64 bit double precision IEEE 754 binary floating point number 1 - 101 1000 0000 - 0011 1100 0001 0111 0010 0100 0111 0100 0101 0011 1000 1110 0010 converted to decimal base ten (double)

64 bit double precision IEEE 754 binary floating point 1 - 101 1000 0000 - 0011 1100 0001 0111 0010 0100 0111 0100 0101 0011 1000 1110 0010 to decimal system (base ten) = ?

1. Identify the elements that make up the binary representation of the number:

The first bit (the leftmost) indicates the sign,

1 = negative, 0 = positive.
1


The next 11 bits contain the exponent:
101 1000 0000


The last 52 bits contain the mantissa:
0011 1100 0001 0111 0010 0100 0111 0100 0101 0011 1000 1110 0010


2. Convert the exponent from binary (base 2) to decimal (base 10):

The exponent is allways a positive integer.

101 1000 0000(2) =


1 × 210 + 0 × 29 + 1 × 28 + 1 × 27 + 0 × 26 + 0 × 25 + 0 × 24 + 0 × 23 + 0 × 22 + 0 × 21 + 0 × 20 =


1,024 + 0 + 256 + 128 + 0 + 0 + 0 + 0 + 0 + 0 + 0 =


1,024 + 256 + 128 =


1,408(10)

3. Adjust the exponent.

Subtract the excess bits: 2(11 - 1) - 1 = 1023,

that is due to the 11 bit excess/bias notation.


Exponent adjusted = 1,408 - 1023 = 385


4. Convert the mantissa from binary (base 2) to decimal (base 10):

Mantissa represents the number's fractional part (the excess beyond the number's integer part, comma delimited).


0011 1100 0001 0111 0010 0100 0111 0100 0101 0011 1000 1110 0010(2) =

0 × 2-1 + 0 × 2-2 + 1 × 2-3 + 1 × 2-4 + 1 × 2-5 + 1 × 2-6 + 0 × 2-7 + 0 × 2-8 + 0 × 2-9 + 0 × 2-10 + 0 × 2-11 + 1 × 2-12 + 0 × 2-13 + 1 × 2-14 + 1 × 2-15 + 1 × 2-16 + 0 × 2-17 + 0 × 2-18 + 1 × 2-19 + 0 × 2-20 + 0 × 2-21 + 1 × 2-22 + 0 × 2-23 + 0 × 2-24 + 0 × 2-25 + 1 × 2-26 + 1 × 2-27 + 1 × 2-28 + 0 × 2-29 + 1 × 2-30 + 0 × 2-31 + 0 × 2-32 + 0 × 2-33 + 1 × 2-34 + 0 × 2-35 + 1 × 2-36 + 0 × 2-37 + 0 × 2-38 + 1 × 2-39 + 1 × 2-40 + 1 × 2-41 + 0 × 2-42 + 0 × 2-43 + 0 × 2-44 + 1 × 2-45 + 1 × 2-46 + 1 × 2-47 + 0 × 2-48 + 0 × 2-49 + 0 × 2-50 + 1 × 2-51 + 0 × 2-52 =


0 + 0 + 0.125 + 0.062 5 + 0.031 25 + 0.015 625 + 0 + 0 + 0 + 0 + 0 + 0.000 244 140 625 + 0 + 0.000 061 035 156 25 + 0.000 030 517 578 125 + 0.000 015 258 789 062 5 + 0 + 0 + 0.000 001 907 348 632 812 5 + 0 + 0 + 0.000 000 238 418 579 101 562 5 + 0 + 0 + 0 + 0.000 000 014 901 161 193 847 656 25 + 0.000 000 007 450 580 596 923 828 125 + 0.000 000 003 725 290 298 461 914 062 5 + 0 + 0.000 000 000 931 322 574 615 478 515 625 + 0 + 0 + 0 + 0.000 000 000 058 207 660 913 467 407 226 562 5 + 0 + 0.000 000 000 014 551 915 228 366 851 806 640 625 + 0 + 0 + 0.000 000 000 001 818 989 403 545 856 475 830 078 125 + 0.000 000 000 000 909 494 701 772 928 237 915 039 062 5 + 0.000 000 000 000 454 747 350 886 464 118 957 519 531 25 + 0 + 0 + 0 + 0.000 000 000 000 028 421 709 430 404 007 434 844 970 703 125 + 0.000 000 000 000 014 210 854 715 202 003 717 422 485 351 562 5 + 0.000 000 000 000 007 105 427 357 601 001 858 711 242 675 781 25 + 0 + 0 + 0 + 0.000 000 000 000 000 444 089 209 850 062 616 169 452 667 236 328 125 + 0 =


