-0.016 738 891 601 562 496 530 553 126 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.016 738 891 601 562 496 530 553 126(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
-0.016 738 891 601 562 496 530 553 126(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:

|-0.016 738 891 601 562 496 530 553 126| = 0.016 738 891 601 562 496 530 553 126


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: 0.016 738 891 601 562 496 530 553 126.

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) 0.016 738 891 601 562 496 530 553 126 × 2 = 0 + 0.033 477 783 203 124 993 061 106 252;
  • 2) 0.033 477 783 203 124 993 061 106 252 × 2 = 0 + 0.066 955 566 406 249 986 122 212 504;
  • 3) 0.066 955 566 406 249 986 122 212 504 × 2 = 0 + 0.133 911 132 812 499 972 244 425 008;
  • 4) 0.133 911 132 812 499 972 244 425 008 × 2 = 0 + 0.267 822 265 624 999 944 488 850 016;
  • 5) 0.267 822 265 624 999 944 488 850 016 × 2 = 0 + 0.535 644 531 249 999 888 977 700 032;
  • 6) 0.535 644 531 249 999 888 977 700 032 × 2 = 1 + 0.071 289 062 499 999 777 955 400 064;
  • 7) 0.071 289 062 499 999 777 955 400 064 × 2 = 0 + 0.142 578 124 999 999 555 910 800 128;
  • 8) 0.142 578 124 999 999 555 910 800 128 × 2 = 0 + 0.285 156 249 999 999 111 821 600 256;
  • 9) 0.285 156 249 999 999 111 821 600 256 × 2 = 0 + 0.570 312 499 999 998 223 643 200 512;
  • 10) 0.570 312 499 999 998 223 643 200 512 × 2 = 1 + 0.140 624 999 999 996 447 286 401 024;
  • 11) 0.140 624 999 999 996 447 286 401 024 × 2 = 0 + 0.281 249 999 999 992 894 572 802 048;
  • 12) 0.281 249 999 999 992 894 572 802 048 × 2 = 0 + 0.562 499 999 999 985 789 145 604 096;
  • 13) 0.562 499 999 999 985 789 145 604 096 × 2 = 1 + 0.124 999 999 999 971 578 291 208 192;
  • 14) 0.124 999 999 999 971 578 291 208 192 × 2 = 0 + 0.249 999 999 999 943 156 582 416 384;
  • 15) 0.249 999 999 999 943 156 582 416 384 × 2 = 0 + 0.499 999 999 999 886 313 164 832 768;
  • 16) 0.499 999 999 999 886 313 164 832 768 × 2 = 0 + 0.999 999 999 999 772 626 329 665 536;
  • 17) 0.999 999 999 999 772 626 329 665 536 × 2 = 1 + 0.999 999 999 999 545 252 659 331 072;
  • 18) 0.999 999 999 999 545 252 659 331 072 × 2 = 1 + 0.999 999 999 999 090 505 318 662 144;
  • 19) 0.999 999 999 999 090 505 318 662 144 × 2 = 1 + 0.999 999 999 998 181 010 637 324 288;
  • 20) 0.999 999 999 998 181 010 637 324 288 × 2 = 1 + 0.999 999 999 996 362 021 274 648 576;
  • 21) 0.999 999 999 996 362 021 274 648 576 × 2 = 1 + 0.999 999 999 992 724 042 549 297 152;
  • 22) 0.999 999 999 992 724 042 549 297 152 × 2 = 1 + 0.999 999 999 985 448 085 098 594 304;
  • 23) 0.999 999 999 985 448 085 098 594 304 × 2 = 1 + 0.999 999 999 970 896 170 197 188 608;
  • 24) 0.999 999 999 970 896 170 197 188 608 × 2 = 1 + 0.999 999 999 941 792 340 394 377 216;
  • 25) 0.999 999 999 941 792 340 394 377 216 × 2 = 1 + 0.999 999 999 883 584 680 788 754 432;
  • 26) 0.999 999 999 883 584 680 788 754 432 × 2 = 1 + 0.999 999 999 767 169 361 577 508 864;
  • 27) 0.999 999 999 767 169 361 577 508 864 × 2 = 1 + 0.999 999 999 534 338 723 155 017 728;
  • 28) 0.999 999 999 534 338 723 155 017 728 × 2 = 1 + 0.999 999 999 068 677 446 310 035 456;
  • 29) 0.999 999 999 068 677 446 310 035 456 × 2 = 1 + 0.999 999 998 137 354 892 620 070 912;
  • 30) 0.999 999 998 137 354 892 620 070 912 × 2 = 1 + 0.999 999 996 274 709 785 240 141 824;
  • 31) 0.999 999 996 274 709 785 240 141 824 × 2 = 1 + 0.999 999 992 549 419 570 480 283 648;
  • 32) 0.999 999 992 549 419 570 480 283 648 × 2 = 1 + 0.999 999 985 098 839 140 960 567 296;
  • 33) 0.999 999 985 098 839 140 960 567 296 × 2 = 1 + 0.999 999 970 197 678 281 921 134 592;
  • 34) 0.999 999 970 197 678 281 921 134 592 × 2 = 1 + 0.999 999 940 395 356 563 842 269 184;
  • 35) 0.999 999 940 395 356 563 842 269 184 × 2 = 1 + 0.999 999 880 790 713 127 684 538 368;
  • 36) 0.999 999 880 790 713 127 684 538 368 × 2 = 1 + 0.999 999 761 581 426 255 369 076 736;
  • 37) 0.999 999 761 581 426 255 369 076 736 × 2 = 1 + 0.999 999 523 162 852 510 738 153 472;
  • 38) 0.999 999 523 162 852 510 738 153 472 × 2 = 1 + 0.999 999 046 325 705 021 476 306 944;
  • 39) 0.999 999 046 325 705 021 476 306 944 × 2 = 1 + 0.999 998 092 651 410 042 952 613 888;
  • 40) 0.999 998 092 651 410 042 952 613 888 × 2 = 1 + 0.999 996 185 302 820 085 905 227 776;
  • 41) 0.999 996 185 302 820 085 905 227 776 × 2 = 1 + 0.999 992 370 605 640 171 810 455 552;
  • 42) 0.999 992 370 605 640 171 810 455 552 × 2 = 1 + 0.999 984 741 211 280 343 620 911 104;
  • 43) 0.999 984 741 211 280 343 620 911 104 × 2 = 1 + 0.999 969 482 422 560 687 241 822 208;
  • 44) 0.999 969 482 422 560 687 241 822 208 × 2 = 1 + 0.999 938 964 845 121 374 483 644 416;
  • 45) 0.999 938 964 845 121 374 483 644 416 × 2 = 1 + 0.999 877 929 690 242 748 967 288 832;
  • 46) 0.999 877 929 690 242 748 967 288 832 × 2 = 1 + 0.999 755 859 380 485 497 934 577 664;
  • 47) 0.999 755 859 380 485 497 934 577 664 × 2 = 1 + 0.999 511 718 760 970 995 869 155 328;
  • 48) 0.999 511 718 760 970 995 869 155 328 × 2 = 1 + 0.999 023 437 521 941 991 738 310 656;
  • 49) 0.999 023 437 521 941 991 738 310 656 × 2 = 1 + 0.998 046 875 043 883 983 476 621 312;
  • 50) 0.998 046 875 043 883 983 476 621 312 × 2 = 1 + 0.996 093 750 087 767 966 953 242 624;
  • 51) 0.996 093 750 087 767 966 953 242 624 × 2 = 1 + 0.992 187 500 175 535 933 906 485 248;
  • 52) 0.992 187 500 175 535 933 906 485 248 × 2 = 1 + 0.984 375 000 351 071 867 812 970 496;
  • 53) 0.984 375 000 351 071 867 812 970 496 × 2 = 1 + 0.968 750 000 702 143 735 625 940 992;
  • 54) 0.968 750 000 702 143 735 625 940 992 × 2 = 1 + 0.937 500 001 404 287 471 251 881 984;
  • 55) 0.937 500 001 404 287 471 251 881 984 × 2 = 1 + 0.875 000 002 808 574 942 503 763 968;
  • 56) 0.875 000 002 808 574 942 503 763 968 × 2 = 1 + 0.750 000 005 617 149 885 007 527 936;
  • 57) 0.750 000 005 617 149 885 007 527 936 × 2 = 1 + 0.500 000 011 234 299 770 015 055 872;
  • 58) 0.500 000 011 234 299 770 015 055 872 × 2 = 1 + 0.000 000 022 468 599 540 030 111 744;

