-0.000 282 006 351 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 351(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
-0.000 282 006 351(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:

|-0.000 282 006 351| = 0.000 282 006 351


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: 0.000 282 006 351.

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) 0.000 282 006 351 × 2 = 0 + 0.000 564 012 702;
  • 2) 0.000 564 012 702 × 2 = 0 + 0.001 128 025 404;
  • 3) 0.001 128 025 404 × 2 = 0 + 0.002 256 050 808;
  • 4) 0.002 256 050 808 × 2 = 0 + 0.004 512 101 616;
  • 5) 0.004 512 101 616 × 2 = 0 + 0.009 024 203 232;
  • 6) 0.009 024 203 232 × 2 = 0 + 0.018 048 406 464;
  • 7) 0.018 048 406 464 × 2 = 0 + 0.036 096 812 928;
  • 8) 0.036 096 812 928 × 2 = 0 + 0.072 193 625 856;
  • 9) 0.072 193 625 856 × 2 = 0 + 0.144 387 251 712;
  • 10) 0.144 387 251 712 × 2 = 0 + 0.288 774 503 424;
  • 11) 0.288 774 503 424 × 2 = 0 + 0.577 549 006 848;
  • 12) 0.577 549 006 848 × 2 = 1 + 0.155 098 013 696;
  • 13) 0.155 098 013 696 × 2 = 0 + 0.310 196 027 392;
  • 14) 0.310 196 027 392 × 2 = 0 + 0.620 392 054 784;
  • 15) 0.620 392 054 784 × 2 = 1 + 0.240 784 109 568;
  • 16) 0.240 784 109 568 × 2 = 0 + 0.481 568 219 136;
  • 17) 0.481 568 219 136 × 2 = 0 + 0.963 136 438 272;
  • 18) 0.963 136 438 272 × 2 = 1 + 0.926 272 876 544;
  • 19) 0.926 272 876 544 × 2 = 1 + 0.852 545 753 088;
  • 20) 0.852 545 753 088 × 2 = 1 + 0.705 091 506 176;
  • 21) 0.705 091 506 176 × 2 = 1 + 0.410 183 012 352;
  • 22) 0.410 183 012 352 × 2 = 0 + 0.820 366 024 704;
  • 23) 0.820 366 024 704 × 2 = 1 + 0.640 732 049 408;
  • 24) 0.640 732 049 408 × 2 = 1 + 0.281 464 098 816;
  • 25) 0.281 464 098 816 × 2 = 0 + 0.562 928 197 632;
  • 26) 0.562 928 197 632 × 2 = 1 + 0.125 856 395 264;
  • 27) 0.125 856 395 264 × 2 = 0 + 0.251 712 790 528;
  • 28) 0.251 712 790 528 × 2 = 0 + 0.503 425 581 056;
  • 29) 0.503 425 581 056 × 2 = 1 + 0.006 851 162 112;
  • 30) 0.006 851 162 112 × 2 = 0 + 0.013 702 324 224;
  • 31) 0.013 702 324 224 × 2 = 0 + 0.027 404 648 448;
  • 32) 0.027 404 648 448 × 2 = 0 + 0.054 809 296 896;
  • 33) 0.054 809 296 896 × 2 = 0 + 0.109 618 593 792;
  • 34) 0.109 618 593 792 × 2 = 0 + 0.219 237 187 584;
  • 35) 0.219 237 187 584 × 2 = 0 + 0.438 474 375 168;
  • 36) 0.438 474 375 168 × 2 = 0 + 0.876 948 750 336;
  • 37) 0.876 948 750 336 × 2 = 1 + 0.753 897 500 672;
  • 38) 0.753 897 500 672 × 2 = 1 + 0.507 795 001 344;
  • 39) 0.507 795 001 344 × 2 = 1 + 0.015 590 002 688;
  • 40) 0.015 590 002 688 × 2 = 0 + 0.031 180 005 376;
  • 41) 0.031 180 005 376 × 2 = 0 + 0.062 360 010 752;
  • 42) 0.062 360 010 752 × 2 = 0 + 0.124 720 021 504;
  • 43) 0.124 720 021 504 × 2 = 0 + 0.249 440 043 008;
  • 44) 0.249 440 043 008 × 2 = 0 + 0.498 880 086 016;
  • 45) 0.498 880 086 016 × 2 = 0 + 0.997 760 172 032;
  • 46) 0.997 760 172 032 × 2 = 1 + 0.995 520 344 064;
  • 47) 0.995 520 344 064 × 2 = 1 + 0.991 040 688 128;
  • 48) 0.991 040 688 128 × 2 = 1 + 0.982 081 376 256;
  • 49) 0.982 081 376 256 × 2 = 1 + 0.964 162 752 512;
  • 50) 0.964 162 752 512 × 2 = 1 + 0.928 325 505 024;
  • 51) 0.928 325 505 024 × 2 = 1 + 0.856 651 010 048;
  • 52) 0.856 651 010 048 × 2 = 1 + 0.713 302 020 096;
  • 53) 0.713 302 020 096 × 2 = 1 + 0.426 604 040 192;
  • 54) 0.426 604 040 192 × 2 = 0 + 0.853 208 080 384;
  • 55) 0.853 208 080 384 × 2 = 1 + 0.706 416 160 768;
  • 56) 0.706 416 160 768 × 2 = 1 + 0.412 832 321 536;
  • 57) 0.412 832 321 536 × 2 = 0 + 0.825 664 643 072;
  • 58) 0.825 664 643 072 × 2 = 1 + 0.651 329 286 144;
  • 59) 0.651 329 286 144 × 2 = 1 + 0.302 658 572 288;
  • 60) 0.302 658 572 288 × 2 = 0 + 0.605 317 144 576;
  • 61) 0.605 317 144 576 × 2 = 1 + 0.210 634 289 152;
  • 62) 0.210 634 289 152 × 2 = 0 + 0.421 268 578 304;
  • 63) 0.421 268 578 304 × 2 = 0 + 0.842 537 156 608;
  • 64) 0.842 537 156 608 × 2 = 1 + 0.685 074 313 216;

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:


0.000 282 006 351(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0000 1110 0000 0111 1111 1011 0110 1001(2)

6. Positive number before normalization:

0.000 282 006 351(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0000 1110 0000 0111 1111 1011 0110 1001(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:


0.000 282 006 351(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0000 1110 0000 0111 1111 1011 0110 1001(2) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0000 1110 0000 0111 1111 1011 0110 1001(2) × 20 =


1.0010 0111 1011 0100 1000 0000 1110 0000 0111 1111 1011 0110 1001(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 0000 1110 0000 0111 1111 1011 0110 1001


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 0000 1110 0000 0111 1111 1011 0110 1001 =


0010 0111 1011 0100 1000 0000 1110 0000 0111 1111 1011 0110 1001


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 0000 1110 0000 0111 1111 1011 0110 1001


Decimal number -0.000 282 006 351 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 1000 0000 1110 0000 0111 1111 1011 0110 1001


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