-0.000 282 005 769 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 769(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
-0.000 282 005 769(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:

|-0.000 282 005 769| = 0.000 282 005 769


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: 0.000 282 005 769.

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) 0.000 282 005 769 × 2 = 0 + 0.000 564 011 538;
  • 2) 0.000 564 011 538 × 2 = 0 + 0.001 128 023 076;
  • 3) 0.001 128 023 076 × 2 = 0 + 0.002 256 046 152;
  • 4) 0.002 256 046 152 × 2 = 0 + 0.004 512 092 304;
  • 5) 0.004 512 092 304 × 2 = 0 + 0.009 024 184 608;
  • 6) 0.009 024 184 608 × 2 = 0 + 0.018 048 369 216;
  • 7) 0.018 048 369 216 × 2 = 0 + 0.036 096 738 432;
  • 8) 0.036 096 738 432 × 2 = 0 + 0.072 193 476 864;
  • 9) 0.072 193 476 864 × 2 = 0 + 0.144 386 953 728;
  • 10) 0.144 386 953 728 × 2 = 0 + 0.288 773 907 456;
  • 11) 0.288 773 907 456 × 2 = 0 + 0.577 547 814 912;
  • 12) 0.577 547 814 912 × 2 = 1 + 0.155 095 629 824;
  • 13) 0.155 095 629 824 × 2 = 0 + 0.310 191 259 648;
  • 14) 0.310 191 259 648 × 2 = 0 + 0.620 382 519 296;
  • 15) 0.620 382 519 296 × 2 = 1 + 0.240 765 038 592;
  • 16) 0.240 765 038 592 × 2 = 0 + 0.481 530 077 184;
  • 17) 0.481 530 077 184 × 2 = 0 + 0.963 060 154 368;
  • 18) 0.963 060 154 368 × 2 = 1 + 0.926 120 308 736;
  • 19) 0.926 120 308 736 × 2 = 1 + 0.852 240 617 472;
  • 20) 0.852 240 617 472 × 2 = 1 + 0.704 481 234 944;
  • 21) 0.704 481 234 944 × 2 = 1 + 0.408 962 469 888;
  • 22) 0.408 962 469 888 × 2 = 0 + 0.817 924 939 776;
  • 23) 0.817 924 939 776 × 2 = 1 + 0.635 849 879 552;
  • 24) 0.635 849 879 552 × 2 = 1 + 0.271 699 759 104;
  • 25) 0.271 699 759 104 × 2 = 0 + 0.543 399 518 208;
  • 26) 0.543 399 518 208 × 2 = 1 + 0.086 799 036 416;
  • 27) 0.086 799 036 416 × 2 = 0 + 0.173 598 072 832;
  • 28) 0.173 598 072 832 × 2 = 0 + 0.347 196 145 664;
  • 29) 0.347 196 145 664 × 2 = 0 + 0.694 392 291 328;
  • 30) 0.694 392 291 328 × 2 = 1 + 0.388 784 582 656;
  • 31) 0.388 784 582 656 × 2 = 0 + 0.777 569 165 312;
  • 32) 0.777 569 165 312 × 2 = 1 + 0.555 138 330 624;
  • 33) 0.555 138 330 624 × 2 = 1 + 0.110 276 661 248;
  • 34) 0.110 276 661 248 × 2 = 0 + 0.220 553 322 496;
  • 35) 0.220 553 322 496 × 2 = 0 + 0.441 106 644 992;
  • 36) 0.441 106 644 992 × 2 = 0 + 0.882 213 289 984;
  • 37) 0.882 213 289 984 × 2 = 1 + 0.764 426 579 968;
  • 38) 0.764 426 579 968 × 2 = 1 + 0.528 853 159 936;
  • 39) 0.528 853 159 936 × 2 = 1 + 0.057 706 319 872;
  • 40) 0.057 706 319 872 × 2 = 0 + 0.115 412 639 744;
  • 41) 0.115 412 639 744 × 2 = 0 + 0.230 825 279 488;
  • 42) 0.230 825 279 488 × 2 = 0 + 0.461 650 558 976;
  • 43) 0.461 650 558 976 × 2 = 0 + 0.923 301 117 952;
  • 44) 0.923 301 117 952 × 2 = 1 + 0.846 602 235 904;
  • 45) 0.846 602 235 904 × 2 = 1 + 0.693 204 471 808;
  • 46) 0.693 204 471 808 × 2 = 1 + 0.386 408 943 616;
  • 47) 0.386 408 943 616 × 2 = 0 + 0.772 817 887 232;
  • 48) 0.772 817 887 232 × 2 = 1 + 0.545 635 774 464;
  • 49) 0.545 635 774 464 × 2 = 1 + 0.091 271 548 928;
  • 50) 0.091 271 548 928 × 2 = 0 + 0.182 543 097 856;
  • 51) 0.182 543 097 856 × 2 = 0 + 0.365 086 195 712;
  • 52) 0.365 086 195 712 × 2 = 0 + 0.730 172 391 424;
  • 53) 0.730 172 391 424 × 2 = 1 + 0.460 344 782 848;
  • 54) 0.460 344 782 848 × 2 = 0 + 0.920 689 565 696;
  • 55) 0.920 689 565 696 × 2 = 1 + 0.841 379 131 392;
  • 56) 0.841 379 131 392 × 2 = 1 + 0.682 758 262 784;
  • 57) 0.682 758 262 784 × 2 = 1 + 0.365 516 525 568;
  • 58) 0.365 516 525 568 × 2 = 0 + 0.731 033 051 136;
  • 59) 0.731 033 051 136 × 2 = 1 + 0.462 066 102 272;
  • 60) 0.462 066 102 272 × 2 = 0 + 0.924 132 204 544;
  • 61) 0.924 132 204 544 × 2 = 1 + 0.848 264 409 088;
  • 62) 0.848 264 409 088 × 2 = 1 + 0.696 528 818 176;
  • 63) 0.696 528 818 176 × 2 = 1 + 0.393 057 636 352;
  • 64) 0.393 057 636 352 × 2 = 0 + 0.786 115 272 704;

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:


0.000 282 005 769(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1000 1110 0001 1101 1000 1011 1010 1110(2)

6. Positive number before normalization:

0.000 282 005 769(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1000 1110 0001 1101 1000 1011 1010 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:


0.000 282 005 769(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1000 1110 0001 1101 1000 1011 1010 1110(2) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1000 1110 0001 1101 1000 1011 1010 1110(2) × 20 =


1.0010 0111 1011 0100 0101 1000 1110 0001 1101 1000 1011 1010 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 0101 1000 1110 0001 1101 1000 1011 1010 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 0101 1000 1110 0001 1101 1000 1011 1010 1110 =


0010 0111 1011 0100 0101 1000 1110 0001 1101 1000 1011 1010 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 0101 1000 1110 0001 1101 1000 1011 1010 1110


Decimal number -0.000 282 005 769 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0101 1000 1110 0001 1101 1000 1011 1010 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