The Harrington Compression Method (HCM) White Paper. - Theory

This is a discussion on The Harrington Compression Method (HCM) White Paper. - Theory ; Jym there is always a few odd carrots in a pile of standard carrots, yes? Ones with cracks, ones to small, ones with really long roots, etc. This is statistics in action I use the word statistics since there is ...

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The Harrington Compression Method (HCM) White Paper.

  1. Default Re: The Harrington Compression Method (HCM) White Paper.

    Jym there is always a few odd carrots in a pile of standard carrots,
    yes? Ones with cracks, ones to small, ones with really long roots,
    etc.

    This is statistics in action


    I use the word statistics since there is no "perfect number". Things
    are not going to be reduced by say 1.241578823191231236% all the time.
    This is why I use the words statistically and probability frequently.
    If I do not some mathematicians will tear me a new one with useless
    posts which divert from the reality of the entirety challenging the
    notion of 'how can that be always true?"


    therefore we can get a range of variation.



    Also the decoding is built in.

    File #1
    11001

    File #2
    101

    File #3
    01

    This leads from the first bit in file #1 becoming the source bit, in
    the new decompressing file. The next place to look is file #2 due to
    the fact it is a 1, take the 1 in file #2 and add it to the source
    file. Now we look to file #3 for the next bit. We add it to the
    decompress file.

    Decompress:
    110

    File #1
    1001

    File #2
    01

    File #3
    1

    next one in file #1 is a 1, we add it to the decompress, then file #2
    since it was a 1, so the 0 gets added as well

    Decompress:
    11010

    File #1
    001

    File #2
    1

    File #3
    1

    I dare say you can complete the run now.

  2. Default Re: The Harrington Compression Method (HCM) White Paper.

    Let me break this down into a real simple example

    64 bits goes in.

    Stage 1 increases it to 72 bits statistically

    Stage 2 puts it in files, we then run file #1 again.

    File #1 had 32 bits when put in, now it has 36 and is split into 3
    subfiles.

    1.1 has 16 bits
    1.2 has 12 bits
    1.3 has 8 bits

    Now the ratio's:
    File 1.1
    93.75% to 6.25%.

    File 1.2
    80% to 20%

    File 1.3
    75% to 25%



    File 1.1 comes out with a statistical 9.47 bits remaining.

    File 1.2 comes out with a statistical 9.36 bits remaining

    File 1.3 comes out with a statistical 6.75 bits remaining

    This is 25.58 bits.

    Compare this to the 28.44 bits that it would normally hold

    Since this is repeatable upon any file (1.1, 1.2, 1.3, 2, 3 currently
    in existance in this example) this means we can compress ALL files of
    sufficient size.

    If no matter what file #1 after being run through the system again is
    smaller than what it went in as, we have proven compression of
    entropic data.


    Let me stress that again.

    So long as 1.1, 1.2, 1.3 is smaller than file #1 was to begin with, we
    have compression of random binary data.

    I will stand by this to the end of my days, and be right always!

  3. Default Re: The Harrington Compression Method (HCM) White Paper.

    On Aug 26, 10:17 pm, Einstein <michae...@gmail.com> wrote:
    ....

    > So long as 1.1, 1.2, 1.3 is smaller than file #1 was to begin with, we
    > have compression of random binary data.
    >
    > I will stand by this to the end of my days, and be right always!


    Not sure why you can't see the obvious. You can't count the sum
    of the 3 files. You need to count after you combine it or else
    something so trival as what follows would be considered compression
    in your sense..

    take a very long random bit string at lest a milllion bits. go to
    third occuance
    of 01
    let file one be every bit upto the 01 but not includeing it.
    let file 2 be the next set of bits up to the sixth occurance of 01 but
    not
    includeing the 01
    let file 3 be the rest.

    Gues what I saved 4 bits. By your logic it was compression. But its
    snot.

    David A. Scott
    --
    My Crypto code
    http://bijective.dogma.net/crypto/scott19u.zip
    http://www.jim.com/jamesd/Kong/scott19u.zip old version
    My Compression code http://bijective.dogma.net/
    **TO EMAIL ME drop the roman "five" **
    Disclaimer:I am in no way responsible for any of the statements
    made in the above text. For all I know I might be drugged.
    As a famous person once said "any cryptograhic
    system is only as strong as its weakest link"


    w

  4. Default Re: The Harrington Compression Method (HCM) White Paper.

    Your missing the entirety of the system

    Since essentially my system self places information in the files, it
    is impossible to get errors back or forward. There is no duality or
    issues with two becomes one. Each result IS UNIQUE.