0.125 + 0.062 5 + 0.031 25 + 0.015 625 + 0.000 244 140 625 + 0.000 061 035 156 25 + 0.000 030 517 578 125 + 0.000 015 258 789 062 5 + 0.000 001 907 348 632 812 5 + 0.000 000 238 418 579 101 562 5 + 0.000 000 014 901 161 193 847 656 25 + 0.000 000 007 450 580 596 923 828 125 + 0.000 000 003 725 290 298 461 914 062 5 + 0.000 000 000 931 322 574 615 478 515 625 + 0.000 000 000 058 207 660 913 467 407 226 562 5 + 0.000 000 000 014 551 915 228 366 851 806 640 625 + 0.000 000 000 001 818 989 403 545 856 475 830 078 125 + 0.000 000 000 000 909 494 701 772 928 237 915 039 062 5 + 0.000 000 000 000 454 747 350 886 464 118 957 519 531 25 + 0.000 000 000 000 028 421 709 430 404 007 434 844 970 703 125 + 0.000 000 000 000 014 210 854 715 202 003 717 422 485 351 562 5 + 0.000 000 000 000 007 105 427 357 601 001 858 711 242 675 781 25 + 0.000 000 000 000 000 444 089 209 850 062 616 169 452 667 236 328 125 =


0.234 728 124 999 997 067 590 129 518 066 532 909 870 147 705 078 125(10)

5. Put all the numbers into expression to calculate the double precision floating point decimal value:

(-1)Sign × (1 + Mantissa) × 2(Exponent adjusted) =


(-1)1 × (1 + 0.234 728 124 999 997 067 590 129 518 066 532 909 870 147 705 078 125) × 2385 =


-1.234 728 124 999 997 067 590 129 518 066 532 909 870 147 705 078 125 × 2385 =


-97 301 530 464 224 843 070 593 778 124 350 848 744 433 146 240 582 942 482 432 410 638 982 610 858 009 366 662 696 972 129 184 108 287 877 314 234 023 936

1 - 101 1000 0000 - 0011 1100 0001 0111 0010 0100 0111 0100 0101 0011 1000 1110 0010 converted from 64 bit double precision IEEE 754 binary floating point to base ten decimal system (double) =
-97 301 530 464 224 843 070 593 778 124 350 848 744 433 146 240 582 942 482 432 410 638 982 610 858 009 366 662 696 972 129 184 108 287 877 314 234 023 936(10)

More operations of this kind:

1 - 101 1000 0000 - 0011 1100 0001 0111 0010 0100 0111 0100 0101 0011 1000 1110 0001 = ?

1 - 101 1000 0000 - 0011 1100 0001 0111 0010 0100 0111 0100 0101 0011 1000 1110 0011 = ?


Convert 64 bit double precision IEEE 754 floating point standard binary numbers to base ten decimal system (double)

64 bit double precision IEEE 754 binary floating point standard representation of numbers requires three building blocks: sign (it takes 1 bit and it's either 0 for positive or 1 for negative numbers), exponent (11 bits), mantissa (52 bits)

Latest 64 bit double precision IEEE 754 floating point binary standard numbers converted to decimal base ten (double)

