-0.000 282 005 987 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 987(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
-0.000 282 005 987(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:

|-0.000 282 005 987| = 0.000 282 005 987


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: 0.000 282 005 987.

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) 0.000 282 005 987 × 2 = 0 + 0.000 564 011 974;
  • 2) 0.000 564 011 974 × 2 = 0 + 0.001 128 023 948;
  • 3) 0.001 128 023 948 × 2 = 0 + 0.002 256 047 896;
  • 4) 0.002 256 047 896 × 2 = 0 + 0.004 512 095 792;
  • 5) 0.004 512 095 792 × 2 = 0 + 0.009 024 191 584;
  • 6) 0.009 024 191 584 × 2 = 0 + 0.018 048 383 168;
  • 7) 0.018 048 383 168 × 2 = 0 + 0.036 096 766 336;
  • 8) 0.036 096 766 336 × 2 = 0 + 0.072 193 532 672;
  • 9) 0.072 193 532 672 × 2 = 0 + 0.144 387 065 344;
  • 10) 0.144 387 065 344 × 2 = 0 + 0.288 774 130 688;
  • 11) 0.288 774 130 688 × 2 = 0 + 0.577 548 261 376;
  • 12) 0.577 548 261 376 × 2 = 1 + 0.155 096 522 752;
  • 13) 0.155 096 522 752 × 2 = 0 + 0.310 193 045 504;
  • 14) 0.310 193 045 504 × 2 = 0 + 0.620 386 091 008;
  • 15) 0.620 386 091 008 × 2 = 1 + 0.240 772 182 016;
  • 16) 0.240 772 182 016 × 2 = 0 + 0.481 544 364 032;
  • 17) 0.481 544 364 032 × 2 = 0 + 0.963 088 728 064;
  • 18) 0.963 088 728 064 × 2 = 1 + 0.926 177 456 128;
  • 19) 0.926 177 456 128 × 2 = 1 + 0.852 354 912 256;
  • 20) 0.852 354 912 256 × 2 = 1 + 0.704 709 824 512;
  • 21) 0.704 709 824 512 × 2 = 1 + 0.409 419 649 024;
  • 22) 0.409 419 649 024 × 2 = 0 + 0.818 839 298 048;
  • 23) 0.818 839 298 048 × 2 = 1 + 0.637 678 596 096;
  • 24) 0.637 678 596 096 × 2 = 1 + 0.275 357 192 192;
  • 25) 0.275 357 192 192 × 2 = 0 + 0.550 714 384 384;
  • 26) 0.550 714 384 384 × 2 = 1 + 0.101 428 768 768;
  • 27) 0.101 428 768 768 × 2 = 0 + 0.202 857 537 536;
  • 28) 0.202 857 537 536 × 2 = 0 + 0.405 715 075 072;
  • 29) 0.405 715 075 072 × 2 = 0 + 0.811 430 150 144;
  • 30) 0.811 430 150 144 × 2 = 1 + 0.622 860 300 288;
  • 31) 0.622 860 300 288 × 2 = 1 + 0.245 720 600 576;
  • 32) 0.245 720 600 576 × 2 = 0 + 0.491 441 201 152;
  • 33) 0.491 441 201 152 × 2 = 0 + 0.982 882 402 304;
  • 34) 0.982 882 402 304 × 2 = 1 + 0.965 764 804 608;
  • 35) 0.965 764 804 608 × 2 = 1 + 0.931 529 609 216;
  • 36) 0.931 529 609 216 × 2 = 1 + 0.863 059 218 432;
  • 37) 0.863 059 218 432 × 2 = 1 + 0.726 118 436 864;
  • 38) 0.726 118 436 864 × 2 = 1 + 0.452 236 873 728;
  • 39) 0.452 236 873 728 × 2 = 0 + 0.904 473 747 456;
  • 40) 0.904 473 747 456 × 2 = 1 + 0.808 947 494 912;
  • 41) 0.808 947 494 912 × 2 = 1 + 0.617 894 989 824;
  • 42) 0.617 894 989 824 × 2 = 1 + 0.235 789 979 648;
  • 43) 0.235 789 979 648 × 2 = 0 + 0.471 579 959 296;
  • 44) 0.471 579 959 296 × 2 = 0 + 0.943 159 918 592;
  • 45) 0.943 159 918 592 × 2 = 1 + 0.886 319 837 184;
  • 46) 0.886 319 837 184 × 2 = 1 + 0.772 639 674 368;
  • 47) 0.772 639 674 368 × 2 = 1 + 0.545 279 348 736;
  • 48) 0.545 279 348 736 × 2 = 1 + 0.090 558 697 472;
  • 49) 0.090 558 697 472 × 2 = 0 + 0.181 117 394 944;
  • 50) 0.181 117 394 944 × 2 = 0 + 0.362 234 789 888;
  • 51) 0.362 234 789 888 × 2 = 0 + 0.724 469 579 776;
  • 52) 0.724 469 579 776 × 2 = 1 + 0.448 939 159 552;
  • 53) 0.448 939 159 552 × 2 = 0 + 0.897 878 319 104;
  • 54) 0.897 878 319 104 × 2 = 1 + 0.795 756 638 208;
  • 55) 0.795 756 638 208 × 2 = 1 + 0.591 513 276 416;
  • 56) 0.591 513 276 416 × 2 = 1 + 0.183 026 552 832;
  • 57) 0.183 026 552 832 × 2 = 0 + 0.366 053 105 664;
  • 58) 0.366 053 105 664 × 2 = 0 + 0.732 106 211 328;
  • 59) 0.732 106 211 328 × 2 = 1 + 0.464 212 422 656;
  • 60) 0.464 212 422 656 × 2 = 0 + 0.928 424 845 312;
  • 61) 0.928 424 845 312 × 2 = 1 + 0.856 849 690 624;
  • 62) 0.856 849 690 624 × 2 = 1 + 0.713 699 381 248;
  • 63) 0.713 699 381 248 × 2 = 1 + 0.427 398 762 496;
  • 64) 0.427 398 762 496 × 2 = 0 + 0.854 797 524 992;

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:


0.000 282 005 987(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0111 1101 1100 1111 0001 0111 0010 1110(2)

6. Positive number before normalization:

0.000 282 005 987(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0111 1101 1100 1111 0001 0111 0010 1110(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:


0.000 282 005 987(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0111 1101 1100 1111 0001 0111 0010 1110(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0111 1101 1100 1111 0001 0111 0010 1110(2) × 20 =


1.0010 0111 1011 0100 0110 0111 1101 1100 1111 0001 0111 0010 1110(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 0111 1101 1100 1111 0001 0111 0010 1110


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 0111 1101 1100 1111 0001 0111 0010 1110 =


0010 0111 1011 0100 0110 0111 1101 1100 1111 0001 0111 0010 1110


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 0111 1101 1100 1111 0001 0111 0010 1110


Decimal number -0.000 282 005 987 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0111 1101 1100 1111 0001 0111 0010 1110


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