    The different files are appended later with a cost, yes, to eachother,
    into a single string in the end...

    A single string which if the original source data was large enough,
    will ALWAYS be compressed.


    I am going to stress this to you

    If the string is long enough, compression ALWAYS can occur.



    Then I am going to stress this to you


    THOSE FILES ARE TEMPORARY AND THE RESULTS END UP BEING ONE STRING
    WHICH IS SMALLER THAN THE ORIGINAL STRING.



    get past your biases, and just run the numbers as my post about file
    #1 shows. It shows a perfect ability to compress data. Get past it man!

  5. Default Re: The Harrington Compression Method (HCM) White Paper.

    Disfruta las emociones que experimentas ahora, de creer haber
    encontrado el algoritmo que cambiara nuestra era informatica. Muy
    pronto experimentaras la desilusion mas profunda de tus terorias.

    Solo te falta algo para no caer de verguenza en verguenza. Ser un
    programador. Asi solo podras llevar tus teorias a la practica
    absoluta, previniendo tus desilusiones.

    El equivocarse es parte de nuestra evolucion, pero el ser testaduro es
    parte de nuestra personalidad.

    Suerte.

  6. Default Re: The Harrington Compression Method (HCM) White Paper.

    Mi agradecimiento, si lo entiendo correctamente. Español no es mi
    lenguaje más fuerte.

    Creo que puedo evitar el problema de malentendidos en breve. Sus
    argumentos son un círculo. Soy capaz de escribir algo hasta esta noche
    Espero que, si bien en el trabajo, que les ayuden a entender mejor.

    La suerte para ti.

  7. Default Re: The Harrington Compression Method (HCM) White Paper.

    Einstein schrieb:
    > Thomas you are trying to divert the actual make up.
    >
    >
    > It's a simple concept, a 50/50%, a 25/25/25/25%, a
    > 12.5/12.5/12.5/12.5/12.5/12.5/12.5/12.5%, and so forth situation can
    > be made into a:
    >
    > Three files with a 75/25% a 67/33% and a 50/50%.


    All fine, but then again, for each data item, you need to index which
    file to take the next item from. For that, you also need some bits. For
    example, let's split things up such that we write the (00) combinations
    into file A, (01) and (10) into file B and (11) into file C, making this
    for IID data two files containing on average 25% of the data, and one
    file containing the other 50%. That you use a huffman in advance doesn't
    matter, the output of the ideal huffman for a given IID source will be
    sufficiently close to IID. Then, obviously, we can simply strip file A
    and file C completely since they are all zero or all one, and only need
    to keep file B (whoa, what a compression, you might think!). We can even
    do better in file B by encoding a 01 as 0 and a 10 as 1, making things
    even shorter. But, we also need to identify in a separate file (or the
    filing system) which file to use to read the next bits from on
    decompression. Obviously, this information is a IID source on a
    three-letter alphabet A,B,C with probabilities p(A) = p(C) = 0.25 and
    p(B) = 0.5. Thus, an optimal huffman code for this would be

    B -> 1
    A -> 01
    C -> 00

    The average length of the output per symbol is then

    1 * 0.5 + 2 * 0.25 + 2 * 0.25 = 0.5 + 0.5 + 0.5 = 1.5 bits per symbol
    for this side-channel. For the overall file, you need to encode for:

    00 :nothing in file A, two bits in the side information: 2 bits
    11 :nothing in file C, two bits in the side information: 2 bits
    01 ne bit in file B, one bit of side information : 2 bits
    10 ne bit in file B, one bit of side information : 2 bits

    Thus, you modified your input of 1 bit per symbol into an output using
    two bits per two symbols.

    Hubba hub, Mr. Marx!

  8. Default Re: The Harrington Compression Method (HCM) White Paper.

    Einstein wrote:
    ) 10 00 10 10 01 01 11 01 01 01 11 10 01 01 00 00 11 10 00 11 00 10 00
    ) 10 00 00 00 11 01 11 11 0
    )
    ) First I divided it into chunks of 2 bits. I found a missing bit, so I
    ) add a 1 to the end (Command section identifies the missing bit by
    ) using a bit to say "add a bit to the end")

    Yeah sorry, there should have been a 0 at the beginning but the software
    cut the leading 0's. I should have checked. But anyways, this will work
    just as well, so no real problem there.

    NB: I got these from http://www.fourmilab.ch/hotbits/ who claim to be a
    genuine source of random numbers.

    ) <snip>
    )
    ) Note that statistically, since we do have command section issues, we
    ) have obtained compression, even after adding two bits to the whole.

