-0.000 282 005 756 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 756(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
-0.000 282 005 756(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:

|-0.000 282 005 756| = 0.000 282 005 756


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: 0.000 282 005 756.

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) 0.000 282 005 756 × 2 = 0 + 0.000 564 011 512;
  • 2) 0.000 564 011 512 × 2 = 0 + 0.001 128 023 024;
  • 3) 0.001 128 023 024 × 2 = 0 + 0.002 256 046 048;
  • 4) 0.002 256 046 048 × 2 = 0 + 0.004 512 092 096;
  • 5) 0.004 512 092 096 × 2 = 0 + 0.009 024 184 192;
  • 6) 0.009 024 184 192 × 2 = 0 + 0.018 048 368 384;
  • 7) 0.018 048 368 384 × 2 = 0 + 0.036 096 736 768;
  • 8) 0.036 096 736 768 × 2 = 0 + 0.072 193 473 536;
  • 9) 0.072 193 473 536 × 2 = 0 + 0.144 386 947 072;
  • 10) 0.144 386 947 072 × 2 = 0 + 0.288 773 894 144;
  • 11) 0.288 773 894 144 × 2 = 0 + 0.577 547 788 288;
  • 12) 0.577 547 788 288 × 2 = 1 + 0.155 095 576 576;
  • 13) 0.155 095 576 576 × 2 = 0 + 0.310 191 153 152;
  • 14) 0.310 191 153 152 × 2 = 0 + 0.620 382 306 304;
  • 15) 0.620 382 306 304 × 2 = 1 + 0.240 764 612 608;
  • 16) 0.240 764 612 608 × 2 = 0 + 0.481 529 225 216;
  • 17) 0.481 529 225 216 × 2 = 0 + 0.963 058 450 432;
  • 18) 0.963 058 450 432 × 2 = 1 + 0.926 116 900 864;
  • 19) 0.926 116 900 864 × 2 = 1 + 0.852 233 801 728;
  • 20) 0.852 233 801 728 × 2 = 1 + 0.704 467 603 456;
  • 21) 0.704 467 603 456 × 2 = 1 + 0.408 935 206 912;
  • 22) 0.408 935 206 912 × 2 = 0 + 0.817 870 413 824;
  • 23) 0.817 870 413 824 × 2 = 1 + 0.635 740 827 648;
  • 24) 0.635 740 827 648 × 2 = 1 + 0.271 481 655 296;
  • 25) 0.271 481 655 296 × 2 = 0 + 0.542 963 310 592;
  • 26) 0.542 963 310 592 × 2 = 1 + 0.085 926 621 184;
  • 27) 0.085 926 621 184 × 2 = 0 + 0.171 853 242 368;
  • 28) 0.171 853 242 368 × 2 = 0 + 0.343 706 484 736;
  • 29) 0.343 706 484 736 × 2 = 0 + 0.687 412 969 472;
  • 30) 0.687 412 969 472 × 2 = 1 + 0.374 825 938 944;
  • 31) 0.374 825 938 944 × 2 = 0 + 0.749 651 877 888;
  • 32) 0.749 651 877 888 × 2 = 1 + 0.499 303 755 776;
  • 33) 0.499 303 755 776 × 2 = 0 + 0.998 607 511 552;
  • 34) 0.998 607 511 552 × 2 = 1 + 0.997 215 023 104;
  • 35) 0.997 215 023 104 × 2 = 1 + 0.994 430 046 208;
  • 36) 0.994 430 046 208 × 2 = 1 + 0.988 860 092 416;
  • 37) 0.988 860 092 416 × 2 = 1 + 0.977 720 184 832;
  • 38) 0.977 720 184 832 × 2 = 1 + 0.955 440 369 664;
  • 39) 0.955 440 369 664 × 2 = 1 + 0.910 880 739 328;
  • 40) 0.910 880 739 328 × 2 = 1 + 0.821 761 478 656;
  • 41) 0.821 761 478 656 × 2 = 1 + 0.643 522 957 312;
  • 42) 0.643 522 957 312 × 2 = 1 + 0.287 045 914 624;
  • 43) 0.287 045 914 624 × 2 = 0 + 0.574 091 829 248;
  • 44) 0.574 091 829 248 × 2 = 1 + 0.148 183 658 496;
  • 45) 0.148 183 658 496 × 2 = 0 + 0.296 367 316 992;
  • 46) 0.296 367 316 992 × 2 = 0 + 0.592 734 633 984;
  • 47) 0.592 734 633 984 × 2 = 1 + 0.185 469 267 968;
  • 48) 0.185 469 267 968 × 2 = 0 + 0.370 938 535 936;
  • 49) 0.370 938 535 936 × 2 = 0 + 0.741 877 071 872;
  • 50) 0.741 877 071 872 × 2 = 1 + 0.483 754 143 744;
  • 51) 0.483 754 143 744 × 2 = 0 + 0.967 508 287 488;
  • 52) 0.967 508 287 488 × 2 = 1 + 0.935 016 574 976;
  • 53) 0.935 016 574 976 × 2 = 1 + 0.870 033 149 952;
  • 54) 0.870 033 149 952 × 2 = 1 + 0.740 066 299 904;
  • 55) 0.740 066 299 904 × 2 = 1 + 0.480 132 599 808;
  • 56) 0.480 132 599 808 × 2 = 0 + 0.960 265 199 616;
  • 57) 0.960 265 199 616 × 2 = 1 + 0.920 530 399 232;
  • 58) 0.920 530 399 232 × 2 = 1 + 0.841 060 798 464;
  • 59) 0.841 060 798 464 × 2 = 1 + 0.682 121 596 928;
  • 60) 0.682 121 596 928 × 2 = 1 + 0.364 243 193 856;
  • 61) 0.364 243 193 856 × 2 = 0 + 0.728 486 387 712;
  • 62) 0.728 486 387 712 × 2 = 1 + 0.456 972 775 424;
  • 63) 0.456 972 775 424 × 2 = 0 + 0.913 945 550 848;
  • 64) 0.913 945 550 848 × 2 = 1 + 0.827 891 101 696;

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:


0.000 282 005 756(10) =


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

6. Positive number before normalization:

0.000 282 005 756(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 0111 1111 1101 0010 0101 1110 1111 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:


0.000 282 005 756(10) =


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


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


1.0010 0111 1011 0100 0101 0111 1111 1101 0010 0101 1110 1111 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 0101 0111 1111 1101 0010 0101 1110 1111 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 0101 0111 1111 1101 0010 0101 1110 1111 0101 =


0010 0111 1011 0100 0101 0111 1111 1101 0010 0101 1110 1111 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 0101 0111 1111 1101 0010 0101 1110 1111 0101


Decimal number -0.000 282 005 756 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0101 0111 1111 1101 0010 0101 1110 1111 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