-0.000 282 005 876 7 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 876 7(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
-0.000 282 005 876 7(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:

|-0.000 282 005 876 7| = 0.000 282 005 876 7


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: 0.000 282 005 876 7.

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) 0.000 282 005 876 7 × 2 = 0 + 0.000 564 011 753 4;
  • 2) 0.000 564 011 753 4 × 2 = 0 + 0.001 128 023 506 8;
  • 3) 0.001 128 023 506 8 × 2 = 0 + 0.002 256 047 013 6;
  • 4) 0.002 256 047 013 6 × 2 = 0 + 0.004 512 094 027 2;
  • 5) 0.004 512 094 027 2 × 2 = 0 + 0.009 024 188 054 4;
  • 6) 0.009 024 188 054 4 × 2 = 0 + 0.018 048 376 108 8;
  • 7) 0.018 048 376 108 8 × 2 = 0 + 0.036 096 752 217 6;
  • 8) 0.036 096 752 217 6 × 2 = 0 + 0.072 193 504 435 2;
  • 9) 0.072 193 504 435 2 × 2 = 0 + 0.144 387 008 870 4;
  • 10) 0.144 387 008 870 4 × 2 = 0 + 0.288 774 017 740 8;
  • 11) 0.288 774 017 740 8 × 2 = 0 + 0.577 548 035 481 6;
  • 12) 0.577 548 035 481 6 × 2 = 1 + 0.155 096 070 963 2;
  • 13) 0.155 096 070 963 2 × 2 = 0 + 0.310 192 141 926 4;
  • 14) 0.310 192 141 926 4 × 2 = 0 + 0.620 384 283 852 8;
  • 15) 0.620 384 283 852 8 × 2 = 1 + 0.240 768 567 705 6;
  • 16) 0.240 768 567 705 6 × 2 = 0 + 0.481 537 135 411 2;
  • 17) 0.481 537 135 411 2 × 2 = 0 + 0.963 074 270 822 4;
  • 18) 0.963 074 270 822 4 × 2 = 1 + 0.926 148 541 644 8;
  • 19) 0.926 148 541 644 8 × 2 = 1 + 0.852 297 083 289 6;
  • 20) 0.852 297 083 289 6 × 2 = 1 + 0.704 594 166 579 2;
  • 21) 0.704 594 166 579 2 × 2 = 1 + 0.409 188 333 158 4;
  • 22) 0.409 188 333 158 4 × 2 = 0 + 0.818 376 666 316 8;
  • 23) 0.818 376 666 316 8 × 2 = 1 + 0.636 753 332 633 6;
  • 24) 0.636 753 332 633 6 × 2 = 1 + 0.273 506 665 267 2;
  • 25) 0.273 506 665 267 2 × 2 = 0 + 0.547 013 330 534 4;
  • 26) 0.547 013 330 534 4 × 2 = 1 + 0.094 026 661 068 8;
  • 27) 0.094 026 661 068 8 × 2 = 0 + 0.188 053 322 137 6;
  • 28) 0.188 053 322 137 6 × 2 = 0 + 0.376 106 644 275 2;
  • 29) 0.376 106 644 275 2 × 2 = 0 + 0.752 213 288 550 4;
  • 30) 0.752 213 288 550 4 × 2 = 1 + 0.504 426 577 100 8;
  • 31) 0.504 426 577 100 8 × 2 = 1 + 0.008 853 154 201 6;
  • 32) 0.008 853 154 201 6 × 2 = 0 + 0.017 706 308 403 2;
  • 33) 0.017 706 308 403 2 × 2 = 0 + 0.035 412 616 806 4;
  • 34) 0.035 412 616 806 4 × 2 = 0 + 0.070 825 233 612 8;
  • 35) 0.070 825 233 612 8 × 2 = 0 + 0.141 650 467 225 6;
  • 36) 0.141 650 467 225 6 × 2 = 0 + 0.283 300 934 451 2;
  • 37) 0.283 300 934 451 2 × 2 = 0 + 0.566 601 868 902 4;
  • 38) 0.566 601 868 902 4 × 2 = 1 + 0.133 203 737 804 8;
  • 39) 0.133 203 737 804 8 × 2 = 0 + 0.266 407 475 609 6;
  • 40) 0.266 407 475 609 6 × 2 = 0 + 0.532 814 951 219 2;
  • 41) 0.532 814 951 219 2 × 2 = 1 + 0.065 629 902 438 4;
  • 42) 0.065 629 902 438 4 × 2 = 0 + 0.131 259 804 876 8;
  • 43) 0.131 259 804 876 8 × 2 = 0 + 0.262 519 609 753 6;
  • 44) 0.262 519 609 753 6 × 2 = 0 + 0.525 039 219 507 2;
  • 45) 0.525 039 219 507 2 × 2 = 1 + 0.050 078 439 014 4;
  • 46) 0.050 078 439 014 4 × 2 = 0 + 0.100 156 878 028 8;
  • 47) 0.100 156 878 028 8 × 2 = 0 + 0.200 313 756 057 6;
  • 48) 0.200 313 756 057 6 × 2 = 0 + 0.400 627 512 115 2;
  • 49) 0.400 627 512 115 2 × 2 = 0 + 0.801 255 024 230 4;
  • 50) 0.801 255 024 230 4 × 2 = 1 + 0.602 510 048 460 8;
  • 51) 0.602 510 048 460 8 × 2 = 1 + 0.205 020 096 921 6;
  • 52) 0.205 020 096 921 6 × 2 = 0 + 0.410 040 193 843 2;
  • 53) 0.410 040 193 843 2 × 2 = 0 + 0.820 080 387 686 4;
  • 54) 0.820 080 387 686 4 × 2 = 1 + 0.640 160 775 372 8;
  • 55) 0.640 160 775 372 8 × 2 = 1 + 0.280 321 550 745 6;
  • 56) 0.280 321 550 745 6 × 2 = 0 + 0.560 643 101 491 2;
  • 57) 0.560 643 101 491 2 × 2 = 1 + 0.121 286 202 982 4;
  • 58) 0.121 286 202 982 4 × 2 = 0 + 0.242 572 405 964 8;
  • 59) 0.242 572 405 964 8 × 2 = 0 + 0.485 144 811 929 6;
  • 60) 0.485 144 811 929 6 × 2 = 0 + 0.970 289 623 859 2;
  • 61) 0.970 289 623 859 2 × 2 = 1 + 0.940 579 247 718 4;
  • 62) 0.940 579 247 718 4 × 2 = 1 + 0.881 158 495 436 8;
  • 63) 0.881 158 495 436 8 × 2 = 1 + 0.762 316 990 873 6;
  • 64) 0.762 316 990 873 6 × 2 = 1 + 0.524 633 981 747 2;

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:


0.000 282 005 876 7(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 0100 1000 1000 0110 0110 1000 1111(2)

6. Positive number before normalization:

0.000 282 005 876 7(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 0100 1000 1000 0110 0110 1000 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:


0.000 282 005 876 7(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 0100 1000 1000 0110 0110 1000 1111(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0000 0100 1000 1000 0110 0110 1000 1111(2) × 20 =


1.0010 0111 1011 0100 0110 0000 0100 1000 1000 0110 0110 1000 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 0110 0000 0100 1000 1000 0110 0110 1000 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 0110 0000 0100 1000 1000 0110 0110 1000 1111 =


0010 0111 1011 0100 0110 0000 0100 1000 1000 0110 0110 1000 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 0110 0000 0100 1000 1000 0110 0110 1000 1111


Decimal number -0.000 282 005 876 7 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0000 0100 1000 1000 0110 0110 1000 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