-0.000 282 005 596 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 005 596(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
-0.000 282 005 596(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:

|-0.000 282 005 596| = 0.000 282 005 596


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: 0.000 282 005 596.

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) 0.000 282 005 596 × 2 = 0 + 0.000 564 011 192;
  • 2) 0.000 564 011 192 × 2 = 0 + 0.001 128 022 384;
  • 3) 0.001 128 022 384 × 2 = 0 + 0.002 256 044 768;
  • 4) 0.002 256 044 768 × 2 = 0 + 0.004 512 089 536;
  • 5) 0.004 512 089 536 × 2 = 0 + 0.009 024 179 072;
  • 6) 0.009 024 179 072 × 2 = 0 + 0.018 048 358 144;
  • 7) 0.018 048 358 144 × 2 = 0 + 0.036 096 716 288;
  • 8) 0.036 096 716 288 × 2 = 0 + 0.072 193 432 576;
  • 9) 0.072 193 432 576 × 2 = 0 + 0.144 386 865 152;
  • 10) 0.144 386 865 152 × 2 = 0 + 0.288 773 730 304;
  • 11) 0.288 773 730 304 × 2 = 0 + 0.577 547 460 608;
  • 12) 0.577 547 460 608 × 2 = 1 + 0.155 094 921 216;
  • 13) 0.155 094 921 216 × 2 = 0 + 0.310 189 842 432;
  • 14) 0.310 189 842 432 × 2 = 0 + 0.620 379 684 864;
  • 15) 0.620 379 684 864 × 2 = 1 + 0.240 759 369 728;
  • 16) 0.240 759 369 728 × 2 = 0 + 0.481 518 739 456;
  • 17) 0.481 518 739 456 × 2 = 0 + 0.963 037 478 912;
  • 18) 0.963 037 478 912 × 2 = 1 + 0.926 074 957 824;
  • 19) 0.926 074 957 824 × 2 = 1 + 0.852 149 915 648;
  • 20) 0.852 149 915 648 × 2 = 1 + 0.704 299 831 296;
  • 21) 0.704 299 831 296 × 2 = 1 + 0.408 599 662 592;
  • 22) 0.408 599 662 592 × 2 = 0 + 0.817 199 325 184;
  • 23) 0.817 199 325 184 × 2 = 1 + 0.634 398 650 368;
  • 24) 0.634 398 650 368 × 2 = 1 + 0.268 797 300 736;
  • 25) 0.268 797 300 736 × 2 = 0 + 0.537 594 601 472;
  • 26) 0.537 594 601 472 × 2 = 1 + 0.075 189 202 944;
  • 27) 0.075 189 202 944 × 2 = 0 + 0.150 378 405 888;
  • 28) 0.150 378 405 888 × 2 = 0 + 0.300 756 811 776;
  • 29) 0.300 756 811 776 × 2 = 0 + 0.601 513 623 552;
  • 30) 0.601 513 623 552 × 2 = 1 + 0.203 027 247 104;
  • 31) 0.203 027 247 104 × 2 = 0 + 0.406 054 494 208;
  • 32) 0.406 054 494 208 × 2 = 0 + 0.812 108 988 416;
  • 33) 0.812 108 988 416 × 2 = 1 + 0.624 217 976 832;
  • 34) 0.624 217 976 832 × 2 = 1 + 0.248 435 953 664;
  • 35) 0.248 435 953 664 × 2 = 0 + 0.496 871 907 328;
  • 36) 0.496 871 907 328 × 2 = 0 + 0.993 743 814 656;
  • 37) 0.993 743 814 656 × 2 = 1 + 0.987 487 629 312;
  • 38) 0.987 487 629 312 × 2 = 1 + 0.974 975 258 624;
  • 39) 0.974 975 258 624 × 2 = 1 + 0.949 950 517 248;
  • 40) 0.949 950 517 248 × 2 = 1 + 0.899 901 034 496;
  • 41) 0.899 901 034 496 × 2 = 1 + 0.799 802 068 992;
  • 42) 0.799 802 068 992 × 2 = 1 + 0.599 604 137 984;
  • 43) 0.599 604 137 984 × 2 = 1 + 0.199 208 275 968;
  • 44) 0.199 208 275 968 × 2 = 0 + 0.398 416 551 936;
  • 45) 0.398 416 551 936 × 2 = 0 + 0.796 833 103 872;
  • 46) 0.796 833 103 872 × 2 = 1 + 0.593 666 207 744;
  • 47) 0.593 666 207 744 × 2 = 1 + 0.187 332 415 488;
  • 48) 0.187 332 415 488 × 2 = 0 + 0.374 664 830 976;
  • 49) 0.374 664 830 976 × 2 = 0 + 0.749 329 661 952;
  • 50) 0.749 329 661 952 × 2 = 1 + 0.498 659 323 904;
  • 51) 0.498 659 323 904 × 2 = 0 + 0.997 318 647 808;
  • 52) 0.997 318 647 808 × 2 = 1 + 0.994 637 295 616;
  • 53) 0.994 637 295 616 × 2 = 1 + 0.989 274 591 232;
  • 54) 0.989 274 591 232 × 2 = 1 + 0.978 549 182 464;
  • 55) 0.978 549 182 464 × 2 = 1 + 0.957 098 364 928;
  • 56) 0.957 098 364 928 × 2 = 1 + 0.914 196 729 856;
  • 57) 0.914 196 729 856 × 2 = 1 + 0.828 393 459 712;
  • 58) 0.828 393 459 712 × 2 = 1 + 0.656 786 919 424;
  • 59) 0.656 786 919 424 × 2 = 1 + 0.313 573 838 848;
  • 60) 0.313 573 838 848 × 2 = 0 + 0.627 147 677 696;
  • 61) 0.627 147 677 696 × 2 = 1 + 0.254 295 355 392;
  • 62) 0.254 295 355 392 × 2 = 0 + 0.508 590 710 784;
  • 63) 0.508 590 710 784 × 2 = 1 + 0.017 181 421 568;
  • 64) 0.017 181 421 568 × 2 = 0 + 0.034 362 843 136;

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:


0.000 282 005 596(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1100 1111 1110 0110 0101 1111 1110 1010(2)

6. Positive number before normalization:

0.000 282 005 596(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1100 1111 1110 0110 0101 1111 1110 1010(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:


0.000 282 005 596(10) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1100 1111 1110 0110 0101 1111 1110 1010(2) =


0.0000 0000 0001 0010 0111 1011 0100 0100 1100 1111 1110 0110 0101 1111 1110 1010(2) × 20 =


1.0010 0111 1011 0100 0100 1100 1111 1110 0110 0101 1111 1110 1010(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 0100 1100 1111 1110 0110 0101 1111 1110 1010


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 0100 1100 1111 1110 0110 0101 1111 1110 1010 =


0010 0111 1011 0100 0100 1100 1111 1110 0110 0101 1111 1110 1010


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 0100 1100 1111 1110 0110 0101 1111 1110 1010


Decimal number -0.000 282 005 596 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0100 1100 1111 1110 0110 0101 1111 1110 1010


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