-0.000 282 006 261 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 261(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
-0.000 282 006 261(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:

|-0.000 282 006 261| = 0.000 282 006 261


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: 0.000 282 006 261.

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) 0.000 282 006 261 × 2 = 0 + 0.000 564 012 522;
  • 2) 0.000 564 012 522 × 2 = 0 + 0.001 128 025 044;
  • 3) 0.001 128 025 044 × 2 = 0 + 0.002 256 050 088;
  • 4) 0.002 256 050 088 × 2 = 0 + 0.004 512 100 176;
  • 5) 0.004 512 100 176 × 2 = 0 + 0.009 024 200 352;
  • 6) 0.009 024 200 352 × 2 = 0 + 0.018 048 400 704;
  • 7) 0.018 048 400 704 × 2 = 0 + 0.036 096 801 408;
  • 8) 0.036 096 801 408 × 2 = 0 + 0.072 193 602 816;
  • 9) 0.072 193 602 816 × 2 = 0 + 0.144 387 205 632;
  • 10) 0.144 387 205 632 × 2 = 0 + 0.288 774 411 264;
  • 11) 0.288 774 411 264 × 2 = 0 + 0.577 548 822 528;
  • 12) 0.577 548 822 528 × 2 = 1 + 0.155 097 645 056;
  • 13) 0.155 097 645 056 × 2 = 0 + 0.310 195 290 112;
  • 14) 0.310 195 290 112 × 2 = 0 + 0.620 390 580 224;
  • 15) 0.620 390 580 224 × 2 = 1 + 0.240 781 160 448;
  • 16) 0.240 781 160 448 × 2 = 0 + 0.481 562 320 896;
  • 17) 0.481 562 320 896 × 2 = 0 + 0.963 124 641 792;
  • 18) 0.963 124 641 792 × 2 = 1 + 0.926 249 283 584;
  • 19) 0.926 249 283 584 × 2 = 1 + 0.852 498 567 168;
  • 20) 0.852 498 567 168 × 2 = 1 + 0.704 997 134 336;
  • 21) 0.704 997 134 336 × 2 = 1 + 0.409 994 268 672;
  • 22) 0.409 994 268 672 × 2 = 0 + 0.819 988 537 344;
  • 23) 0.819 988 537 344 × 2 = 1 + 0.639 977 074 688;
  • 24) 0.639 977 074 688 × 2 = 1 + 0.279 954 149 376;
  • 25) 0.279 954 149 376 × 2 = 0 + 0.559 908 298 752;
  • 26) 0.559 908 298 752 × 2 = 1 + 0.119 816 597 504;
  • 27) 0.119 816 597 504 × 2 = 0 + 0.239 633 195 008;
  • 28) 0.239 633 195 008 × 2 = 0 + 0.479 266 390 016;
  • 29) 0.479 266 390 016 × 2 = 0 + 0.958 532 780 032;
  • 30) 0.958 532 780 032 × 2 = 1 + 0.917 065 560 064;
  • 31) 0.917 065 560 064 × 2 = 1 + 0.834 131 120 128;
  • 32) 0.834 131 120 128 × 2 = 1 + 0.668 262 240 256;
  • 33) 0.668 262 240 256 × 2 = 1 + 0.336 524 480 512;
  • 34) 0.336 524 480 512 × 2 = 0 + 0.673 048 961 024;
  • 35) 0.673 048 961 024 × 2 = 1 + 0.346 097 922 048;
  • 36) 0.346 097 922 048 × 2 = 0 + 0.692 195 844 096;
  • 37) 0.692 195 844 096 × 2 = 1 + 0.384 391 688 192;
  • 38) 0.384 391 688 192 × 2 = 0 + 0.768 783 376 384;
  • 39) 0.768 783 376 384 × 2 = 1 + 0.537 566 752 768;
  • 40) 0.537 566 752 768 × 2 = 1 + 0.075 133 505 536;
  • 41) 0.075 133 505 536 × 2 = 0 + 0.150 267 011 072;
  • 42) 0.150 267 011 072 × 2 = 0 + 0.300 534 022 144;
  • 43) 0.300 534 022 144 × 2 = 0 + 0.601 068 044 288;
  • 44) 0.601 068 044 288 × 2 = 1 + 0.202 136 088 576;
  • 45) 0.202 136 088 576 × 2 = 0 + 0.404 272 177 152;
  • 46) 0.404 272 177 152 × 2 = 0 + 0.808 544 354 304;
  • 47) 0.808 544 354 304 × 2 = 1 + 0.617 088 708 608;
  • 48) 0.617 088 708 608 × 2 = 1 + 0.234 177 417 216;
  • 49) 0.234 177 417 216 × 2 = 0 + 0.468 354 834 432;
  • 50) 0.468 354 834 432 × 2 = 0 + 0.936 709 668 864;
  • 51) 0.936 709 668 864 × 2 = 1 + 0.873 419 337 728;
  • 52) 0.873 419 337 728 × 2 = 1 + 0.746 838 675 456;
  • 53) 0.746 838 675 456 × 2 = 1 + 0.493 677 350 912;
  • 54) 0.493 677 350 912 × 2 = 0 + 0.987 354 701 824;
  • 55) 0.987 354 701 824 × 2 = 1 + 0.974 709 403 648;
  • 56) 0.974 709 403 648 × 2 = 1 + 0.949 418 807 296;
  • 57) 0.949 418 807 296 × 2 = 1 + 0.898 837 614 592;
  • 58) 0.898 837 614 592 × 2 = 1 + 0.797 675 229 184;
  • 59) 0.797 675 229 184 × 2 = 1 + 0.595 350 458 368;
  • 60) 0.595 350 458 368 × 2 = 1 + 0.190 700 916 736;
  • 61) 0.190 700 916 736 × 2 = 0 + 0.381 401 833 472;
  • 62) 0.381 401 833 472 × 2 = 0 + 0.762 803 666 944;
  • 63) 0.762 803 666 944 × 2 = 1 + 0.525 607 333 888;
  • 64) 0.525 607 333 888 × 2 = 1 + 0.051 214 667 776;

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:


0.000 282 006 261(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1010 1011 0001 0011 0011 1011 1111 0011(2)

6. Positive number before normalization:

0.000 282 006 261(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1010 1011 0001 0011 0011 1011 1111 0011(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:


0.000 282 006 261(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1010 1011 0001 0011 0011 1011 1111 0011(2) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1010 1011 0001 0011 0011 1011 1111 0011(2) × 20 =


1.0010 0111 1011 0100 0111 1010 1011 0001 0011 0011 1011 1111 0011(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 0111 1010 1011 0001 0011 0011 1011 1111 0011


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 0111 1010 1011 0001 0011 0011 1011 1111 0011 =


0010 0111 1011 0100 0111 1010 1011 0001 0011 0011 1011 1111 0011


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 0111 1010 1011 0001 0011 0011 1011 1111 0011


Decimal number -0.000 282 006 261 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0111 1010 1011 0001 0011 0011 1011 1111 0011


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