-0.000 282 006 388 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 388(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
-0.000 282 006 388(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:

|-0.000 282 006 388| = 0.000 282 006 388


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: 0.000 282 006 388.

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) 0.000 282 006 388 × 2 = 0 + 0.000 564 012 776;
  • 2) 0.000 564 012 776 × 2 = 0 + 0.001 128 025 552;
  • 3) 0.001 128 025 552 × 2 = 0 + 0.002 256 051 104;
  • 4) 0.002 256 051 104 × 2 = 0 + 0.004 512 102 208;
  • 5) 0.004 512 102 208 × 2 = 0 + 0.009 024 204 416;
  • 6) 0.009 024 204 416 × 2 = 0 + 0.018 048 408 832;
  • 7) 0.018 048 408 832 × 2 = 0 + 0.036 096 817 664;
  • 8) 0.036 096 817 664 × 2 = 0 + 0.072 193 635 328;
  • 9) 0.072 193 635 328 × 2 = 0 + 0.144 387 270 656;
  • 10) 0.144 387 270 656 × 2 = 0 + 0.288 774 541 312;
  • 11) 0.288 774 541 312 × 2 = 0 + 0.577 549 082 624;
  • 12) 0.577 549 082 624 × 2 = 1 + 0.155 098 165 248;
  • 13) 0.155 098 165 248 × 2 = 0 + 0.310 196 330 496;
  • 14) 0.310 196 330 496 × 2 = 0 + 0.620 392 660 992;
  • 15) 0.620 392 660 992 × 2 = 1 + 0.240 785 321 984;
  • 16) 0.240 785 321 984 × 2 = 0 + 0.481 570 643 968;
  • 17) 0.481 570 643 968 × 2 = 0 + 0.963 141 287 936;
  • 18) 0.963 141 287 936 × 2 = 1 + 0.926 282 575 872;
  • 19) 0.926 282 575 872 × 2 = 1 + 0.852 565 151 744;
  • 20) 0.852 565 151 744 × 2 = 1 + 0.705 130 303 488;
  • 21) 0.705 130 303 488 × 2 = 1 + 0.410 260 606 976;
  • 22) 0.410 260 606 976 × 2 = 0 + 0.820 521 213 952;
  • 23) 0.820 521 213 952 × 2 = 1 + 0.641 042 427 904;
  • 24) 0.641 042 427 904 × 2 = 1 + 0.282 084 855 808;
  • 25) 0.282 084 855 808 × 2 = 0 + 0.564 169 711 616;
  • 26) 0.564 169 711 616 × 2 = 1 + 0.128 339 423 232;
  • 27) 0.128 339 423 232 × 2 = 0 + 0.256 678 846 464;
  • 28) 0.256 678 846 464 × 2 = 0 + 0.513 357 692 928;
  • 29) 0.513 357 692 928 × 2 = 1 + 0.026 715 385 856;
  • 30) 0.026 715 385 856 × 2 = 0 + 0.053 430 771 712;
  • 31) 0.053 430 771 712 × 2 = 0 + 0.106 861 543 424;
  • 32) 0.106 861 543 424 × 2 = 0 + 0.213 723 086 848;
  • 33) 0.213 723 086 848 × 2 = 0 + 0.427 446 173 696;
  • 34) 0.427 446 173 696 × 2 = 0 + 0.854 892 347 392;
  • 35) 0.854 892 347 392 × 2 = 1 + 0.709 784 694 784;
  • 36) 0.709 784 694 784 × 2 = 1 + 0.419 569 389 568;
  • 37) 0.419 569 389 568 × 2 = 0 + 0.839 138 779 136;
  • 38) 0.839 138 779 136 × 2 = 1 + 0.678 277 558 272;
  • 39) 0.678 277 558 272 × 2 = 1 + 0.356 555 116 544;
  • 40) 0.356 555 116 544 × 2 = 0 + 0.713 110 233 088;
  • 41) 0.713 110 233 088 × 2 = 1 + 0.426 220 466 176;
  • 42) 0.426 220 466 176 × 2 = 0 + 0.852 440 932 352;
  • 43) 0.852 440 932 352 × 2 = 1 + 0.704 881 864 704;
  • 44) 0.704 881 864 704 × 2 = 1 + 0.409 763 729 408;
  • 45) 0.409 763 729 408 × 2 = 0 + 0.819 527 458 816;
  • 46) 0.819 527 458 816 × 2 = 1 + 0.639 054 917 632;
  • 47) 0.639 054 917 632 × 2 = 1 + 0.278 109 835 264;
  • 48) 0.278 109 835 264 × 2 = 0 + 0.556 219 670 528;
  • 49) 0.556 219 670 528 × 2 = 1 + 0.112 439 341 056;
  • 50) 0.112 439 341 056 × 2 = 0 + 0.224 878 682 112;
  • 51) 0.224 878 682 112 × 2 = 0 + 0.449 757 364 224;
  • 52) 0.449 757 364 224 × 2 = 0 + 0.899 514 728 448;
  • 53) 0.899 514 728 448 × 2 = 1 + 0.799 029 456 896;
  • 54) 0.799 029 456 896 × 2 = 1 + 0.598 058 913 792;
  • 55) 0.598 058 913 792 × 2 = 1 + 0.196 117 827 584;
  • 56) 0.196 117 827 584 × 2 = 0 + 0.392 235 655 168;
  • 57) 0.392 235 655 168 × 2 = 0 + 0.784 471 310 336;
  • 58) 0.784 471 310 336 × 2 = 1 + 0.568 942 620 672;
  • 59) 0.568 942 620 672 × 2 = 1 + 0.137 885 241 344;
  • 60) 0.137 885 241 344 × 2 = 0 + 0.275 770 482 688;
  • 61) 0.275 770 482 688 × 2 = 0 + 0.551 540 965 376;
  • 62) 0.551 540 965 376 × 2 = 1 + 0.103 081 930 752;
  • 63) 0.103 081 930 752 × 2 = 0 + 0.206 163 861 504;
  • 64) 0.206 163 861 504 × 2 = 0 + 0.412 327 723 008;

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:


0.000 282 006 388(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0011 0110 1011 0110 1000 1110 0110 0100(2)

6. Positive number before normalization:

0.000 282 006 388(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0011 0110 1011 0110 1000 1110 0110 0100(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:


0.000 282 006 388(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0011 0110 1011 0110 1000 1110 0110 0100(2) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0011 0110 1011 0110 1000 1110 0110 0100(2) × 20 =


1.0010 0111 1011 0100 1000 0011 0110 1011 0110 1000 1110 0110 0100(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 1000 0011 0110 1011 0110 1000 1110 0110 0100


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 1000 0011 0110 1011 0110 1000 1110 0110 0100 =


0010 0111 1011 0100 1000 0011 0110 1011 0110 1000 1110 0110 0100


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 1000 0011 0110 1011 0110 1000 1110 0110 0100


Decimal number -0.000 282 006 388 converted to 64 bit double precision IEEE 754 binary floating point representation:

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


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