-0.000 282 005 914 15 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 914 15(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
-0.000 282 005 914 15(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:

|-0.000 282 005 914 15| = 0.000 282 005 914 15


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: 0.000 282 005 914 15.

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) 0.000 282 005 914 15 × 2 = 0 + 0.000 564 011 828 3;
  • 2) 0.000 564 011 828 3 × 2 = 0 + 0.001 128 023 656 6;
  • 3) 0.001 128 023 656 6 × 2 = 0 + 0.002 256 047 313 2;
  • 4) 0.002 256 047 313 2 × 2 = 0 + 0.004 512 094 626 4;
  • 5) 0.004 512 094 626 4 × 2 = 0 + 0.009 024 189 252 8;
  • 6) 0.009 024 189 252 8 × 2 = 0 + 0.018 048 378 505 6;
  • 7) 0.018 048 378 505 6 × 2 = 0 + 0.036 096 757 011 2;
  • 8) 0.036 096 757 011 2 × 2 = 0 + 0.072 193 514 022 4;
  • 9) 0.072 193 514 022 4 × 2 = 0 + 0.144 387 028 044 8;
  • 10) 0.144 387 028 044 8 × 2 = 0 + 0.288 774 056 089 6;
  • 11) 0.288 774 056 089 6 × 2 = 0 + 0.577 548 112 179 2;
  • 12) 0.577 548 112 179 2 × 2 = 1 + 0.155 096 224 358 4;
  • 13) 0.155 096 224 358 4 × 2 = 0 + 0.310 192 448 716 8;
  • 14) 0.310 192 448 716 8 × 2 = 0 + 0.620 384 897 433 6;
  • 15) 0.620 384 897 433 6 × 2 = 1 + 0.240 769 794 867 2;
  • 16) 0.240 769 794 867 2 × 2 = 0 + 0.481 539 589 734 4;
  • 17) 0.481 539 589 734 4 × 2 = 0 + 0.963 079 179 468 8;
  • 18) 0.963 079 179 468 8 × 2 = 1 + 0.926 158 358 937 6;
  • 19) 0.926 158 358 937 6 × 2 = 1 + 0.852 316 717 875 2;
  • 20) 0.852 316 717 875 2 × 2 = 1 + 0.704 633 435 750 4;
  • 21) 0.704 633 435 750 4 × 2 = 1 + 0.409 266 871 500 8;
  • 22) 0.409 266 871 500 8 × 2 = 0 + 0.818 533 743 001 6;
  • 23) 0.818 533 743 001 6 × 2 = 1 + 0.637 067 486 003 2;
  • 24) 0.637 067 486 003 2 × 2 = 1 + 0.274 134 972 006 4;
  • 25) 0.274 134 972 006 4 × 2 = 0 + 0.548 269 944 012 8;
  • 26) 0.548 269 944 012 8 × 2 = 1 + 0.096 539 888 025 6;
  • 27) 0.096 539 888 025 6 × 2 = 0 + 0.193 079 776 051 2;
  • 28) 0.193 079 776 051 2 × 2 = 0 + 0.386 159 552 102 4;
  • 29) 0.386 159 552 102 4 × 2 = 0 + 0.772 319 104 204 8;
  • 30) 0.772 319 104 204 8 × 2 = 1 + 0.544 638 208 409 6;
  • 31) 0.544 638 208 409 6 × 2 = 1 + 0.089 276 416 819 2;
  • 32) 0.089 276 416 819 2 × 2 = 0 + 0.178 552 833 638 4;
  • 33) 0.178 552 833 638 4 × 2 = 0 + 0.357 105 667 276 8;
  • 34) 0.357 105 667 276 8 × 2 = 0 + 0.714 211 334 553 6;
  • 35) 0.714 211 334 553 6 × 2 = 1 + 0.428 422 669 107 2;
  • 36) 0.428 422 669 107 2 × 2 = 0 + 0.856 845 338 214 4;
  • 37) 0.856 845 338 214 4 × 2 = 1 + 0.713 690 676 428 8;
  • 38) 0.713 690 676 428 8 × 2 = 1 + 0.427 381 352 857 6;
  • 39) 0.427 381 352 857 6 × 2 = 0 + 0.854 762 705 715 2;
  • 40) 0.854 762 705 715 2 × 2 = 1 + 0.709 525 411 430 4;
  • 41) 0.709 525 411 430 4 × 2 = 1 + 0.419 050 822 860 8;
  • 42) 0.419 050 822 860 8 × 2 = 0 + 0.838 101 645 721 6;
  • 43) 0.838 101 645 721 6 × 2 = 1 + 0.676 203 291 443 2;
  • 44) 0.676 203 291 443 2 × 2 = 1 + 0.352 406 582 886 4;
  • 45) 0.352 406 582 886 4 × 2 = 0 + 0.704 813 165 772 8;
  • 46) 0.704 813 165 772 8 × 2 = 1 + 0.409 626 331 545 6;
  • 47) 0.409 626 331 545 6 × 2 = 0 + 0.819 252 663 091 2;
  • 48) 0.819 252 663 091 2 × 2 = 1 + 0.638 505 326 182 4;
  • 49) 0.638 505 326 182 4 × 2 = 1 + 0.277 010 652 364 8;
  • 50) 0.277 010 652 364 8 × 2 = 0 + 0.554 021 304 729 6;
  • 51) 0.554 021 304 729 6 × 2 = 1 + 0.108 042 609 459 2;
  • 52) 0.108 042 609 459 2 × 2 = 0 + 0.216 085 218 918 4;
  • 53) 0.216 085 218 918 4 × 2 = 0 + 0.432 170 437 836 8;
  • 54) 0.432 170 437 836 8 × 2 = 0 + 0.864 340 875 673 6;
  • 55) 0.864 340 875 673 6 × 2 = 1 + 0.728 681 751 347 2;
  • 56) 0.728 681 751 347 2 × 2 = 1 + 0.457 363 502 694 4;
  • 57) 0.457 363 502 694 4 × 2 = 0 + 0.914 727 005 388 8;
  • 58) 0.914 727 005 388 8 × 2 = 1 + 0.829 454 010 777 6;
  • 59) 0.829 454 010 777 6 × 2 = 1 + 0.658 908 021 555 2;
  • 60) 0.658 908 021 555 2 × 2 = 1 + 0.317 816 043 110 4;
  • 61) 0.317 816 043 110 4 × 2 = 0 + 0.635 632 086 220 8;
  • 62) 0.635 632 086 220 8 × 2 = 1 + 0.271 264 172 441 6;
  • 63) 0.271 264 172 441 6 × 2 = 0 + 0.542 528 344 883 2;
  • 64) 0.542 528 344 883 2 × 2 = 1 + 0.085 056 689 766 4;

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:


0.000 282 005 914 15(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1011 0101 1010 0011 0111 0101(2)

6. Positive number before normalization:

0.000 282 005 914 15(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1011 0101 1010 0011 0111 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:


0.000 282 005 914 15(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1011 0101 1010 0011 0111 0101(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 0010 1101 1011 0101 1010 0011 0111 0101(2) × 20 =


1.0010 0111 1011 0100 0110 0010 1101 1011 0101 1010 0011 0111 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 0110 0010 1101 1011 0101 1010 0011 0111 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 0110 0010 1101 1011 0101 1010 0011 0111 0101 =


0010 0111 1011 0100 0110 0010 1101 1011 0101 1010 0011 0111 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 0110 0010 1101 1011 0101 1010 0011 0111 0101


Decimal number -0.000 282 005 914 15 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 0010 1101 1011 0101 1010 0011 0111 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