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:


0.016 738 891 601 562 496 530 553 126(10) =

0.0000 0100 0100 1000 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 11(2)

6. Positive number before normalization:

0.016 738 891 601 562 496 530 553 126(10) =

0.0000 0100 0100 1000 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 11(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 6 positions to the right, so that only one non zero digit remains to the left of it:


0.016 738 891 601 562 496 530 553 126(10) =

0.0000 0100 0100 1000 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 11(2) =

0.0000 0100 0100 1000 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 11(2) × 20 =

1.0001 0010 0011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111(2) × 2-6


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): -6

Mantissa (not normalized):
1.0001 0010 0011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =

Exponent (unadjusted) + 2(11-1) - 1 =

-6 + 2(11-1) - 1 =

(-6 + 1 023)(10) =

1 017(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;
  • 1 017 ÷ 2 = 508 + 1;
  • 508 ÷ 2 = 254 + 0;
  • 254 ÷ 2 = 127 + 0;
  • 127 ÷ 2 = 63 + 1;
  • 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) =

1017(10) =

011 1111 1001(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. 0001 0010 0011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 =

0001 0010 0011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111


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 1001

Mantissa (52 bits) =
0001 0010 0011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111


Decimal number -0.016 738 891 601 562 496 530 553 126 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1001 - 0001 0010 0011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111

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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