1 - 101 1000 0000 - 0011 1100 0001 0111 0010 0100 0111 0100 0101 0011 1000 1110 0010 = ? Feb 04 09:11 UTC (GMT)
0 - 100 0001 0110 - 0010 1010 0000 1010 1001 0101 0000 0100 0111 1000 0011 1100 0110 = ? Feb 04 09:07 UTC (GMT)
0 - 000 0000 0000 - 0100 0000 1111 1010 1111 1011 1110 0111 1010 0011 1111 1110 1000 = ? Feb 04 09:07 UTC (GMT)
0 - 010 0001 0000 - 0011 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0010 = ? Feb 04 09:06 UTC (GMT)
0 - 100 0001 1000 - 0001 1011 1101 1100 0000 1001 1100 1010 0100 1110 0100 0111 1000 = ? Feb 04 09:06 UTC (GMT)
0 - 111 1111 1111 - 0000 0000 0000 0000 0000 0000 0000 0000 0000 1011 0000 0010 1101 = ? Feb 04 09:02 UTC (GMT)
0 - 100 0000 0011 - 0110 1100 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0001 = ? Feb 04 08:55 UTC (GMT)
0 - 001 1011 1100 - 0011 0111 1000 1011 0011 1110 1111 0010 1011 1110 1000 1011 1011 = ? Feb 04 08:47 UTC (GMT)
0 - 000 0000 0000 - 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1110 = ? Feb 04 08:42 UTC (GMT)
1 - 110 0000 0000 - 0111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1110 = ? Feb 04 08:41 UTC (GMT)
0 - 001 0000 0110 - 0000 1000 1111 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 = ? Feb 04 08:35 UTC (GMT)
1 - 010 1000 0001 - 1010 0100 1011 0100 0000 0000 0000 0000 0000 0000 0000 0000 0001 = ? Feb 04 08:28 UTC (GMT)
1 - 110 0000 0000 - 1000 0010 0101 0011 1010 1010 0111 1101 0101 0111 1110 0000 1110 = ? Feb 04 08:24 UTC (GMT)
All base ten decimal numbers converted to 64 bit double precision IEEE 754 binary floating point

How to convert numbers from 64 bit double precision IEEE 754 binary floating point standard to decimal system in base 10

Follow the steps below to convert a number from 64 bit double precision IEEE 754 binary floating point representation to base 10 decimal system:

  • 1. Identify the elements that make up the binary representation of the number:
    First bit (leftmost) indicates the sign, 1 = negative, 0 = pozitive.
    The next 11 bits contain the exponent.
    The last 52 bits contain the mantissa.
  • 2. Convert the exponent, that is allways a positive integer, from binary (base 2) to decimal (base 10).
  • 3. Adjust the exponent, subtract the excess bits, 2(11 - 1) - 1 = 1,023, that is due to the 11 bit excess/bias notation.
  • 4. Convert the mantissa, that represents the number's fractional part (the excess beyond the number's integer part, comma delimited), from binary (base 2) to decimal (base 10).
  • 5. Put all the numbers into expression to calculate the double precision floating point decimal value:
    (-1)Sign × (1 + Mantissa) × 2(Exponent adjusted)

Example: convert the number 1 - 100 0011 1101 - 1000 0000 0010 0001 0100 0000 0100 1110 0000 0100 0000 1010 1000 from 64 bit double precision IEEE 754 binary floating point system to base ten decimal (double):

