) 0.964 601 683 968 × 2 = 1 + 0.929 203 367 936;
  • 41) 0.929 203 367 936 × 2 = 1 + 0.858 406 735 872;
  • 42) 0.858 406 735 872 × 2 = 1 + 0.716 813 471 744;
  • 43) 0.716 813 471 744 × 2 = 1 + 0.433 626 943 488;
  • 44) 0.433 626 943 488 × 2 = 0 + 0.867 253 886 976;
  • 45) 0.867 253 886 976 × 2 = 1 + 0.734 507 773 952;
  • 46) 0.734 507 773 952 × 2 = 1 + 0.469 015 547 904;
  • 47) 0.469 015 547 904 × 2 = 0 + 0.938 031 095 808;
  • 48) 0.938 031 095 808 × 2 = 1 + 0.876 062 191 616;
  • 49) 0.876 062 191 616 × 2 = 1 + 0.752 124 383 232;
  • 50) 0.752 124 383 232 × 2 = 1 + 0.504 248 766 464;
  • 51) 0.504 248 766 464 × 2 = 1 + 0.008 497 532 928;
  • 52) 0.008 497 532 928 × 2 = 0 + 0.016 995 065 856;
  • 53) 0.016 995 065 856 × 2 = 0 + 0.033 990 131 712;
  • 54) 0.033 990 131 712 × 2 = 0 + 0.067 980 263 424;
  • 55) 0.067 980 263 424 × 2 = 0 + 0.135 960 526 848;
  • 56) 0.135 960 526 848 × 2 = 0 + 0.271 921 053 696;
  • 57) 0.271 921 053 696 × 2 = 0 + 0.543 842 107 392;
  • 58) 0.543 842 107 392 × 2 = 1 + 0.087 684 214 784;
  • 59) 0.087 684 214 784 × 2 = 0 + 0.175 368 429 568;
  • 60) 0.175 368 429 568 × 2 = 0 + 0.350 736 859 136;
  • 61) 0.350 736 859 136 × 2 = 0 + 0.701 473 718 272;
  • 62) 0.701 473 718 272 × 2 = 1 + 0.402 947 436 544;
  • 63) 0.402 947 436 544 × 2 = 0 + 0.805 894 873 088;
  • 64) 0.805 894 873 088 × 2 = 1 + 0.611 789 746 176;

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:


0.000 282 005 536(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1000 1101 1110 1101 1110 0000 0100 0101(2)

6. Positive number before normalization:

0.000 282 005 536(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1000 1101 1110 1101 1110 0000 0100 0101(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:


0.000 282 005 536(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1000 1101 1110 1101 1110 0000 0100 0101(2) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1000 1101 1110 1101 1110 0000 0100 0101(2) × 20 =


1.0010 0111 1011 0100 0100 1000 1101 1110 1101 1110 0000 0100 0101(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 1000 1101 1110 1101 1110 0000 0100 0101


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 1000 1101 1110 1101 1110 0000 0100 0101 =


0010 0111 1011 0100 0100 1000 1101 1110 1101 1110 0000 0100 0101


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 1000 1101 1110 1101 1110 0000 0100 0101


Decimal number -0.000 282 005 536 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0100 1000 1101 1110 1101 1110 0000 0100 0101


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