    What do you mean by 'statistically' ?

    ) Yes the command section requires knowing which swaps we will do per
    ) file, such as in file #1.2 we swap 00 for 10 in our make up so that it
    ) has a value length of 2 bits., and 01 in file #1.3 has the same
    ) happening.
    )
    ) This has 63 bits + command section, for 64 bits. Now the command
    ) sections will come out to less than 350 bits total. I can even say a
    ) rounded 500 bits if you desire. Therefore if this statistical sample
    ) was 31500 bits or more we would have factual compression after the
    ) command section.

    So, what you're saying, roughly, is that by showing that 64 bits can be
    compressed to 62 bits plus a 'command section', you have proven that
    64000 bits can be compressed to 62000 bits plus a 'command section' ?
    And then you claim that the 'command section' has a maximum size.

    You're wrong.

    The big error you're making here is to assume that your measurement
    of compression on a small file will scale up to keep the same ratio
    for the bigger files. I see no proof or evidence of this.

    It looks like all the compression gain you get is by making a few
    choices along the way (such as the swapping of huffman table values)
    so you get the best result.

    But those choices give you a *constant* gain, not a percentual one.



    SaSW, Willem
    --
    Disclaimer: I am in no way responsible for any of the statements
    made in the above text. For all I know I might be
    drugged or something..
    No I'm not paranoid. You all think I'm paranoid, don't you !
    #EOT

  9. Default Re: The Harrington Compression Method (HCM) White Paper.

    Einstein wrote:
    > Your missing the entirety of the system


    > get past your biases, and just run the numbers as my post about file
    > #1 shows. It shows a perfect ability to compress data. Get past it man!


    Shame, shame, shame on you.

    You already gone thru this in the past. When making claims the burden
    is on you to prove what you claim not others.

    You claimed to have tested you idea. But so far you have not:

    1) Shown all the steps used to compress the data. All the steps
    includes all the control codes/bits. Instead you make claims about
    about what the expect number of bits will be. DON'T CLAIM IT, SHOW
    IT.

    2) You have not shown what the final compressed file will look like,
    just claims about what you expect it to be. DON'T CLAIM IT, SHOW IT.

    3) And most important, shown that the decompression stage works by
    using it on the compressed data and then getting the original data
    back. Every con-artist and misled compression expert always seems to
    mess up at this stage of the game.

    So Einstein if you want people to believe you have something
    worthwhile, why are you avoiding doing everything from start to finish?

  10. Default Re: The Harrington Compression Method (HCM) White Paper.

    On 26 Aug, 17:14, Willem <wil...@stack.nl> wrote:
    > Einstein wrote:
    >
    > ) Introduction:
    > ) This is a lossless compression method which WILL work on random binary
    > ) data and data considered Entropic.
    >
    > <snip>
    > I'll jump right to the blatant error.
    >
    > ) File 1.1 = 1.05 bits
    > ) File 1.2 = 1.04 bits
    > ) File 1.3 = .75 bits
    > ) File 2 = 2.83 bits
    > ) File 3 = 2 bits
    > )
    > ) Statistically speaking there are 7.67 bits for every original 8 bits.
    >
    > And you have 5 files instead of 1.  This represents extra information.
    > So much extra that it easily accounts for the 0.33 bits/byte you 'gained'..
    >
    > ) 5)Command Section
    > ) We now need a command section to handle all the different files,
    > ) changes, etc. Each file will have a specific number of bits. This can
    > ) be easily represented with a simplistic counting system allowing for
    > ) maximum space savings. If < 1 kilobyte then 00, if less than 1
    > ) megabyte then 01, if less than 1 gigabyte then 10, if greater than 1
    > ) gigabyte then 11.
    >
    > I note that you fail to calculate how many bits this command section will
    > take, statistically.
    >
    > ) The claim of the pigeon hole problem naturally arises at this point.
    > ) However, all the steps are reversible and lead IMMEDIATELY back to the
    > ) same original code. No two results will be exactly the same. It is
    > ) mathematically not possible. The HCM system completely leads to the
    > ) data as inputted originally.
    >
    > Note that the counting theorem has been proven true.


    Or the bounds of the system used to prove the 'argument' have been
    exceeded, by such a simplistic assumption that all compression must
    work by direct mapping of 2^n bit state possibilities of n bits.
    Nothing actually said anything about 1 of 2^n to another of 2^n being
    in anyway informative. No mutual information calculation has been
    shown. reduct6o-ad-OBSERDum has the right name. Apart from this you
    are most probably right.

    cheers
    jacko

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