  • 1. Identify the elements that make up the binary representation of the number:
    First bit (leftmost) indicates the sign, 1 = negative, 0 = pozitive.
    The next 11 bits contain the exponent: 100 0011 1101
    The last 52 bits contain the mantissa:
    1000 0000 0010 0001 0100 0000 0100 1110 0000 0100 0000 1010 1000
  • 2. Convert the exponent, that is allways a positive integer, from binary (base 2) to decimal (base 10):
    100 0011 1101(2) =
    1 × 210 + 0 × 29 + 0 × 28 + 0 × 27 + 0 × 26 + 1 × 25 + 1 × 24 + 1 × 23 + 1 × 22 + 0 × 21 + 1 × 20 =
    1,024 + 0 + 0 + 0 + 0 + 32 + 16 + 8 + 4 + 0 + 1 =
    1,024 + 32 + 16 + 8 + 4 + 1 =
    1,085(10)
  • 3. Adjust the exponent, subtract the excess bits, 2(11 - 1) - 1 = 1,023, that is due to the 11 bit excess/bias notation:
    Exponent adjusted = 1,085 - 1,023 = 62
  • 4. Convert the mantissa, that represents the number's fractional part (the excess beyond the number's integer part, comma delimited), from binary (base 2) to decimal (base 10):
    1000 0000 0010 0001 0100 0000 0100 1110 0000 0100 0000 1010 1000(2) =
    1 × 2-1 + 0 × 2-2 + 0 × 2-3 + 0 × 2-4 + 0 × 2-5 + 0 × 2-6 + 0 × 2-7 + 0 × 2-8 + 0 × 2-9 + 0 × 2-10 + 1 × 2-11 + 0 × 2-12 + 0 × 2-13 + 0 × 2-14 + 0 × 2-15 + 1 × 2-16 + 0 × 2-17 + 1 × 2-18 + 0 × 2-19 + 0 × 2-20 + 0 × 2-21 + 0 × 2-22 + 0 × 2-23 + 0 × 2-24 + 0 × 2-25 + 1 × 2-26 + 0 × 2-27 + 0 × 2-28 + 1 × 2-29 + 1 × 2-30 + 1 × 2-31 + 0 × 2-32 + 0 × 2-33 + 0 × 2-34 + 0 × 2-35 + 0 × 2-36 + 0 × 2-37 + 1 × 2-38 + 0 × 2-39 + 0 × 2-40 + 0 × 2-41 + 0 × 2-42 + 0 × 2-43 + 0 × 2-44 + 1 × 2-45 + 0 × 2-46 + 1 × 2-47 + 0 × 2-48 + 1 × 2-49 + 0 × 2-50 + 0 × 2-51 + 0 × 2-52 =
    0.5 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0.000 488 281 25 + 0 + 0 + 0 + 0 + 0.000 015 258 789 062 5 + 0 + 0.000 003 814 697 265 625 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0.000 000 014 901 161 193 847 656 25 + 0 + 0 + 0.000 000 001 862 645 149 230 957 031 25 + 0.000 000 000 931 322 574 615 478 515 625 + 0.000 000 000 465 661 287 307 739 257 812 5 + 0 + 0 + 0 + 0 + 0 + 0 + 0.000 000 000 003 637 978 807 091 712 951 660 156 25 + 0 + 0 + 0 + 0 + 0 + 0 + 0.000 000 000 000 028 421 709 430 404 007 434 844 970 703 125 + 0 + 0.000 000 000 000 007 105 427 357 601 001 858 711 242 675 781 25 + 0 + 0.000 000 000 000 001 776 356 839 400 250 464 677 810 668 945 312 5 + 0 + 0 + 0 =
    0.5 + 0.000 488 281 25 + 0.000 015 258 789 062 5 + 0.000 003 814 697 265 625 + 0.000 000 014 901 161 193 847 656 25 + 0.000 000 001 862 645 149 230 957 031 25 + 0.000 000 000 931 322 574 615 478 515 625 + 0.000 000 000 465 661 287 307 739 257 812 5 + 0.000 000 000 003 637 978 807 091 712 951 660 156 25 + 0.000 000 000 000 028 421 709 430 404 007 434 844 970 703 125 + 0.000 000 000 000 007 105 427 357 601 001 858 711 242 675 781 25 + 0.000 000 000 000 001 776 356 839 400 250 464 677 810 668 945 312 5 =
    0.500 507 372 900 793 612 302 550 172 898 918 390 274 047 851 562 5(10)
  • 5. Put all the numbers into expression to calculate the double precision floating point decimal value:
    (-1)Sign × (1 + Mantissa) × 2(Exponent adjusted) =
    (-1)1 × (1 + 0.500 507 372 900 793 612 302 550 172 898 918 390 274 047 851 562 5) × 262 =
    -1.500 507 372 900 793 612 302 550 172 898 918 390 274 047 851 562 5 × 262 =
    -6 919 868 872 153 800 704(10)
  • 1 - 100 0011 1101 - 1000 0000 0010 0001 0100 0000 0100 1110 0000 0100 0000 1010 1000 converted from 64 bit double precision IEEE 754 binary floating point representation to a decimal number (float) in decimal system (in base 10) = -6 919 868 872 153 800 704(10)