-0.000 282 006 198 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 198(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
-0.000 282 006 198(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:

|-0.000 282 006 198| = 0.000 282 006 198


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: 0.000 282 006 198.

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) 0.000 282 006 198 × 2 = 0 + 0.000 564 012 396;
  • 2) 0.000 564 012 396 × 2 = 0 + 0.001 128 024 792;
  • 3) 0.001 128 024 792 × 2 = 0 + 0.002 256 049 584;
  • 4) 0.002 256 049 584 × 2 = 0 + 0.004 512 099 168;
  • 5) 0.004 512 099 168 × 2 = 0 + 0.009 024 198 336;
  • 6) 0.009 024 198 336 × 2 = 0 + 0.018 048 396 672;
  • 7) 0.018 048 396 672 × 2 = 0 + 0.036 096 793 344;
  • 8) 0.036 096 793 344 × 2 = 0 + 0.072 193 586 688;
  • 9) 0.072 193 586 688 × 2 = 0 + 0.144 387 173 376;
  • 10) 0.144 387 173 376 × 2 = 0 + 0.288 774 346 752;
  • 11) 0.288 774 346 752 × 2 = 0 + 0.577 548 693 504;
  • 12) 0.577 548 693 504 × 2 = 1 + 0.155 097 387 008;
  • 13) 0.155 097 387 008 × 2 = 0 + 0.310 194 774 016;
  • 14) 0.310 194 774 016 × 2 = 0 + 0.620 389 548 032;
  • 15) 0.620 389 548 032 × 2 = 1 + 0.240 779 096 064;
  • 16) 0.240 779 096 064 × 2 = 0 + 0.481 558 192 128;
  • 17) 0.481 558 192 128 × 2 = 0 + 0.963 116 384 256;
  • 18) 0.963 116 384 256 × 2 = 1 + 0.926 232 768 512;
  • 19) 0.926 232 768 512 × 2 = 1 + 0.852 465 537 024;
  • 20) 0.852 465 537 024 × 2 = 1 + 0.704 931 074 048;
  • 21) 0.704 931 074 048 × 2 = 1 + 0.409 862 148 096;
  • 22) 0.409 862 148 096 × 2 = 0 + 0.819 724 296 192;
  • 23) 0.819 724 296 192 × 2 = 1 + 0.639 448 592 384;
  • 24) 0.639 448 592 384 × 2 = 1 + 0.278 897 184 768;
  • 25) 0.278 897 184 768 × 2 = 0 + 0.557 794 369 536;
  • 26) 0.557 794 369 536 × 2 = 1 + 0.115 588 739 072;
  • 27) 0.115 588 739 072 × 2 = 0 + 0.231 177 478 144;
  • 28) 0.231 177 478 144 × 2 = 0 + 0.462 354 956 288;
  • 29) 0.462 354 956 288 × 2 = 0 + 0.924 709 912 576;
  • 30) 0.924 709 912 576 × 2 = 1 + 0.849 419 825 152;
  • 31) 0.849 419 825 152 × 2 = 1 + 0.698 839 650 304;
  • 32) 0.698 839 650 304 × 2 = 1 + 0.397 679 300 608;
  • 33) 0.397 679 300 608 × 2 = 0 + 0.795 358 601 216;
  • 34) 0.795 358 601 216 × 2 = 1 + 0.590 717 202 432;
  • 35) 0.590 717 202 432 × 2 = 1 + 0.181 434 404 864;
  • 36) 0.181 434 404 864 × 2 = 0 + 0.362 868 809 728;
  • 37) 0.362 868 809 728 × 2 = 0 + 0.725 737 619 456;
  • 38) 0.725 737 619 456 × 2 = 1 + 0.451 475 238 912;
  • 39) 0.451 475 238 912 × 2 = 0 + 0.902 950 477 824;
  • 40) 0.902 950 477 824 × 2 = 1 + 0.805 900 955 648;
  • 41) 0.805 900 955 648 × 2 = 1 + 0.611 801 911 296;
  • 42) 0.611 801 911 296 × 2 = 1 + 0.223 603 822 592;
  • 43) 0.223 603 822 592 × 2 = 0 + 0.447 207 645 184;
  • 44) 0.447 207 645 184 × 2 = 0 + 0.894 415 290 368;
  • 45) 0.894 415 290 368 × 2 = 1 + 0.788 830 580 736;
  • 46) 0.788 830 580 736 × 2 = 1 + 0.577 661 161 472;
  • 47) 0.577 661 161 472 × 2 = 1 + 0.155 322 322 944;
  • 48) 0.155 322 322 944 × 2 = 0 + 0.310 644 645 888;
  • 49) 0.310 644 645 888 × 2 = 0 + 0.621 289 291 776;
  • 50) 0.621 289 291 776 × 2 = 1 + 0.242 578 583 552;
  • 51) 0.242 578 583 552 × 2 = 0 + 0.485 157 167 104;
  • 52) 0.485 157 167 104 × 2 = 0 + 0.970 314 334 208;
  • 53) 0.970 314 334 208 × 2 = 1 + 0.940 628 668 416;
  • 54) 0.940 628 668 416 × 2 = 1 + 0.881 257 336 832;
  • 55) 0.881 257 336 832 × 2 = 1 + 0.762 514 673 664;
  • 56) 0.762 514 673 664 × 2 = 1 + 0.525 029 347 328;
  • 57) 0.525 029 347 328 × 2 = 1 + 0.050 058 694 656;
  • 58) 0.050 058 694 656 × 2 = 0 + 0.100 117 389 312;
  • 59) 0.100 117 389 312 × 2 = 0 + 0.200 234 778 624;
  • 60) 0.200 234 778 624 × 2 = 0 + 0.400 469 557 248;
  • 61) 0.400 469 557 248 × 2 = 0 + 0.800 939 114 496;
  • 62) 0.800 939 114 496 × 2 = 1 + 0.601 878 228 992;
  • 63) 0.601 878 228 992 × 2 = 1 + 0.203 756 457 984;
  • 64) 0.203 756 457 984 × 2 = 0 + 0.407 512 915 968;

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:


0.000 282 006 198(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 0110 0101 1100 1110 0100 1111 1000 0110(2)

6. Positive number before normalization:

0.000 282 006 198(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 0110 0101 1100 1110 0100 1111 1000 0110(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:


0.000 282 006 198(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 0110 0101 1100 1110 0100 1111 1000 0110(2) =


0.0000 0000 0001 0010 0111 1011 0100 0111 0110 0101 1100 1110 0100 1111 1000 0110(2) × 20 =


1.0010 0111 1011 0100 0111 0110 0101 1100 1110 0100 1111 1000 0110(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 0110 0101 1100 1110 0100 1111 1000 0110


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 0110 0101 1100 1110 0100 1111 1000 0110 =


0010 0111 1011 0100 0111 0110 0101 1100 1110 0100 1111 1000 0110


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 0110 0101 1100 1110 0100 1111 1000 0110


Decimal number -0.000 282 006 198 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0111 0110 0101 1100 1110 0100 1111 1000 0110


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