-0.000 282 005 532 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 532(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
-0.000 282 005 532(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:

|-0.000 282 005 532| = 0.000 282 005 532


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: 0.000 282 005 532.

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) 0.000 282 005 532 × 2 = 0 + 0.000 564 011 064;
  • 2) 0.000 564 011 064 × 2 = 0 + 0.001 128 022 128;
  • 3) 0.001 128 022 128 × 2 = 0 + 0.002 256 044 256;
  • 4) 0.002 256 044 256 × 2 = 0 + 0.004 512 088 512;
  • 5) 0.004 512 088 512 × 2 = 0 + 0.009 024 177 024;
  • 6) 0.009 024 177 024 × 2 = 0 + 0.018 048 354 048;
  • 7) 0.018 048 354 048 × 2 = 0 + 0.036 096 708 096;
  • 8) 0.036 096 708 096 × 2 = 0 + 0.072 193 416 192;
  • 9) 0.072 193 416 192 × 2 = 0 + 0.144 386 832 384;
  • 10) 0.144 386 832 384 × 2 = 0 + 0.288 773 664 768;
  • 11) 0.288 773 664 768 × 2 = 0 + 0.577 547 329 536;
  • 12) 0.577 547 329 536 × 2 = 1 + 0.155 094 659 072;
  • 13) 0.155 094 659 072 × 2 = 0 + 0.310 189 318 144;
  • 14) 0.310 189 318 144 × 2 = 0 + 0.620 378 636 288;
  • 15) 0.620 378 636 288 × 2 = 1 + 0.240 757 272 576;
  • 16) 0.240 757 272 576 × 2 = 0 + 0.481 514 545 152;
  • 17) 0.481 514 545 152 × 2 = 0 + 0.963 029 090 304;
  • 18) 0.963 029 090 304 × 2 = 1 + 0.926 058 180 608;
  • 19) 0.926 058 180 608 × 2 = 1 + 0.852 116 361 216;
  • 20) 0.852 116 361 216 × 2 = 1 + 0.704 232 722 432;
  • 21) 0.704 232 722 432 × 2 = 1 + 0.408 465 444 864;
  • 22) 0.408 465 444 864 × 2 = 0 + 0.816 930 889 728;
  • 23) 0.816 930 889 728 × 2 = 1 + 0.633 861 779 456;
  • 24) 0.633 861 779 456 × 2 = 1 + 0.267 723 558 912;
  • 25) 0.267 723 558 912 × 2 = 0 + 0.535 447 117 824;
  • 26) 0.535 447 117 824 × 2 = 1 + 0.070 894 235 648;
  • 27) 0.070 894 235 648 × 2 = 0 + 0.141 788 471 296;
  • 28) 0.141 788 471 296 × 2 = 0 + 0.283 576 942 592;
  • 29) 0.283 576 942 592 × 2 = 0 + 0.567 153 885 184;
  • 30) 0.567 153 885 184 × 2 = 1 + 0.134 307 770 368;
  • 31) 0.134 307 770 368 × 2 = 0 + 0.268 615 540 736;
  • 32) 0.268 615 540 736 × 2 = 0 + 0.537 231 081 472;
  • 33) 0.537 231 081 472 × 2 = 1 + 0.074 462 162 944;
  • 34) 0.074 462 162 944 × 2 = 0 + 0.148 924 325 888;
  • 35) 0.148 924 325 888 × 2 = 0 + 0.297 848 651 776;
  • 36) 0.297 848 651 776 × 2 = 0 + 0.595 697 303 552;
  • 37) 0.595 697 303 552 × 2 = 1 + 0.191 394 607 104;
  • 38) 0.191 394 607 104 × 2 = 0 + 0.382 789 214 208;
  • 39) 0.382 789 214 208 × 2 = 0 + 0.765 578 428 416;
  • 40) 0.765 578 428 416 × 2 = 1 + 0.531 156 856 832;
  • 41) 0.531 156 856 832 × 2 = 1 + 0.062 313 713 664;
  • 42) 0.062 313 713 664 × 2 = 0 + 0.124 627 427 328;
  • 43) 0.124 627 427 328 × 2 = 0 + 0.249 254 854 656;
  • 44) 0.249 254 854 656 × 2 = 0 + 0.498 509 709 312;
  • 45) 0.498 509 709 312 × 2 = 0 + 0.997 019 418 624;
  • 46) 0.997 019 418 624 × 2 = 1 + 0.994 038 837 248;
  • 47) 0.994 038 837 248 × 2 = 1 + 0.988 077 674 496;
  • 48) 0.988 077 674 496 × 2 = 1 + 0.976 155 348 992;
  • 49) 0.976 155 348 992 × 2 = 1 + 0.952 310 697 984;
  • 50) 0.952 310 697 984 × 2 = 1 + 0.904 621 395 968;
  • 51) 0.904 621 395 968 × 2 = 1 + 0.809 242 791 936;
  • 52) 0.809 242 791 936 × 2 = 1 + 0.618 485 583 872;
  • 53) 0.618 485 583 872 × 2 = 1 + 0.236 971 167 744;
  • 54) 0.236 971 167 744 × 2 = 0 + 0.473 942 335 488;
  • 55) 0.473 942 335 488 × 2 = 0 + 0.947 884 670 976;
  • 56) 0.947 884 670 976 × 2 = 1 + 0.895 769 341 952;
  • 57) 0.895 769 341 952 × 2 = 1 + 0.791 538 683 904;
  • 58) 0.791 538 683 904 × 2 = 1 + 0.583 077 367 808;
  • 59) 0.583 077 367 808 × 2 = 1 + 0.166 154 735 616;
  • 60) 0.166 154 735 616 × 2 = 0 + 0.332 309 471 232;
  • 61) 0.332 309 471 232 × 2 = 0 + 0.664 618 942 464;
  • 62) 0.664 618 942 464 × 2 = 1 + 0.329 237 884 928;
  • 63) 0.329 237 884 928 × 2 = 0 + 0.658 475 769 856;
  • 64) 0.658 475 769 856 × 2 = 1 + 0.316 951 539 712;

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:


0.000 282 005 532(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1000 1001 1000 0111 1111 1001 1110 0101(2)

6. Positive number before normalization:

0.000 282 005 532(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1000 1001 1000 0111 1111 1001 1110 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:


0.000 282 005 532(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1000 1001 1000 0111 1111 1001 1110 0101(2) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1000 1001 1000 0111 1111 1001 1110 0101(2) × 20 =


1.0010 0111 1011 0100 0100 1000 1001 1000 0111 1111 1001 1110 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 1001 1000 0111 1111 1001 1110 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 1001 1000 0111 1111 1001 1110 0101 =


0010 0111 1011 0100 0100 1000 1001 1000 0111 1111 1001 1110 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 1001 1000 0111 1111 1001 1110 0101


Decimal number -0.000 282 005 532 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0100 1000 1001 1000 0111 1111 1001 1110 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