-0.000 282 005 979 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 979(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
-0.000 282 005 979(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:

|-0.000 282 005 979| = 0.000 282 005 979


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: 0.000 282 005 979.

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) 0.000 282 005 979 × 2 = 0 + 0.000 564 011 958;
  • 2) 0.000 564 011 958 × 2 = 0 + 0.001 128 023 916;
  • 3) 0.001 128 023 916 × 2 = 0 + 0.002 256 047 832;
  • 4) 0.002 256 047 832 × 2 = 0 + 0.004 512 095 664;
  • 5) 0.004 512 095 664 × 2 = 0 + 0.009 024 191 328;
  • 6) 0.009 024 191 328 × 2 = 0 + 0.018 048 382 656;
  • 7) 0.018 048 382 656 × 2 = 0 + 0.036 096 765 312;
  • 8) 0.036 096 765 312 × 2 = 0 + 0.072 193 530 624;
  • 9) 0.072 193 530 624 × 2 = 0 + 0.144 387 061 248;
  • 10) 0.144 387 061 248 × 2 = 0 + 0.288 774 122 496;
  • 11) 0.288 774 122 496 × 2 = 0 + 0.577 548 244 992;
  • 12) 0.577 548 244 992 × 2 = 1 + 0.155 096 489 984;
  • 13) 0.155 096 489 984 × 2 = 0 + 0.310 192 979 968;
  • 14) 0.310 192 979 968 × 2 = 0 + 0.620 385 959 936;
  • 15) 0.620 385 959 936 × 2 = 1 + 0.240 771 919 872;
  • 16) 0.240 771 919 872 × 2 = 0 + 0.481 543 839 744;
  • 17) 0.481 543 839 744 × 2 = 0 + 0.963 087 679 488;
  • 18) 0.963 087 679 488 × 2 = 1 + 0.926 175 358 976;
  • 19) 0.926 175 358 976 × 2 = 1 + 0.852 350 717 952;
  • 20) 0.852 350 717 952 × 2 = 1 + 0.704 701 435 904;
  • 21) 0.704 701 435 904 × 2 = 1 + 0.409 402 871 808;
  • 22) 0.409 402 871 808 × 2 = 0 + 0.818 805 743 616;
  • 23) 0.818 805 743 616 × 2 = 1 + 0.637 611 487 232;
  • 24) 0.637 611 487 232 × 2 = 1 + 0.275 222 974 464;
  • 25) 0.275 222 974 464 × 2 = 0 + 0.550 445 948 928;
  • 26) 0.550 445 948 928 × 2 = 1 + 0.100 891 897 856;
  • 27) 0.100 891 897 856 × 2 = 0 + 0.201 783 795 712;
  • 28) 0.201 783 795 712 × 2 = 0 + 0.403 567 591 424;
  • 29) 0.403 567 591 424 × 2 = 0 + 0.807 135 182 848;
  • 30) 0.807 135 182 848 × 2 = 1 + 0.614 270 365 696;
  • 31) 0.614 270 365 696 × 2 = 1 + 0.228 540 731 392;
  • 32) 0.228 540 731 392 × 2 = 0 + 0.457 081 462 784;
  • 33) 0.457 081 462 784 × 2 = 0 + 0.914 162 925 568;
  • 34) 0.914 162 925 568 × 2 = 1 + 0.828 325 851 136;
  • 35) 0.828 325 851 136 × 2 = 1 + 0.656 651 702 272;
  • 36) 0.656 651 702 272 × 2 = 1 + 0.313 303 404 544;
  • 37) 0.313 303 404 544 × 2 = 0 + 0.626 606 809 088;
  • 38) 0.626 606 809 088 × 2 = 1 + 0.253 213 618 176;
  • 39) 0.253 213 618 176 × 2 = 0 + 0.506 427 236 352;
  • 40) 0.506 427 236 352 × 2 = 1 + 0.012 854 472 704;
  • 41) 0.012 854 472 704 × 2 = 0 + 0.025 708 945 408;
  • 42) 0.025 708 945 408 × 2 = 0 + 0.051 417 890 816;
  • 43) 0.051 417 890 816 × 2 = 0 + 0.102 835 781 632;
  • 44) 0.102 835 781 632 × 2 = 0 + 0.205 671 563 264;
  • 45) 0.205 671 563 264 × 2 = 0 + 0.411 343 126 528;
  • 46) 0.411 343 126 528 × 2 = 0 + 0.822 686 253 056;
  • 47) 0.822 686 253 056 × 2 = 1 + 0.645 372 506 112;
  • 48) 0.645 372 506 112 × 2 = 1 + 0.290 745 012 224;
  • 49) 0.290 745 012 224 × 2 = 0 + 0.581 490 024 448;
  • 50) 0.581 490 024 448 × 2 = 1 + 0.162 980 048 896;
  • 51) 0.162 980 048 896 × 2 = 0 + 0.325 960 097 792;
  • 52) 0.325 960 097 792 × 2 = 0 + 0.651 920 195 584;
  • 53) 0.651 920 195 584 × 2 = 1 + 0.303 840 391 168;
  • 54) 0.303 840 391 168 × 2 = 0 + 0.607 680 782 336;
  • 55) 0.607 680 782 336 × 2 = 1 + 0.215 361 564 672;
  • 56) 0.215 361 564 672 × 2 = 0 + 0.430 723 129 344;
  • 57) 0.430 723 129 344 × 2 = 0 + 0.861 446 258 688;
  • 58) 0.861 446 258 688 × 2 = 1 + 0.722 892 517 376;
  • 59) 0.722 892 517 376 × 2 = 1 + 0.445 785 034 752;
  • 60) 0.445 785 034 752 × 2 = 0 + 0.891 570 069 504;
  • 61) 0.891 570 069 504 × 2 = 1 + 0.783 140 139 008;
  • 62) 0.783 140 139 008 × 2 = 1 + 0.566 280 278 016;
  • 63) 0.566 280 278 016 × 2 = 1 + 0.132 560 556 032;
  • 64) 0.132 560 556 032 × 2 = 0 + 0.265 121 112 064;

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:


0.000 282 005 979(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0111 0101 0000 0011 0100 1010 0110 1110(2)

6. Positive number before normalization:

0.000 282 005 979(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0111 0101 0000 0011 0100 1010 0110 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:


0.000 282 005 979(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0111 0101 0000 0011 0100 1010 0110 1110(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0111 0101 0000 0011 0100 1010 0110 1110(2) × 20 =


1.0010 0111 1011 0100 0110 0111 0101 0000 0011 0100 1010 0110 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 0101 0000 0011 0100 1010 0110 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 0101 0000 0011 0100 1010 0110 1110 =


0010 0111 1011 0100 0110 0111 0101 0000 0011 0100 1010 0110 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 0101 0000 0011 0100 1010 0110 1110


Decimal number -0.000 282 005 979 converted to 64 bit double precision IEEE 754 binary floating point representation:

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