-0.000 282 006 358 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 358(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
-0.000 282 006 358(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:

|-0.000 282 006 358| = 0.000 282 006 358


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: 0.000 282 006 358.

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) 0.000 282 006 358 × 2 = 0 + 0.000 564 012 716;
  • 2) 0.000 564 012 716 × 2 = 0 + 0.001 128 025 432;
  • 3) 0.001 128 025 432 × 2 = 0 + 0.002 256 050 864;
  • 4) 0.002 256 050 864 × 2 = 0 + 0.004 512 101 728;
  • 5) 0.004 512 101 728 × 2 = 0 + 0.009 024 203 456;
  • 6) 0.009 024 203 456 × 2 = 0 + 0.018 048 406 912;
  • 7) 0.018 048 406 912 × 2 = 0 + 0.036 096 813 824;
  • 8) 0.036 096 813 824 × 2 = 0 + 0.072 193 627 648;
  • 9) 0.072 193 627 648 × 2 = 0 + 0.144 387 255 296;
  • 10) 0.144 387 255 296 × 2 = 0 + 0.288 774 510 592;
  • 11) 0.288 774 510 592 × 2 = 0 + 0.577 549 021 184;
  • 12) 0.577 549 021 184 × 2 = 1 + 0.155 098 042 368;
  • 13) 0.155 098 042 368 × 2 = 0 + 0.310 196 084 736;
  • 14) 0.310 196 084 736 × 2 = 0 + 0.620 392 169 472;
  • 15) 0.620 392 169 472 × 2 = 1 + 0.240 784 338 944;
  • 16) 0.240 784 338 944 × 2 = 0 + 0.481 568 677 888;
  • 17) 0.481 568 677 888 × 2 = 0 + 0.963 137 355 776;
  • 18) 0.963 137 355 776 × 2 = 1 + 0.926 274 711 552;
  • 19) 0.926 274 711 552 × 2 = 1 + 0.852 549 423 104;
  • 20) 0.852 549 423 104 × 2 = 1 + 0.705 098 846 208;
  • 21) 0.705 098 846 208 × 2 = 1 + 0.410 197 692 416;
  • 22) 0.410 197 692 416 × 2 = 0 + 0.820 395 384 832;
  • 23) 0.820 395 384 832 × 2 = 1 + 0.640 790 769 664;
  • 24) 0.640 790 769 664 × 2 = 1 + 0.281 581 539 328;
  • 25) 0.281 581 539 328 × 2 = 0 + 0.563 163 078 656;
  • 26) 0.563 163 078 656 × 2 = 1 + 0.126 326 157 312;
  • 27) 0.126 326 157 312 × 2 = 0 + 0.252 652 314 624;
  • 28) 0.252 652 314 624 × 2 = 0 + 0.505 304 629 248;
  • 29) 0.505 304 629 248 × 2 = 1 + 0.010 609 258 496;
  • 30) 0.010 609 258 496 × 2 = 0 + 0.021 218 516 992;
  • 31) 0.021 218 516 992 × 2 = 0 + 0.042 437 033 984;
  • 32) 0.042 437 033 984 × 2 = 0 + 0.084 874 067 968;
  • 33) 0.084 874 067 968 × 2 = 0 + 0.169 748 135 936;
  • 34) 0.169 748 135 936 × 2 = 0 + 0.339 496 271 872;
  • 35) 0.339 496 271 872 × 2 = 0 + 0.678 992 543 744;
  • 36) 0.678 992 543 744 × 2 = 1 + 0.357 985 087 488;
  • 37) 0.357 985 087 488 × 2 = 0 + 0.715 970 174 976;
  • 38) 0.715 970 174 976 × 2 = 1 + 0.431 940 349 952;
  • 39) 0.431 940 349 952 × 2 = 0 + 0.863 880 699 904;
  • 40) 0.863 880 699 904 × 2 = 1 + 0.727 761 399 808;
  • 41) 0.727 761 399 808 × 2 = 1 + 0.455 522 799 616;
  • 42) 0.455 522 799 616 × 2 = 0 + 0.911 045 599 232;
  • 43) 0.911 045 599 232 × 2 = 1 + 0.822 091 198 464;
  • 44) 0.822 091 198 464 × 2 = 1 + 0.644 182 396 928;
  • 45) 0.644 182 396 928 × 2 = 1 + 0.288 364 793 856;
  • 46) 0.288 364 793 856 × 2 = 0 + 0.576 729 587 712;
  • 47) 0.576 729 587 712 × 2 = 1 + 0.153 459 175 424;
  • 48) 0.153 459 175 424 × 2 = 0 + 0.306 918 350 848;
  • 49) 0.306 918 350 848 × 2 = 0 + 0.613 836 701 696;
  • 50) 0.613 836 701 696 × 2 = 1 + 0.227 673 403 392;
  • 51) 0.227 673 403 392 × 2 = 0 + 0.455 346 806 784;
  • 52) 0.455 346 806 784 × 2 = 0 + 0.910 693 613 568;
  • 53) 0.910 693 613 568 × 2 = 1 + 0.821 387 227 136;
  • 54) 0.821 387 227 136 × 2 = 1 + 0.642 774 454 272;
  • 55) 0.642 774 454 272 × 2 = 1 + 0.285 548 908 544;
  • 56) 0.285 548 908 544 × 2 = 0 + 0.571 097 817 088;
  • 57) 0.571 097 817 088 × 2 = 1 + 0.142 195 634 176;
  • 58) 0.142 195 634 176 × 2 = 0 + 0.284 391 268 352;
  • 59) 0.284 391 268 352 × 2 = 0 + 0.568 782 536 704;
  • 60) 0.568 782 536 704 × 2 = 1 + 0.137 565 073 408;
  • 61) 0.137 565 073 408 × 2 = 0 + 0.275 130 146 816;
  • 62) 0.275 130 146 816 × 2 = 0 + 0.550 260 293 632;
  • 63) 0.550 260 293 632 × 2 = 1 + 0.100 520 587 264;
  • 64) 0.100 520 587 264 × 2 = 0 + 0.201 041 174 528;

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:


0.000 282 006 358(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0001 0101 1011 1010 0100 1110 1001 0010(2)

6. Positive number before normalization:

0.000 282 006 358(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0001 0101 1011 1010 0100 1110 1001 0010(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:


0.000 282 006 358(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0001 0101 1011 1010 0100 1110 1001 0010(2) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0001 0101 1011 1010 0100 1110 1001 0010(2) × 20 =


1.0010 0111 1011 0100 1000 0001 0101 1011 1010 0100 1110 1001 0010(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 1000 0001 0101 1011 1010 0100 1110 1001 0010


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 1000 0001 0101 1011 1010 0100 1110 1001 0010 =


0010 0111 1011 0100 1000 0001 0101 1011 1010 0100 1110 1001 0010


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 1000 0001 0101 1011 1010 0100 1110 1001 0010


Decimal number -0.000 282 006 358 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 1000 0001 0101 1011 1010 0100 1110 1001 0010


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