-0.000 282 006 069 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 069(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
-0.000 282 006 069(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:

|-0.000 282 006 069| = 0.000 282 006 069


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: 0.000 282 006 069.

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) 0.000 282 006 069 × 2 = 0 + 0.000 564 012 138;
  • 2) 0.000 564 012 138 × 2 = 0 + 0.001 128 024 276;
  • 3) 0.001 128 024 276 × 2 = 0 + 0.002 256 048 552;
  • 4) 0.002 256 048 552 × 2 = 0 + 0.004 512 097 104;
  • 5) 0.004 512 097 104 × 2 = 0 + 0.009 024 194 208;
  • 6) 0.009 024 194 208 × 2 = 0 + 0.018 048 388 416;
  • 7) 0.018 048 388 416 × 2 = 0 + 0.036 096 776 832;
  • 8) 0.036 096 776 832 × 2 = 0 + 0.072 193 553 664;
  • 9) 0.072 193 553 664 × 2 = 0 + 0.144 387 107 328;
  • 10) 0.144 387 107 328 × 2 = 0 + 0.288 774 214 656;
  • 11) 0.288 774 214 656 × 2 = 0 + 0.577 548 429 312;
  • 12) 0.577 548 429 312 × 2 = 1 + 0.155 096 858 624;
  • 13) 0.155 096 858 624 × 2 = 0 + 0.310 193 717 248;
  • 14) 0.310 193 717 248 × 2 = 0 + 0.620 387 434 496;
  • 15) 0.620 387 434 496 × 2 = 1 + 0.240 774 868 992;
  • 16) 0.240 774 868 992 × 2 = 0 + 0.481 549 737 984;
  • 17) 0.481 549 737 984 × 2 = 0 + 0.963 099 475 968;
  • 18) 0.963 099 475 968 × 2 = 1 + 0.926 198 951 936;
  • 19) 0.926 198 951 936 × 2 = 1 + 0.852 397 903 872;
  • 20) 0.852 397 903 872 × 2 = 1 + 0.704 795 807 744;
  • 21) 0.704 795 807 744 × 2 = 1 + 0.409 591 615 488;
  • 22) 0.409 591 615 488 × 2 = 0 + 0.819 183 230 976;
  • 23) 0.819 183 230 976 × 2 = 1 + 0.638 366 461 952;
  • 24) 0.638 366 461 952 × 2 = 1 + 0.276 732 923 904;
  • 25) 0.276 732 923 904 × 2 = 0 + 0.553 465 847 808;
  • 26) 0.553 465 847 808 × 2 = 1 + 0.106 931 695 616;
  • 27) 0.106 931 695 616 × 2 = 0 + 0.213 863 391 232;
  • 28) 0.213 863 391 232 × 2 = 0 + 0.427 726 782 464;
  • 29) 0.427 726 782 464 × 2 = 0 + 0.855 453 564 928;
  • 30) 0.855 453 564 928 × 2 = 1 + 0.710 907 129 856;
  • 31) 0.710 907 129 856 × 2 = 1 + 0.421 814 259 712;
  • 32) 0.421 814 259 712 × 2 = 0 + 0.843 628 519 424;
  • 33) 0.843 628 519 424 × 2 = 1 + 0.687 257 038 848;
  • 34) 0.687 257 038 848 × 2 = 1 + 0.374 514 077 696;
  • 35) 0.374 514 077 696 × 2 = 0 + 0.749 028 155 392;
  • 36) 0.749 028 155 392 × 2 = 1 + 0.498 056 310 784;
  • 37) 0.498 056 310 784 × 2 = 0 + 0.996 112 621 568;
  • 38) 0.996 112 621 568 × 2 = 1 + 0.992 225 243 136;
  • 39) 0.992 225 243 136 × 2 = 1 + 0.984 450 486 272;
  • 40) 0.984 450 486 272 × 2 = 1 + 0.968 900 972 544;
  • 41) 0.968 900 972 544 × 2 = 1 + 0.937 801 945 088;
  • 42) 0.937 801 945 088 × 2 = 1 + 0.875 603 890 176;
  • 43) 0.875 603 890 176 × 2 = 1 + 0.751 207 780 352;
  • 44) 0.751 207 780 352 × 2 = 1 + 0.502 415 560 704;
  • 45) 0.502 415 560 704 × 2 = 1 + 0.004 831 121 408;
  • 46) 0.004 831 121 408 × 2 = 0 + 0.009 662 242 816;
  • 47) 0.009 662 242 816 × 2 = 0 + 0.019 324 485 632;
  • 48) 0.019 324 485 632 × 2 = 0 + 0.038 648 971 264;
  • 49) 0.038 648 971 264 × 2 = 0 + 0.077 297 942 528;
  • 50) 0.077 297 942 528 × 2 = 0 + 0.154 595 885 056;
  • 51) 0.154 595 885 056 × 2 = 0 + 0.309 191 770 112;
  • 52) 0.309 191 770 112 × 2 = 0 + 0.618 383 540 224;
  • 53) 0.618 383 540 224 × 2 = 1 + 0.236 767 080 448;
  • 54) 0.236 767 080 448 × 2 = 0 + 0.473 534 160 896;
  • 55) 0.473 534 160 896 × 2 = 0 + 0.947 068 321 792;
  • 56) 0.947 068 321 792 × 2 = 1 + 0.894 136 643 584;
  • 57) 0.894 136 643 584 × 2 = 1 + 0.788 273 287 168;
  • 58) 0.788 273 287 168 × 2 = 1 + 0.576 546 574 336;
  • 59) 0.576 546 574 336 × 2 = 1 + 0.153 093 148 672;
  • 60) 0.153 093 148 672 × 2 = 0 + 0.306 186 297 344;
  • 61) 0.306 186 297 344 × 2 = 0 + 0.612 372 594 688;
  • 62) 0.612 372 594 688 × 2 = 1 + 0.224 745 189 376;
  • 63) 0.224 745 189 376 × 2 = 0 + 0.449 490 378 752;
  • 64) 0.449 490 378 752 × 2 = 0 + 0.898 980 757 504;

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:


0.000 282 006 069(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 1101 0111 1111 1000 0000 1001 1110 0100(2)

6. Positive number before normalization:

0.000 282 006 069(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 1101 0111 1111 1000 0000 1001 1110 0100(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:


0.000 282 006 069(10) =


0.0000 0000 0001 0010 0111 1011 0100 0110 1101 0111 1111 1000 0000 1001 1110 0100(2) =


0.0000 0000 0001 0010 0111 1011 0100 0110 1101 0111 1111 1000 0000 1001 1110 0100(2) × 20 =


1.0010 0111 1011 0100 0110 1101 0111 1111 1000 0000 1001 1110 0100(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 1101 0111 1111 1000 0000 1001 1110 0100


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 1101 0111 1111 1000 0000 1001 1110 0100 =


0010 0111 1011 0100 0110 1101 0111 1111 1000 0000 1001 1110 0100


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 1101 0111 1111 1000 0000 1001 1110 0100


Decimal number -0.000 282 006 069 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0110 1101 0111 1111 1000 0000 1001 1110 0100


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