-0.000 282 005 858 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 858(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
-0.000 282 005 858(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:

|-0.000 282 005 858| = 0.000 282 005 858


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: 0.000 282 005 858.

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) 0.000 282 005 858 × 2 = 0 + 0.000 564 011 716;
  • 2) 0.000 564 011 716 × 2 = 0 + 0.001 128 023 432;
  • 3) 0.001 128 023 432 × 2 = 0 + 0.002 256 046 864;
  • 4) 0.002 256 046 864 × 2 = 0 + 0.004 512 093 728;
  • 5) 0.004 512 093 728 × 2 = 0 + 0.009 024 187 456;
  • 6) 0.009 024 187 456 × 2 = 0 + 0.018 048 374 912;
  • 7) 0.018 048 374 912 × 2 = 0 + 0.036 096 749 824;
  • 8) 0.036 096 749 824 × 2 = 0 + 0.072 193 499 648;
  • 9) 0.072 193 499 648 × 2 = 0 + 0.144 386 999 296;
  • 10) 0.144 386 999 296 × 2 = 0 + 0.288 773 998 592;
  • 11) 0.288 773 998 592 × 2 = 0 + 0.577 547 997 184;
  • 12) 0.577 547 997 184 × 2 = 1 + 0.155 095 994 368;
  • 13) 0.155 095 994 368 × 2 = 0 + 0.310 191 988 736;
  • 14) 0.310 191 988 736 × 2 = 0 + 0.620 383 977 472;
  • 15) 0.620 383 977 472 × 2 = 1 + 0.240 767 954 944;
  • 16) 0.240 767 954 944 × 2 = 0 + 0.481 535 909 888;
  • 17) 0.481 535 909 888 × 2 = 0 + 0.963 071 819 776;
  • 18) 0.963 071 819 776 × 2 = 1 + 0.926 143 639 552;
  • 19) 0.926 143 639 552 × 2 = 1 + 0.852 287 279 104;
  • 20) 0.852 287 279 104 × 2 = 1 + 0.704 574 558 208;
  • 21) 0.704 574 558 208 × 2 = 1 + 0.409 149 116 416;
  • 22) 0.409 149 116 416 × 2 = 0 + 0.818 298 232 832;
  • 23) 0.818 298 232 832 × 2 = 1 + 0.636 596 465 664;
  • 24) 0.636 596 465 664 × 2 = 1 + 0.273 192 931 328;
  • 25) 0.273 192 931 328 × 2 = 0 + 0.546 385 862 656;
  • 26) 0.546 385 862 656 × 2 = 1 + 0.092 771 725 312;
  • 27) 0.092 771 725 312 × 2 = 0 + 0.185 543 450 624;
  • 28) 0.185 543 450 624 × 2 = 0 + 0.371 086 901 248;
  • 29) 0.371 086 901 248 × 2 = 0 + 0.742 173 802 496;
  • 30) 0.742 173 802 496 × 2 = 1 + 0.484 347 604 992;
  • 31) 0.484 347 604 992 × 2 = 0 + 0.968 695 209 984;
  • 32) 0.968 695 209 984 × 2 = 1 + 0.937 390 419 968;
  • 33) 0.937 390 419 968 × 2 = 1 + 0.874 780 839 936;
  • 34) 0.874 780 839 936 × 2 = 1 + 0.749 561 679 872;
  • 35) 0.749 561 679 872 × 2 = 1 + 0.499 123 359 744;
  • 36) 0.499 123 359 744 × 2 = 0 + 0.998 246 719 488;
  • 37) 0.998 246 719 488 × 2 = 1 + 0.996 493 438 976;
  • 38) 0.996 493 438 976 × 2 = 1 + 0.992 986 877 952;
  • 39) 0.992 986 877 952 × 2 = 1 + 0.985 973 755 904;
  • 40) 0.985 973 755 904 × 2 = 1 + 0.971 947 511 808;
  • 41) 0.971 947 511 808 × 2 = 1 + 0.943 895 023 616;
  • 42) 0.943 895 023 616 × 2 = 1 + 0.887 790 047 232;
  • 43) 0.887 790 047 232 × 2 = 1 + 0.775 580 094 464;
  • 44) 0.775 580 094 464 × 2 = 1 + 0.551 160 188 928;
  • 45) 0.551 160 188 928 × 2 = 1 + 0.102 320 377 856;
  • 46) 0.102 320 377 856 × 2 = 0 + 0.204 640 755 712;
  • 47) 0.204 640 755 712 × 2 = 0 + 0.409 281 511 424;
  • 48) 0.409 281 511 424 × 2 = 0 + 0.818 563 022 848;
  • 49) 0.818 563 022 848 × 2 = 1 + 0.637 126 045 696;
  • 50) 0.637 126 045 696 × 2 = 1 + 0.274 252 091 392;
  • 51) 0.274 252 091 392 × 2 = 0 + 0.548 504 182 784;
  • 52) 0.548 504 182 784 × 2 = 1 + 0.097 008 365 568;
  • 53) 0.097 008 365 568 × 2 = 0 + 0.194 016 731 136;
  • 54) 0.194 016 731 136 × 2 = 0 + 0.388 033 462 272;
  • 55) 0.388 033 462 272 × 2 = 0 + 0.776 066 924 544;
  • 56) 0.776 066 924 544 × 2 = 1 + 0.552 133 849 088;
  • 57) 0.552 133 849 088 × 2 = 1 + 0.104 267 698 176;
  • 58) 0.104 267 698 176 × 2 = 0 + 0.208 535 396 352;
  • 59) 0.208 535 396 352 × 2 = 0 + 0.417 070 792 704;
  • 60) 0.417 070 792 704 × 2 = 0 + 0.834 141 585 408;
  • 61) 0.834 141 585 408 × 2 = 1 + 0.668 283 170 816;
  • 62) 0.668 283 170 816 × 2 = 1 + 0.336 566 341 632;
  • 63) 0.336 566 341 632 × 2 = 0 + 0.673 132 683 264;
  • 64) 0.673 132 683 264 × 2 = 1 + 0.346 265 366 528;

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:


0.000 282 005 858(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1110 1111 1111 1000 1101 0001 1000 1101(2)

6. Positive number before normalization:

0.000 282 005 858(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1110 1111 1111 1000 1101 0001 1000 1101(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:


0.000 282 005 858(10) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1110 1111 1111 1000 1101 0001 1000 1101(2) =


0.0000 0000 0001 0010 0111 1011 0100 0101 1110 1111 1111 1000 1101 0001 1000 1101(2) × 20 =


1.0010 0111 1011 0100 0101 1110 1111 1111 1000 1101 0001 1000 1101(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 0101 1110 1111 1111 1000 1101 0001 1000 1101


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 0101 1110 1111 1111 1000 1101 0001 1000 1101 =


0010 0111 1011 0100 0101 1110 1111 1111 1000 1101 0001 1000 1101


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 0101 1110 1111 1111 1000 1101 0001 1000 1101


Decimal number -0.000 282 005 858 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0101 1110 1111 1111 1000 1101 0001 1000 1101


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