-0.000 282 005 791 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 791(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
-0.000 282 005 791(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:

|-0.000 282 005 791| = 0.000 282 005 791


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: 0.000 282 005 791.

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) 0.000 282 005 791 × 2 = 0 + 0.000 564 011 582;
  • 2) 0.000 564 011 582 × 2 = 0 + 0.001 128 023 164;
  • 3) 0.001 128 023 164 × 2 = 0 + 0.002 256 046 328;
  • 4) 0.002 256 046 328 × 2 = 0 + 0.004 512 092 656;
  • 5) 0.004 512 092 656 × 2 = 0 + 0.009 024 185 312;
  • 6) 0.009 024 185 312 × 2 = 0 + 0.018 048 370 624;
  • 7) 0.018 048 370 624 × 2 = 0 + 0.036 096 741 248;
  • 8) 0.036 096 741 248 × 2 = 0 + 0.072 193 482 496;
  • 9) 0.072 193 482 496 × 2 = 0 + 0.144 386 964 992;
  • 10) 0.144 386 964 992 × 2 = 0 + 0.288 773 929 984;
  • 11) 0.288 773 929 984 × 2 = 0 + 0.577 547 859 968;
  • 12) 0.577 547 859 968 × 2 = 1 + 0.155 095 719 936;
  • 13) 0.155 095 719 936 × 2 = 0 + 0.310 191 439 872;
  • 14) 0.310 191 439 872 × 2 = 0 + 0.620 382 879 744;
  • 15) 0.620 382 879 744 × 2 = 1 + 0.240 765 759 488;
  • 16) 0.240 765 759 488 × 2 = 0 + 0.481 531 518 976;
  • 17) 0.481 531 518 976 × 2 = 0 + 0.963 063 037 952;
  • 18) 0.963 063 037 952 × 2 = 1 + 0.926 126 075 904;
  • 19) 0.926 126 075 904 × 2 = 1 + 0.852 252 151 808;
  • 20) 0.852 252 151 808 × 2 = 1 + 0.704 504 303 616;
  • 21) 0.704 504 303 616 × 2 = 1 + 0.409 008 607 232;
  • 22) 0.409 008 607 232 × 2 = 0 + 0.818 017 214 464;
  • 23) 0.818 017 214 464 × 2 = 1 + 0.636 034 428 928;
  • 24) 0.636 034 428 928 × 2 = 1 + 0.272 068 857 856;
  • 25) 0.272 068 857 856 × 2 = 0 + 0.544 137 715 712;
  • 26) 0.544 137 715 712 × 2 = 1 + 0.088 275 431 424;
  • 27) 0.088 275 431 424 × 2 = 0 + 0.176 550 862 848;
  • 28) 0.176 550 862 848 × 2 = 0 + 0.353 101 725 696;
  • 29) 0.353 101 725 696 × 2 = 0 + 0.706 203 451 392;
  • 30) 0.706 203 451 392 × 2 = 1 + 0.412 406 902 784;
  • 31) 0.412 406 902 784 × 2 = 0 + 0.824 813 805 568;
  • 32) 0.824 813 805 568 × 2 = 1 + 0.649 627 611 136;
  • 33) 0.649 627 611 136 × 2 = 1 + 0.299 255 222 272;
  • 34) 0.299 255 222 272 × 2 = 0 + 0.598 510 444 544;
  • 35) 0.598 510 444 544 × 2 = 1 + 0.197 020 889 088;
  • 36) 0.197 020 889 088 × 2 = 0 + 0.394 041 778 176;
  • 37) 0.394 041 778 176 × 2 = 0 + 0.788 083 556 352;
  • 38) 0.788 083 556 352 × 2 = 1 + 0.576 167 112 704;
  • 39) 0.576 167 112 704 × 2 = 1 + 0.152 334 225 408;
  • 40) 0.152 334 225 408 × 2 = 0 + 0.304 668 450 816;
  • 41) 0.304 668 450 816 × 2 = 0 + 0.609 336 901 632;
  • 42) 0.609 336 901 632 × 2 = 1 + 0.218 673 803 264;
  • 43) 0.218 673 803 264 × 2 = 0 + 0.437 347 606 528;
  • 44) 0.437 347 606 528 × 2 = 0 + 0.874 695 213 056;
  • 45) 0.874 695 213 056 × 2 = 1 + 0.749 390 426 112;
  • 46) 0.749 390 426 112 × 2 = 1 + 0.498 780 852 224;
  • 47) 0.498 780 852 224 × 2 = 0 + 0.997 561 704 448;
  • 48) 0.997 561 704 448 × 2 = 1 + 0.995 123 408 896;
  • 49) 0.995 123 408 896 × 2 = 1 + 0.990 246 817 792;
  • 50) 0.990 246 817 792 × 2 = 1 + 0.980 493 635 584;
  • 51) 0.980 493 635 584 × 2 = 1 + 0.960 987 271 168;
  • 52) 0.960 987 271 168 × 2 = 1 + 0.921 974 542 336;
  • 53) 0.921 974 542 336 × 2 = 1 + 0.843 949 084 672;
  • 54) 0.843 949 084 672 × 2 = 1 + 0.687 898 169 344;
  • 55) 0.687 898 169 344 × 2 = 1 + 0.375 796 338 688;
  • 56) 0.375 796 338 688 × 2 = 0 + 0.751 592 677 376;
  • 57) 0.751 592 677 376 × 2 = 1 + 0.503 185 354 752;
  • 58) 0.503 185 354 752 × 2 = 1 + 0.006 370 709 504;
  • 59) 0.006 370 709 504 × 2 = 0 + 0.012 741 419 008;
  • 60) 0.012 741 419 008 × 2 = 0 + 0.025 482 838 016;
  • 61) 0.025 482 838 016 × 2 = 0 + 0.050 965 676 032;
  • 62) 0.050 965 676 032 × 2 = 0 + 0.101 931 352 064;
  • 63) 0.101 931 352 064 × 2 = 0 + 0.203 862 704 128;
  • 64) 0.203 862 704 128 × 2 = 0 + 0.407 725 408 256;

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:


0.000 282 005 791(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1010 0110 0100 1101 1111 1110 1100 0000(2)

6. Positive number before normalization:

0.000 282 005 791(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1010 0110 0100 1101 1111 1110 1100 0000(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:


0.000 282 005 791(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1010 0110 0100 1101 1111 1110 1100 0000(2) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1010 0110 0100 1101 1111 1110 1100 0000(2) × 20 =


1.0010 0111 1011 0100 0101 1010 0110 0100 1101 1111 1110 1100 0000(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 0101 1010 0110 0100 1101 1111 1110 1100 0000


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 0101 1010 0110 0100 1101 1111 1110 1100 0000 =


0010 0111 1011 0100 0101 1010 0110 0100 1101 1111 1110 1100 0000


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 0101 1010 0110 0100 1101 1111 1110 1100 0000


Decimal number -0.000 282 005 791 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0101 1010 0110 0100 1101 1111 1110 1100 0000


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