-0.000 282 006 394 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 394(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
-0.000 282 006 394(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:

|-0.000 282 006 394| = 0.000 282 006 394


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: 0.000 282 006 394.

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) 0.000 282 006 394 × 2 = 0 + 0.000 564 012 788;
  • 2) 0.000 564 012 788 × 2 = 0 + 0.001 128 025 576;
  • 3) 0.001 128 025 576 × 2 = 0 + 0.002 256 051 152;
  • 4) 0.002 256 051 152 × 2 = 0 + 0.004 512 102 304;
  • 5) 0.004 512 102 304 × 2 = 0 + 0.009 024 204 608;
  • 6) 0.009 024 204 608 × 2 = 0 + 0.018 048 409 216;
  • 7) 0.018 048 409 216 × 2 = 0 + 0.036 096 818 432;
  • 8) 0.036 096 818 432 × 2 = 0 + 0.072 193 636 864;
  • 9) 0.072 193 636 864 × 2 = 0 + 0.144 387 273 728;
  • 10) 0.144 387 273 728 × 2 = 0 + 0.288 774 547 456;
  • 11) 0.288 774 547 456 × 2 = 0 + 0.577 549 094 912;
  • 12) 0.577 549 094 912 × 2 = 1 + 0.155 098 189 824;
  • 13) 0.155 098 189 824 × 2 = 0 + 0.310 196 379 648;
  • 14) 0.310 196 379 648 × 2 = 0 + 0.620 392 759 296;
  • 15) 0.620 392 759 296 × 2 = 1 + 0.240 785 518 592;
  • 16) 0.240 785 518 592 × 2 = 0 + 0.481 571 037 184;
  • 17) 0.481 571 037 184 × 2 = 0 + 0.963 142 074 368;
  • 18) 0.963 142 074 368 × 2 = 1 + 0.926 284 148 736;
  • 19) 0.926 284 148 736 × 2 = 1 + 0.852 568 297 472;
  • 20) 0.852 568 297 472 × 2 = 1 + 0.705 136 594 944;
  • 21) 0.705 136 594 944 × 2 = 1 + 0.410 273 189 888;
  • 22) 0.410 273 189 888 × 2 = 0 + 0.820 546 379 776;
  • 23) 0.820 546 379 776 × 2 = 1 + 0.641 092 759 552;
  • 24) 0.641 092 759 552 × 2 = 1 + 0.282 185 519 104;
  • 25) 0.282 185 519 104 × 2 = 0 + 0.564 371 038 208;
  • 26) 0.564 371 038 208 × 2 = 1 + 0.128 742 076 416;
  • 27) 0.128 742 076 416 × 2 = 0 + 0.257 484 152 832;
  • 28) 0.257 484 152 832 × 2 = 0 + 0.514 968 305 664;
  • 29) 0.514 968 305 664 × 2 = 1 + 0.029 936 611 328;
  • 30) 0.029 936 611 328 × 2 = 0 + 0.059 873 222 656;
  • 31) 0.059 873 222 656 × 2 = 0 + 0.119 746 445 312;
  • 32) 0.119 746 445 312 × 2 = 0 + 0.239 492 890 624;
  • 33) 0.239 492 890 624 × 2 = 0 + 0.478 985 781 248;
  • 34) 0.478 985 781 248 × 2 = 0 + 0.957 971 562 496;
  • 35) 0.957 971 562 496 × 2 = 1 + 0.915 943 124 992;
  • 36) 0.915 943 124 992 × 2 = 1 + 0.831 886 249 984;
  • 37) 0.831 886 249 984 × 2 = 1 + 0.663 772 499 968;
  • 38) 0.663 772 499 968 × 2 = 1 + 0.327 544 999 936;
  • 39) 0.327 544 999 936 × 2 = 0 + 0.655 089 999 872;
  • 40) 0.655 089 999 872 × 2 = 1 + 0.310 179 999 744;
  • 41) 0.310 179 999 744 × 2 = 0 + 0.620 359 999 488;
  • 42) 0.620 359 999 488 × 2 = 1 + 0.240 719 998 976;
  • 43) 0.240 719 998 976 × 2 = 0 + 0.481 439 997 952;
  • 44) 0.481 439 997 952 × 2 = 0 + 0.962 879 995 904;
  • 45) 0.962 879 995 904 × 2 = 1 + 0.925 759 991 808;
  • 46) 0.925 759 991 808 × 2 = 1 + 0.851 519 983 616;
  • 47) 0.851 519 983 616 × 2 = 1 + 0.703 039 967 232;
  • 48) 0.703 039 967 232 × 2 = 1 + 0.406 079 934 464;
  • 49) 0.406 079 934 464 × 2 = 0 + 0.812 159 868 928;
  • 50) 0.812 159 868 928 × 2 = 1 + 0.624 319 737 856;
  • 51) 0.624 319 737 856 × 2 = 1 + 0.248 639 475 712;
  • 52) 0.248 639 475 712 × 2 = 0 + 0.497 278 951 424;
  • 53) 0.497 278 951 424 × 2 = 0 + 0.994 557 902 848;
  • 54) 0.994 557 902 848 × 2 = 1 + 0.989 115 805 696;
  • 55) 0.989 115 805 696 × 2 = 1 + 0.978 231 611 392;
  • 56) 0.978 231 611 392 × 2 = 1 + 0.956 463 222 784;
  • 57) 0.956 463 222 784 × 2 = 1 + 0.912 926 445 568;
  • 58) 0.912 926 445 568 × 2 = 1 + 0.825 852 891 136;
  • 59) 0.825 852 891 136 × 2 = 1 + 0.651 705 782 272;
  • 60) 0.651 705 782 272 × 2 = 1 + 0.303 411 564 544;
  • 61) 0.303 411 564 544 × 2 = 0 + 0.606 823 129 088;
  • 62) 0.606 823 129 088 × 2 = 1 + 0.213 646 258 176;
  • 63) 0.213 646 258 176 × 2 = 0 + 0.427 292 516 352;
  • 64) 0.427 292 516 352 × 2 = 0 + 0.854 585 032 704;

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:


0.000 282 006 394(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0011 1101 0100 1111 0110 0111 1111 0100(2)

6. Positive number before normalization:

0.000 282 006 394(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0011 1101 0100 1111 0110 0111 1111 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:


0.000 282 006 394(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0011 1101 0100 1111 0110 0111 1111 0100(2) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0011 1101 0100 1111 0110 0111 1111 0100(2) × 20 =


1.0010 0111 1011 0100 1000 0011 1101 0100 1111 0110 0111 1111 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 1101 0100 1111 0110 0111 1111 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 1101 0100 1111 0110 0111 1111 0100 =


0010 0111 1011 0100 1000 0011 1101 0100 1111 0110 0111 1111 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 1101 0100 1111 0110 0111 1111 0100


Decimal number -0.000 282 006 394 converted to 64 bit double precision IEEE 754 binary floating point representation:

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