A First Course In Coding Theory (Oxford Applied Mathematics And Computing Science Series)

* PhysicalThis book has a good quality binding and a font size thats adequate to read if you need specs.* A - level, H.N.D, undergraduate, postgraduate?The target seems to be second - third year engineering or second - third year Math.* Whats covered then?The definition is to produce the simpler, theoretical backup when building error - correcting codes methods for digital technology. The book design is to use a minimum backbone of Math to help the applied problems. The early pages have a crib for math notation early in the book so straight away its a useful reminder. Then the important definitions of what is to be required to create error correcting systems. The nomenclature is (n, M, d), 'n' that is the fast transmission of messages, 'M' is to transmit a wider variety of messages, and a large 'd' is for error correction. Such as a definition of a individual codeword, and the total list of additional codewords as part of a set of codewords, and the error correction required.* What codes types are covered?The best error correction systems has perfect codes, that is individual code word that shares little with other individual code word that helpfully imagined by non - overlapping circles and use binomial probability equations. The difficulty from now on seems to depend if you have experienced' Group Theory' before using Galois finite fields and how they are linked to MOD number handling. With further application from Euler - based methods to solve linear matrices using fundamental operations such as permutation of rows to make generator / identities matrices and so on. The code explanations cover from linear, Latin square, dual codes, cyclic codes too. If you have all this under your belt already, your in a much better position that perhaps this being your first encounter of these features?* SummaryThis book has been a fair introduction to a useful topic that must have an impact if you a creating a digital hardware project for a dissertation. Even if you do not use all of this, its still a fabulous eye-opener of useful digital Applied Mathematical background.

A nice book, and an easy read if you already feel comfortable around vectorspaces over finite fields. Most of the math required in a basic course on coding is here and it's quite accessible. A few sections seems out of place, but except from that it's a good book. Although the pace picks up towards the end, this is probably not a graduate level book, so if used at that level to introduce coding theory additional material is required. Most of the problems are fairly simple, and have answers towards the end of the book. If you have the required level of "mathematical maturity" and are meeting coding theory for the first time, pick up this book, it was written for you. If you are looking for your second book you probably want to look somewhere else. (There are many "second books" out there but Blahut's book from 2003, or one of the titles by Vera Pless would be my choice).

I bought this book to prepare for a postgraduate course that has coding theory as an element. I found it relatively clear and, so far as I can tell, free of errors. There are many exercises, with (very brief) solutions. It's not a recent publication, and I'm not sure how many of the "unknowns" the book refers to are still unknown. However, I doubt the fundamentals of the subject have changed much since Hamming's heyday, so that's probably not a problem.I see two obvious problems:1. It's extremely expensive, for a short book. I'm aware that specialist textbooks are expensive, but I think the publishers are having a laugh here.2. Although the author claims that no particular knowledge is needed of abstract algebra, number theory, linear algebra, etc., the explanations of these subjects in the text were extremely abrupt. I found that I had to do a lot of additional reading to be able to follow many of the proofs.

As an introduction to coding theory this book is serviceable but not great. it covers the basics and is a reasonable introduction to more advanced texts. There, alas, my plaudits end.The author's style of mathematical writing is, IMO, appalling and a good illustration of the reasons why so many people find mathematics difficult. The rot starts in Chapter 1 where the Hamming distance is introduced without any indication of the significance of the concept or the degree to which it is used in proofs. Similarly the treatment in Chapter 2 of the concept of equivalence of codes is cursory, again taking no care to explain its wider significance. The author introduces theorems without any prefatory words and only after the proofs does one get any hint of why a theorem was introduced. Worse still, some of the proofs are so thoughtlessly worded as to engender misunderstanding. Worst of all, the author fails to exploit the close connections between coding theory and geometry, thereby casually ignoring one of the most enlightening connections of coding theory with other branches of mathematics. Other irritations abound, notably the overuse of formulae in running text and the inevitable impairment of legibility that results.Even though I can cope comfortably with these flaws, mathematical authors who write in this way simply annoy me to the point where I start thinking about guillotining a few of them in public "pour encourager les autres".Linguistically inept mathematical writers persistently defend lousy presentation on the pretext of writing for a certain level of mathematical maturity. The fact is, however, that if the exposition of mathematics is not crystal-clear, then it's almost invariably the author's fault. I can imagine some readers beginning a study of coding theory having many difficulties with the subject using this book. If they do, it's not necessarily any fault on their part but simply that the author's mathematical prose is, to use British army slang, "piss-poor". All-in all, this book falls well below the standard one should expect from an introductory text. It baffles me why OUP accepted it for publication.