-0.000 282 005 972 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 972(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
-0.000 282 005 972(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:

|-0.000 282 005 972| = 0.000 282 005 972


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: 0.000 282 005 972.

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) 0.000 282 005 972 × 2 = 0 + 0.000 564 011 944;
  • 2) 0.000 564 011 944 × 2 = 0 + 0.001 128 023 888;
  • 3) 0.001 128 023 888 × 2 = 0 + 0.002 256 047 776;
  • 4) 0.002 256 047 776 × 2 = 0 + 0.004 512 095 552;
  • 5) 0.004 512 095 552 × 2 = 0 + 0.009 024 191 104;
  • 6) 0.009 024 191 104 × 2 = 0 + 0.018 048 382 208;
  • 7) 0.018 048 382 208 × 2 = 0 + 0.036 096 764 416;
  • 8) 0.036 096 764 416 × 2 = 0 + 0.072 193 528 832;
  • 9) 0.072 193 528 832 × 2 = 0 + 0.144 387 057 664;
  • 10) 0.144 387 057 664 × 2 = 0 + 0.288 774 115 328;
  • 11) 0.288 774 115 328 × 2 = 0 + 0.577 548 230 656;
  • 12) 0.577 548 230 656 × 2 = 1 + 0.155 096 461 312;
  • 13) 0.155 096 461 312 × 2 = 0 + 0.310 192 922 624;
  • 14) 0.310 192 922 624 × 2 = 0 + 0.620 385 845 248;
  • 15) 0.620 385 845 248 × 2 = 1 + 0.240 771 690 496;
  • 16) 0.240 771 690 496 × 2 = 0 + 0.481 543 380 992;
  • 17) 0.481 543 380 992 × 2 = 0 + 0.963 086 761 984;
  • 18) 0.963 086 761 984 × 2 = 1 + 0.926 173 523 968;
  • 19) 0.926 173 523 968 × 2 = 1 + 0.852 347 047 936;
  • 20) 0.852 347 047 936 × 2 = 1 + 0.704 694 095 872;
  • 21) 0.704 694 095 872 × 2 = 1 + 0.409 388 191 744;
  • 22) 0.409 388 191 744 × 2 = 0 + 0.818 776 383 488;
  • 23) 0.818 776 383 488 × 2 = 1 + 0.637 552 766 976;
  • 24) 0.637 552 766 976 × 2 = 1 + 0.275 105 533 952;
  • 25) 0.275 105 533 952 × 2 = 0 + 0.550 211 067 904;
  • 26) 0.550 211 067 904 × 2 = 1 + 0.100 422 135 808;
  • 27) 0.100 422 135 808 × 2 = 0 + 0.200 844 271 616;
  • 28) 0.200 844 271 616 × 2 = 0 + 0.401 688 543 232;
  • 29) 0.401 688 543 232 × 2 = 0 + 0.803 377 086 464;
  • 30) 0.803 377 086 464 × 2 = 1 + 0.606 754 172 928;
  • 31) 0.606 754 172 928 × 2 = 1 + 0.213 508 345 856;
  • 32) 0.213 508 345 856 × 2 = 0 + 0.427 016 691 712;
  • 33) 0.427 016 691 712 × 2 = 0 + 0.854 033 383 424;
  • 34) 0.854 033 383 424 × 2 = 1 + 0.708 066 766 848;
  • 35) 0.708 066 766 848 × 2 = 1 + 0.416 133 533 696;
  • 36) 0.416 133 533 696 × 2 = 0 + 0.832 267 067 392;
  • 37) 0.832 267 067 392 × 2 = 1 + 0.664 534 134 784;
  • 38) 0.664 534 134 784 × 2 = 1 + 0.329 068 269 568;
  • 39) 0.329 068 269 568 × 2 = 0 + 0.658 136 539 136;
  • 40) 0.658 136 539 136 × 2 = 1 + 0.316 273 078 272;
  • 41) 0.316 273 078 272 × 2 = 0 + 0.632 546 156 544;
  • 42) 0.632 546 156 544 × 2 = 1 + 0.265 092 313 088;
  • 43) 0.265 092 313 088 × 2 = 0 + 0.530 184 626 176;
  • 44) 0.530 184 626 176 × 2 = 1 + 0.060 369 252 352;
  • 45) 0.060 369 252 352 × 2 = 0 + 0.120 738 504 704;
  • 46) 0.120 738 504 704 × 2 = 0 + 0.241 477 009 408;
  • 47) 0.241 477 009 408 × 2 = 0 + 0.482 954 018 816;
  • 48) 0.482 954 018 816 × 2 = 0 + 0.965 908 037 632;
  • 49) 0.965 908 037 632 × 2 = 1 + 0.931 816 075 264;
  • 50) 0.931 816 075 264 × 2 = 1 + 0.863 632 150 528;
  • 51) 0.863 632 150 528 × 2 = 1 + 0.727 264 301 056;
  • 52) 0.727 264 301 056 × 2 = 1 + 0.454 528 602 112;
  • 53) 0.454 528 602 112 × 2 = 0 + 0.909 057 204 224;
  • 54) 0.909 057 204 224 × 2 = 1 + 0.818 114 408 448;
  • 55) 0.818 114 408 448 × 2 = 1 + 0.636 228 816 896;
  • 56) 0.636 228 816 896 × 2 = 1 + 0.272 457 633 792;
  • 57) 0.272 457 633 792 × 2 = 0 + 0.544 915 267 584;
  • 58) 0.544 915 267 584 × 2 = 1 + 0.089 830 535 168;
  • 59) 0.089 830 535 168 × 2 = 0 + 0.179 661 070 336;
  • 60) 0.179 661 070 336 × 2 = 0 + 0.359 322 140 672;
  • 61) 0.359 322 140 672 × 2 = 0 + 0.718 644 281 344;
  • 62) 0.718 644 281 344 × 2 = 1 + 0.437 288 562 688;
  • 63) 0.437 288 562 688 × 2 = 0 + 0.874 577 125 376;
  • 64) 0.874 577 125 376 × 2 = 1 + 0.749 154 250 752;

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:


0.000 282 005 972(10) =


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

6. Positive number before normalization:

0.000 282 005 972(10) =


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


0.000 282 005 972(10) =


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


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


1.0010 0111 1011 0100 0110 0110 1101 0101 0000 1111 0111 0100 0101(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 0110 1101 0101 0000 1111 0111 0100 0101


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 0110 1101 0101 0000 1111 0111 0100 0101 =


0010 0111 1011 0100 0110 0110 1101 0101 0000 1111 0111 0100 0101


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 0110 1101 0101 0000 1111 0111 0100 0101


Decimal number -0.000 282 005 972 converted to 64 bit double precision IEEE 754 binary floating point representation:

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


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