-0.000 282 006 182 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 182(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
-0.000 282 006 182(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:

|-0.000 282 006 182| = 0.000 282 006 182


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: 0.000 282 006 182.

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) 0.000 282 006 182 × 2 = 0 + 0.000 564 012 364;
  • 2) 0.000 564 012 364 × 2 = 0 + 0.001 128 024 728;
  • 3) 0.001 128 024 728 × 2 = 0 + 0.002 256 049 456;
  • 4) 0.002 256 049 456 × 2 = 0 + 0.004 512 098 912;
  • 5) 0.004 512 098 912 × 2 = 0 + 0.009 024 197 824;
  • 6) 0.009 024 197 824 × 2 = 0 + 0.018 048 395 648;
  • 7) 0.018 048 395 648 × 2 = 0 + 0.036 096 791 296;
  • 8) 0.036 096 791 296 × 2 = 0 + 0.072 193 582 592;
  • 9) 0.072 193 582 592 × 2 = 0 + 0.144 387 165 184;
  • 10) 0.144 387 165 184 × 2 = 0 + 0.288 774 330 368;
  • 11) 0.288 774 330 368 × 2 = 0 + 0.577 548 660 736;
  • 12) 0.577 548 660 736 × 2 = 1 + 0.155 097 321 472;
  • 13) 0.155 097 321 472 × 2 = 0 + 0.310 194 642 944;
  • 14) 0.310 194 642 944 × 2 = 0 + 0.620 389 285 888;
  • 15) 0.620 389 285 888 × 2 = 1 + 0.240 778 571 776;
  • 16) 0.240 778 571 776 × 2 = 0 + 0.481 557 143 552;
  • 17) 0.481 557 143 552 × 2 = 0 + 0.963 114 287 104;
  • 18) 0.963 114 287 104 × 2 = 1 + 0.926 228 574 208;
  • 19) 0.926 228 574 208 × 2 = 1 + 0.852 457 148 416;
  • 20) 0.852 457 148 416 × 2 = 1 + 0.704 914 296 832;
  • 21) 0.704 914 296 832 × 2 = 1 + 0.409 828 593 664;
  • 22) 0.409 828 593 664 × 2 = 0 + 0.819 657 187 328;
  • 23) 0.819 657 187 328 × 2 = 1 + 0.639 314 374 656;
  • 24) 0.639 314 374 656 × 2 = 1 + 0.278 628 749 312;
  • 25) 0.278 628 749 312 × 2 = 0 + 0.557 257 498 624;
  • 26) 0.557 257 498 624 × 2 = 1 + 0.114 514 997 248;
  • 27) 0.114 514 997 248 × 2 = 0 + 0.229 029 994 496;
  • 28) 0.229 029 994 496 × 2 = 0 + 0.458 059 988 992;
  • 29) 0.458 059 988 992 × 2 = 0 + 0.916 119 977 984;
  • 30) 0.916 119 977 984 × 2 = 1 + 0.832 239 955 968;
  • 31) 0.832 239 955 968 × 2 = 1 + 0.664 479 911 936;
  • 32) 0.664 479 911 936 × 2 = 1 + 0.328 959 823 872;
  • 33) 0.328 959 823 872 × 2 = 0 + 0.657 919 647 744;
  • 34) 0.657 919 647 744 × 2 = 1 + 0.315 839 295 488;
  • 35) 0.315 839 295 488 × 2 = 0 + 0.631 678 590 976;
  • 36) 0.631 678 590 976 × 2 = 1 + 0.263 357 181 952;
  • 37) 0.263 357 181 952 × 2 = 0 + 0.526 714 363 904;
  • 38) 0.526 714 363 904 × 2 = 1 + 0.053 428 727 808;
  • 39) 0.053 428 727 808 × 2 = 0 + 0.106 857 455 616;
  • 40) 0.106 857 455 616 × 2 = 0 + 0.213 714 911 232;
  • 41) 0.213 714 911 232 × 2 = 0 + 0.427 429 822 464;
  • 42) 0.427 429 822 464 × 2 = 0 + 0.854 859 644 928;
  • 43) 0.854 859 644 928 × 2 = 1 + 0.709 719 289 856;
  • 44) 0.709 719 289 856 × 2 = 1 + 0.419 438 579 712;
  • 45) 0.419 438 579 712 × 2 = 0 + 0.838 877 159 424;
  • 46) 0.838 877 159 424 × 2 = 1 + 0.677 754 318 848;
  • 47) 0.677 754 318 848 × 2 = 1 + 0.355 508 637 696;
  • 48) 0.355 508 637 696 × 2 = 0 + 0.711 017 275 392;
  • 49) 0.711 017 275 392 × 2 = 1 + 0.422 034 550 784;
  • 50) 0.422 034 550 784 × 2 = 0 + 0.844 069 101 568;
  • 51) 0.844 069 101 568 × 2 = 1 + 0.688 138 203 136;
  • 52) 0.688 138 203 136 × 2 = 1 + 0.376 276 406 272;
  • 53) 0.376 276 406 272 × 2 = 0 + 0.752 552 812 544;
  • 54) 0.752 552 812 544 × 2 = 1 + 0.505 105 625 088;
  • 55) 0.505 105 625 088 × 2 = 1 + 0.010 211 250 176;
  • 56) 0.010 211 250 176 × 2 = 0 + 0.020 422 500 352;
  • 57) 0.020 422 500 352 × 2 = 0 + 0.040 845 000 704;
  • 58) 0.040 845 000 704 × 2 = 0 + 0.081 690 001 408;
  • 59) 0.081 690 001 408 × 2 = 0 + 0.163 380 002 816;
  • 60) 0.163 380 002 816 × 2 = 0 + 0.326 760 005 632;
  • 61) 0.326 760 005 632 × 2 = 0 + 0.653 520 011 264;
  • 62) 0.653 520 011 264 × 2 = 1 + 0.307 040 022 528;
  • 63) 0.307 040 022 528 × 2 = 0 + 0.614 080 045 056;
  • 64) 0.614 080 045 056 × 2 = 1 + 0.228 160 090 112;

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:


0.000 282 006 182(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 0101 0100 0011 0110 1011 0110 0000 0101(2)

6. Positive number before normalization:

0.000 282 006 182(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 0101 0100 0011 0110 1011 0110 0000 0101(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:


0.000 282 006 182(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 0101 0100 0011 0110 1011 0110 0000 0101(2) =


0.0000 0000 0001 0010 0111 1011 0100 0111 0101 0100 0011 0110 1011 0110 0000 0101(2) × 20 =


1.0010 0111 1011 0100 0111 0101 0100 0011 0110 1011 0110 0000 0101(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 0101 0100 0011 0110 1011 0110 0000 0101


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 0101 0100 0011 0110 1011 0110 0000 0101 =


0010 0111 1011 0100 0111 0101 0100 0011 0110 1011 0110 0000 0101


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 0101 0100 0011 0110 1011 0110 0000 0101


Decimal number -0.000 282 006 182 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0111 0101 0100 0011 0110 1011 0110 0000 0101


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