-0.000 282 006 35 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 35(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 35(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 35| = 0.000 282 006 35


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 35.

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 35 × 2 = 0 + 0.000 564 012 7;
  • 2) 0.000 564 012 7 × 2 = 0 + 0.001 128 025 4;
  • 3) 0.001 128 025 4 × 2 = 0 + 0.002 256 050 8;
  • 4) 0.002 256 050 8 × 2 = 0 + 0.004 512 101 6;
  • 5) 0.004 512 101 6 × 2 = 0 + 0.009 024 203 2;
  • 6) 0.009 024 203 2 × 2 = 0 + 0.018 048 406 4;
  • 7) 0.018 048 406 4 × 2 = 0 + 0.036 096 812 8;
  • 8) 0.036 096 812 8 × 2 = 0 + 0.072 193 625 6;
  • 9) 0.072 193 625 6 × 2 = 0 + 0.144 387 251 2;
  • 10) 0.144 387 251 2 × 2 = 0 + 0.288 774 502 4;
  • 11) 0.288 774 502 4 × 2 = 0 + 0.577 549 004 8;
  • 12) 0.577 549 004 8 × 2 = 1 + 0.155 098 009 6;
  • 13) 0.155 098 009 6 × 2 = 0 + 0.310 196 019 2;
  • 14) 0.310 196 019 2 × 2 = 0 + 0.620 392 038 4;
  • 15) 0.620 392 038 4 × 2 = 1 + 0.240 784 076 8;
  • 16) 0.240 784 076 8 × 2 = 0 + 0.481 568 153 6;
  • 17) 0.481 568 153 6 × 2 = 0 + 0.963 136 307 2;
  • 18) 0.963 136 307 2 × 2 = 1 + 0.926 272 614 4;
  • 19) 0.926 272 614 4 × 2 = 1 + 0.852 545 228 8;
  • 20) 0.852 545 228 8 × 2 = 1 + 0.705 090 457 6;
  • 21) 0.705 090 457 6 × 2 = 1 + 0.410 180 915 2;
  • 22) 0.410 180 915 2 × 2 = 0 + 0.820 361 830 4;
  • 23) 0.820 361 830 4 × 2 = 1 + 0.640 723 660 8;
  • 24) 0.640 723 660 8 × 2 = 1 + 0.281 447 321 6;
  • 25) 0.281 447 321 6 × 2 = 0 + 0.562 894 643 2;
  • 26) 0.562 894 643 2 × 2 = 1 + 0.125 789 286 4;
  • 27) 0.125 789 286 4 × 2 = 0 + 0.251 578 572 8;
  • 28) 0.251 578 572 8 × 2 = 0 + 0.503 157 145 6;
  • 29) 0.503 157 145 6 × 2 = 1 + 0.006 314 291 2;
  • 30) 0.006 314 291 2 × 2 = 0 + 0.012 628 582 4;
  • 31) 0.012 628 582 4 × 2 = 0 + 0.025 257 164 8;
  • 32) 0.025 257 164 8 × 2 = 0 + 0.050 514 329 6;
  • 33) 0.050 514 329 6 × 2 = 0 + 0.101 028 659 2;
  • 34) 0.101 028 659 2 × 2 = 0 + 0.202 057 318 4;
  • 35) 0.202 057 318 4 × 2 = 0 + 0.404 114 636 8;
  • 36) 0.404 114 636 8 × 2 = 0 + 0.808 229 273 6;
  • 37) 0.808 229 273 6 × 2 = 1 + 0.616 458 547 2;
  • 38) 0.616 458 547 2 × 2 = 1 + 0.232 917 094 4;
  • 39) 0.232 917 094 4 × 2 = 0 + 0.465 834 188 8;
  • 40) 0.465 834 188 8 × 2 = 0 + 0.931 668 377 6;
  • 41) 0.931 668 377 6 × 2 = 1 + 0.863 336 755 2;
  • 42) 0.863 336 755 2 × 2 = 1 + 0.726 673 510 4;
  • 43) 0.726 673 510 4 × 2 = 1 + 0.453 347 020 8;
  • 44) 0.453 347 020 8 × 2 = 0 + 0.906 694 041 6;
  • 45) 0.906 694 041 6 × 2 = 1 + 0.813 388 083 2;
  • 46) 0.813 388 083 2 × 2 = 1 + 0.626 776 166 4;
  • 47) 0.626 776 166 4 × 2 = 1 + 0.253 552 332 8;
  • 48) 0.253 552 332 8 × 2 = 0 + 0.507 104 665 6;
  • 49) 0.507 104 665 6 × 2 = 1 + 0.014 209 331 2;
  • 50) 0.014 209 331 2 × 2 = 0 + 0.028 418 662 4;
  • 51) 0.028 418 662 4 × 2 = 0 + 0.056 837 324 8;
  • 52) 0.056 837 324 8 × 2 = 0 + 0.113 674 649 6;
  • 53) 0.113 674 649 6 × 2 = 0 + 0.227 349 299 2;
  • 54) 0.227 349 299 2 × 2 = 0 + 0.454 698 598 4;
  • 55) 0.454 698 598 4 × 2 = 0 + 0.909 397 196 8;
  • 56) 0.909 397 196 8 × 2 = 1 + 0.818 794 393 6;
  • 57) 0.818 794 393 6 × 2 = 1 + 0.637 588 787 2;
  • 58) 0.637 588 787 2 × 2 = 1 + 0.275 177 574 4;
  • 59) 0.275 177 574 4 × 2 = 0 + 0.550 355 148 8;
  • 60) 0.550 355 148 8 × 2 = 1 + 0.100 710 297 6;
  • 61) 0.100 710 297 6 × 2 = 0 + 0.201 420 595 2;
  • 62) 0.201 420 595 2 × 2 = 0 + 0.402 841 190 4;
  • 63) 0.402 841 190 4 × 2 = 0 + 0.805 682 380 8;
  • 64) 0.805 682 380 8 × 2 = 1 + 0.611 364 761 6;

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 35(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0000 1100 1110 1110 1000 0001 1101 0001(2)

6. Positive number before normalization:

0.000 282 006 35(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0000 1100 1110 1110 1000 0001 1101 0001(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 35(10) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0000 1100 1110 1110 1000 0001 1101 0001(2) =


0.0000 0000 0001 0010 0111 1011 0100 1000 0000 1100 1110 1110 1000 0001 1101 0001(2) × 20 =


1.0010 0111 1011 0100 1000 0000 1100 1110 1110 1000 0001 1101 0001(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 0000 1100 1110 1110 1000 0001 1101 0001


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 0000 1100 1110 1110 1000 0001 1101 0001 =


0010 0111 1011 0100 1000 0000 1100 1110 1110 1000 0001 1101 0001


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 0000 1100 1110 1110 1000 0001 1101 0001


Decimal number -0.000 282 006 35 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 1000 0000 1100 1110 1110 1000 0001 1101 0001


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