[Edit: I regret turning nasty here. See the comments section for something rather more kind I would say to Winston Ewert.]
I mentioned a couple posts ago that I was annoyed with the editors and reviewers of an article, apparently to be published in an IEEE journal, by Winston Ewert, William Dembski, and Robert J. Marks II. [Edit 9/18/2014: Marks has removed the paper from his website. The IEEE Transactions on Systems, Man, and Cybernetics presently offers "Algorithmic Specified Complexity in the Game of Life" as a preprint.] Although I focus on the authors here, it will be clear enough what the folks responsible for quality control, including those on Ewert’s dissertation committee at Baylor, should have done. The short version is that, Googling obvious keywords, it takes at most a minute to discover that prior work, of which the authors claim to have no knowledge, exists in abundance.
Before continuing, I want to emphasize that my response to ID creationism is anything but knee-jerk. Consider, if nothing else, that the way I dealt with a dubious theorem supplied by Ewert et al. was to attempt to prove it. I not only succeeded in doing so, but supplied the proof here. I have since proved a fundamental theorem that some might take as advancing ID theory, though I see it otherwise.
Back to the article. There is no way around concluding that the veterans, Dembski and Marks, are either incompetent or dishonest. (You can guess which way I lean from a subtitle I’ve considered for this blog: Truth Is the First Casualty of Culture War.) And Youngman Ewert is either lazy, dishonest, or intellectually hobbled. (I see many signs of hero worship and true-believerism.)
You need no clear idea of what information theory is to grasp the significance of Dembski allowing himself to be promoted as the “Isaac Newton of information theory.” Marks edited a volume on engineering applications of information theory. The two have repeatedly cited standard texts that I own, but have not studied thoroughly. I am not an information theorist. So how is it that I should be thunderstruck by a flatly incorrect statement in the second sentence of the abstract, and then be floored by an intensification of it in the second paragraph of the text?
You may think that you are unqualified to judge whether Ewert, Dembski, and Marks are right or wrong. But Google Scholar settles the matter unequivocally. That is what makes the falsehood so atrocious. The authors state in the introduction:
Both Shannon ,  and Kolmogorov-Chaitin-Solomonoff (KCS)1 - measures of information are famous for not being able to measure meaning. [...] We propose an information theoretic method to measure meaning. To our knowledge, there exists no other general analytic model for numerically assigning functional meaning to an object.My immediate thoughts, incomprehensible to most of you, but eminently sensible to many who’ve had a course in information theory, were Kolmogorov structure function and Kolmogorov sufficient statistic. I first learned about Kolmogorov complexity from a chapter in reference : Cover and Thomas, Elements of Information Theory. See Section 14.12, “Kolmogorov Sufficient Statistic.” If Dembski and Marks do not understand the relevance, then they are incompetent. If they do, then they are dishonest.
1Sometimes referred to as only Kolmogorov complexity or Kolmogorov information.
Back to Google. And to Ewert. And to Baylor. The article clearly draws on Ewert’s dissertation, which had better include a chapter with a title like “Literature Review.” Actually, his dissertation proposal should have surveyed the relevant literature. A scholar should comprehend a body of knowledge before trying to extend it — right? Let’s make the relatively charitable assumptions that Ewert, though presuming to make a fundamental contribution to information theory, never took a course in information theory, and failed to grasp some aspects of the introduction to Kolmogorov complexity in Cover and Thomas. He nonetheless had obvious keywords to enter into Google Scholar. There are 41,500 results for the unclever searchthe more recent of Vitányi's articles, because he’s a prominent researcher in Kolmogorov complexity, and also the coauthor of the standard text on the topic (reference  in Ewert et al.). I have highlighted key phrases in the abstract for those of you who don’t care to grapple with it.
Abstract—The information in an individual finite object (like a binary string) is commonly measured by its Kolmogorov complexity. One can divide that information into two parts: the information accounting for the useful regularity present in the object and the information accounting for the remaining accidental information. There can be several ways (model classes) in which the regularity is expressed. Kolmogorov has proposed the model class of finite sets, generalized later to computable probability mass functions. The resulting theory, known as Algorithmic Statistics, analyzes the algorithmic [Kolmogorov] sufficient statistic when the statistic is restricted to the given model class. However, the most general way to proceed is perhaps to express the useful information as a total recursive function. The resulting measure has been called the “sophistication” of the object. We develop the theory of recursive functions statistic, the maximum and minimum value, the existence of absolutely nonstochastic objects (that have maximal sophistication—all the information in them is meaningful and there is no residual randomness), determine its relation with the more restricted model classes of finite sets, and computable probability distributions, in particular with respect to the algorithmic (Kolmogorov) minimal sufficient statistic, the relation to the halting problem and further algorithmic properties.
So what are you up to in this paper, Dr. Ewert? When you feed us the “to our knowledge” guano, knowingly creating the misimpression that you tried to acquire knowledge, you are essentially lying. You have exaggerated the significance of your own work by failing to report on the prior work of others. I doubt highly that you are capable of understanding their work. Were you so inept as to not Google, or so deceitful as to sweep a big mound of inconvenient truth under the rug? Assuming the former, you need to catch on to the fact that your “maverick genius” coauthors should have known what was out there.