-0.000 282 005 557 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 557(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
-0.000 282 005 557(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:

|-0.000 282 005 557| = 0.000 282 005 557


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: 0.000 282 005 557.

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) 0.000 282 005 557 × 2 = 0 + 0.000 564 011 114;
  • 2) 0.000 564 011 114 × 2 = 0 + 0.001 128 022 228;
  • 3) 0.001 128 022 228 × 2 = 0 + 0.002 256 044 456;
  • 4) 0.002 256 044 456 × 2 = 0 + 0.004 512 088 912;
  • 5) 0.004 512 088 912 × 2 = 0 + 0.009 024 177 824;
  • 6) 0.009 024 177 824 × 2 = 0 + 0.018 048 355 648;
  • 7) 0.018 048 355 648 × 2 = 0 + 0.036 096 711 296;
  • 8) 0.036 096 711 296 × 2 = 0 + 0.072 193 422 592;
  • 9) 0.072 193 422 592 × 2 = 0 + 0.144 386 845 184;
  • 10) 0.144 386 845 184 × 2 = 0 + 0.288 773 690 368;
  • 11) 0.288 773 690 368 × 2 = 0 + 0.577 547 380 736;
  • 12) 0.577 547 380 736 × 2 = 1 + 0.155 094 761 472;
  • 13) 0.155 094 761 472 × 2 = 0 + 0.310 189 522 944;
  • 14) 0.310 189 522 944 × 2 = 0 + 0.620 379 045 888;
  • 15) 0.620 379 045 888 × 2 = 1 + 0.240 758 091 776;
  • 16) 0.240 758 091 776 × 2 = 0 + 0.481 516 183 552;
  • 17) 0.481 516 183 552 × 2 = 0 + 0.963 032 367 104;
  • 18) 0.963 032 367 104 × 2 = 1 + 0.926 064 734 208;
  • 19) 0.926 064 734 208 × 2 = 1 + 0.852 129 468 416;
  • 20) 0.852 129 468 416 × 2 = 1 + 0.704 258 936 832;
  • 21) 0.704 258 936 832 × 2 = 1 + 0.408 517 873 664;
  • 22) 0.408 517 873 664 × 2 = 0 + 0.817 035 747 328;
  • 23) 0.817 035 747 328 × 2 = 1 + 0.634 071 494 656;
  • 24) 0.634 071 494 656 × 2 = 1 + 0.268 142 989 312;
  • 25) 0.268 142 989 312 × 2 = 0 + 0.536 285 978 624;
  • 26) 0.536 285 978 624 × 2 = 1 + 0.072 571 957 248;
  • 27) 0.072 571 957 248 × 2 = 0 + 0.145 143 914 496;
  • 28) 0.145 143 914 496 × 2 = 0 + 0.290 287 828 992;
  • 29) 0.290 287 828 992 × 2 = 0 + 0.580 575 657 984;
  • 30) 0.580 575 657 984 × 2 = 1 + 0.161 151 315 968;
  • 31) 0.161 151 315 968 × 2 = 0 + 0.322 302 631 936;
  • 32) 0.322 302 631 936 × 2 = 0 + 0.644 605 263 872;
  • 33) 0.644 605 263 872 × 2 = 1 + 0.289 210 527 744;
  • 34) 0.289 210 527 744 × 2 = 0 + 0.578 421 055 488;
  • 35) 0.578 421 055 488 × 2 = 1 + 0.156 842 110 976;
  • 36) 0.156 842 110 976 × 2 = 0 + 0.313 684 221 952;
  • 37) 0.313 684 221 952 × 2 = 0 + 0.627 368 443 904;
  • 38) 0.627 368 443 904 × 2 = 1 + 0.254 736 887 808;
  • 39) 0.254 736 887 808 × 2 = 0 + 0.509 473 775 616;
  • 40) 0.509 473 775 616 × 2 = 1 + 0.018 947 551 232;
  • 41) 0.018 947 551 232 × 2 = 0 + 0.037 895 102 464;
  • 42) 0.037 895 102 464 × 2 = 0 + 0.075 790 204 928;
  • 43) 0.075 790 204 928 × 2 = 0 + 0.151 580 409 856;
  • 44) 0.151 580 409 856 × 2 = 0 + 0.303 160 819 712;
  • 45) 0.303 160 819 712 × 2 = 0 + 0.606 321 639 424;
  • 46) 0.606 321 639 424 × 2 = 1 + 0.212 643 278 848;
  • 47) 0.212 643 278 848 × 2 = 0 + 0.425 286 557 696;
  • 48) 0.425 286 557 696 × 2 = 0 + 0.850 573 115 392;
  • 49) 0.850 573 115 392 × 2 = 1 + 0.701 146 230 784;
  • 50) 0.701 146 230 784 × 2 = 1 + 0.402 292 461 568;
  • 51) 0.402 292 461 568 × 2 = 0 + 0.804 584 923 136;
  • 52) 0.804 584 923 136 × 2 = 1 + 0.609 169 846 272;
  • 53) 0.609 169 846 272 × 2 = 1 + 0.218 339 692 544;
  • 54) 0.218 339 692 544 × 2 = 0 + 0.436 679 385 088;
  • 55) 0.436 679 385 088 × 2 = 0 + 0.873 358 770 176;
  • 56) 0.873 358 770 176 × 2 = 1 + 0.746 717 540 352;
  • 57) 0.746 717 540 352 × 2 = 1 + 0.493 435 080 704;
  • 58) 0.493 435 080 704 × 2 = 0 + 0.986 870 161 408;
  • 59) 0.986 870 161 408 × 2 = 1 + 0.973 740 322 816;
  • 60) 0.973 740 322 816 × 2 = 1 + 0.947 480 645 632;
  • 61) 0.947 480 645 632 × 2 = 1 + 0.894 961 291 264;
  • 62) 0.894 961 291 264 × 2 = 1 + 0.789 922 582 528;
  • 63) 0.789 922 582 528 × 2 = 1 + 0.579 845 165 056;
  • 64) 0.579 845 165 056 × 2 = 1 + 0.159 690 330 112;

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:


0.000 282 005 557(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1010 0101 0000 0100 1101 1001 1011 1111(2)

6. Positive number before normalization:

0.000 282 005 557(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1010 0101 0000 0100 1101 1001 1011 1111(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:


0.000 282 005 557(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1010 0101 0000 0100 1101 1001 1011 1111(2) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1010 0101 0000 0100 1101 1001 1011 1111(2) × 20 =


1.0010 0111 1011 0100 0100 1010 0101 0000 0100 1101 1001 1011 1111(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 0100 1010 0101 0000 0100 1101 1001 1011 1111


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 0100 1010 0101 0000 0100 1101 1001 1011 1111 =


0010 0111 1011 0100 0100 1010 0101 0000 0100 1101 1001 1011 1111


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 0100 1010 0101 0000 0100 1101 1001 1011 1111


Decimal number -0.000 282 005 557 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0100 1010 0101 0000 0100 1101 1001 1011 1111


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