-0.000 282 006 502 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 502(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
-0.000 282 006 502(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:

|-0.000 282 006 502| = 0.000 282 006 502


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: 0.000 282 006 502.

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) 0.000 282 006 502 × 2 = 0 + 0.000 564 013 004;
  • 2) 0.000 564 013 004 × 2 = 0 + 0.001 128 026 008;
  • 3) 0.001 128 026 008 × 2 = 0 + 0.002 256 052 016;
  • 4) 0.002 256 052 016 × 2 = 0 + 0.004 512 104 032;
  • 5) 0.004 512 104 032 × 2 = 0 + 0.009 024 208 064;
  • 6) 0.009 024 208 064 × 2 = 0 + 0.018 048 416 128;
  • 7) 0.018 048 416 128 × 2 = 0 + 0.036 096 832 256;
  • 8) 0.036 096 832 256 × 2 = 0 + 0.072 193 664 512;
  • 9) 0.072 193 664 512 × 2 = 0 + 0.144 387 329 024;
  • 10) 0.144 387 329 024 × 2 = 0 + 0.288 774 658 048;
  • 11) 0.288 774 658 048 × 2 = 0 + 0.577 549 316 096;
  • 12) 0.577 549 316 096 × 2 = 1 + 0.155 098 632 192;
  • 13) 0.155 098 632 192 × 2 = 0 + 0.310 197 264 384;
  • 14) 0.310 197 264 384 × 2 = 0 + 0.620 394 528 768;
  • 15) 0.620 394 528 768 × 2 = 1 + 0.240 789 057 536;
  • 16) 0.240 789 057 536 × 2 = 0 + 0.481 578 115 072;
  • 17) 0.481 578 115 072 × 2 = 0 + 0.963 156 230 144;
  • 18) 0.963 156 230 144 × 2 = 1 + 0.926 312 460 288;
  • 19) 0.926 312 460 288 × 2 = 1 + 0.852 624 920 576;
  • 20) 0.852 624 920 576 × 2 = 1 + 0.705 249 841 152;
  • 21) 0.705 249 841 152 × 2 = 1 + 0.410 499 682 304;
  • 22) 0.410 499 682 304 × 2 = 0 + 0.820 999 364 608;
  • 23) 0.820 999 364 608 × 2 = 1 + 0.641 998 729 216;
  • 24) 0.641 998 729 216 × 2 = 1 + 0.283 997 458 432;
  • 25) 0.283 997 458 432 × 2 = 0 + 0.567 994 916 864;
  • 26) 0.567 994 916 864 × 2 = 1 + 0.135 989 833 728;
  • 27) 0.135 989 833 728 × 2 = 0 + 0.271 979 667 456;
  • 28) 0.271 979 667 456 × 2 = 0 + 0.543 959 334 912;
  • 29) 0.543 959 334 912 × 2 = 1 + 0.087 918 669 824;
  • 30) 0.087 918 669 824 × 2 = 0 + 0.175 837 339 648;
  • 31) 0.175 837 339 648 × 2 = 0 + 0.351 674 679 296;
  • 32) 0.351 674 679 296 × 2 = 0 + 0.703 349 358 592;
  • 33) 0.703 349 358 592 × 2 = 1 + 0.406 698 717 184;
  • 34) 0.406 698 717 184 × 2 = 0 + 0.813 397 434 368;
  • 35) 0.813 397 434 368 × 2 = 1 + 0.626 794 868 736;
  • 36) 0.626 794 868 736 × 2 = 1 + 0.253 589 737 472;
  • 37) 0.253 589 737 472 × 2 = 0 + 0.507 179 474 944;
  • 38) 0.507 179 474 944 × 2 = 1 + 0.014 358 949 888;
  • 39) 0.014 358 949 888 × 2 = 0 + 0.028 717 899 776;
  • 40) 0.028 717 899 776 × 2 = 0 + 0.057 435 799 552;
  • 41) 0.057 435 799 552 × 2 = 0 + 0.114 871 599 104;
  • 42) 0.114 871 599 104 × 2 = 0 + 0.229 743 198 208;
  • 43) 0.229 743 198 208 × 2 = 0 + 0.459 486 396 416;
  • 44) 0.459 486 396 416 × 2 = 0 + 0.918 972 792 832;
  • 45) 0.918 972 792 832 × 2 = 1 + 0.837 945 585 664;
  • 46) 0.837 945 585 664 × 2 = 1 + 0.675 891 171 328;
  • 47) 0.675 891 171 328 × 2 = 1 + 0.351 782 342 656;
  • 48) 0.351 782 342 656 × 2 = 0 + 0.703 564 685 312;
  • 49) 0.703 564 685 312 × 2 = 1 + 0.407 129 370 624;
  • 50) 0.407 129 370 624 × 2 = 0 + 0.814 258 741 248;
  • 51) 0.814 258 741 248 × 2 = 1 + 0.628 517 482 496;
  • 52) 0.628 517 482 496 × 2 = 1 + 0.257 034 964 992;
  • 53) 0.257 034 964 992 × 2 = 0 + 0.514 069 929 984;
  • 54) 0.514 069 929 984 × 2 = 1 + 0.028 139 859 968;
  • 55) 0.028 139 859 968 × 2 = 0 + 0.056 279 719 936;
  • 56) 0.056 279 719 936 × 2 = 0 + 0.112 559 439 872;
  • 57) 0.112 559 439 872 × 2 = 0 + 0.225 118 879 744;
  • 58) 0.225 118 879 744 × 2 = 0 + 0.450 237 759 488;
  • 59) 0.450 237 759 488 × 2 = 0 + 0.900 475 518 976;
  • 60) 0.900 475 518 976 × 2 = 1 + 0.800 951 037 952;
  • 61) 0.800 951 037 952 × 2 = 1 + 0.601 902 075 904;
  • 62) 0.601 902 075 904 × 2 = 1 + 0.203 804 151 808;
  • 63) 0.203 804 151 808 × 2 = 0 + 0.407 608 303 616;
  • 64) 0.407 608 303 616 × 2 = 0 + 0.815 216 607 232;

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:


0.000 282 006 502(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 1011 0100 0000 1110 1011 0100 0001 1100(2)

6. Positive number before normalization:

0.000 282 006 502(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 1011 0100 0000 1110 1011 0100 0001 1100(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:


0.000 282 006 502(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 1011 0100 0000 1110 1011 0100 0001 1100(2) =


0.0000 0000 0001 0010 0111 1011 0100 1000 1011 0100 0000 1110 1011 0100 0001 1100(2) × 20 =


1.0010 0111 1011 0100 1000 1011 0100 0000 1110 1011 0100 0001 1100(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 1011 0100 0000 1110 1011 0100 0001 1100


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 1011 0100 0000 1110 1011 0100 0001 1100 =


0010 0111 1011 0100 1000 1011 0100 0000 1110 1011 0100 0001 1100


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 1011 0100 0000 1110 1011 0100 0001 1100


Decimal number -0.000 282 006 502 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 1000 1011 0100 0000 1110 1011 0100 0001 1100


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