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Written for advanced C/C++ programmers, Walter Oney's Programming the Microsoft Windows Driver Model is a technically astute and clearly presented guide to writing custom Windows 2000 device drivers.
The author's command of the details of the new Windows Driver Model (WDM) standard is what makes this book such a clear success. (Because the WDM is rich in kernel and system services, the trick is often knowing how to use what's available rather than doing everything yourself.) The author presents a solid overview of the WDM architecture and breaks down the process of writing custom device drivers into manageable pieces, from the basics of loading device drivers to creating and processing I/O request packets. The book is very good at exposing kernel system calls, design principles, and programming techniques (such as managing synchronization and handling errors). There are also "nerd alerts" that point out extremely technical material.
This book shows you what you'll need to create WDM drivers that cooperate fully with Windows 2000 (and Windows 98). Features like Plug and Play (PnP), Windows power management, and the new Windows Management Instrumentation (WDM) standard get full attention here. There is plenty of sample code (plus a custom Visual C++ AppWizard that generates skeleton code for a default WDM driver) to get you started. Examples for working with the S5933 PCI chip set (and other simple hardware) let you see WDM drivers in action.
The process of writing device drivers certainly has changed from the early days of DOS. But armed with this handy and thorough book, C/C++ programmers can successfully create drivers for custom hardware that take full advantage of all the features of the powerful new WDM standard. --Richard Dragan
Topics covered: Windows Driver Model (WDM) overview and driver structure; kernel mode; physical filter, function and bus drivers; loading device drivers (DDs); driver objects; Windows 98 compatibility; kernel mode programming basics; error handling; memory management; synchronization; interrupt request levels, kernel synchronization objects, I/O request packets (IRPs), completion routines, plug and play (PnP) basics, reading and writing data, direct memory access (DMA) transfers, power management, error logging, watchdog timers, Windows Management Instrumentation (WMI), Universal Serial Bus (USB): bulk transfer and isochronous pipes; installing DDs: INF files, property pages, and Registry keys.
Book Description
Microsoft's new driver model for Windows 98 and Windows 2000 supports Plug and Play, provides power management capabilities, and expands on the driver/minidriver approach. Written by device-driver expert Walter Oney in cooperation with the Windows DDK team, this book provides extensive practical examples, illustrations, advice, and line-by-line analysis of code samples to clarify real-world driver-programming issues. Topics covered include:• An introduction to the Windows Driver Model architecture• Programming techniques, including error handling, memory and data-structure management, and registry and file access• Synchronization and driver development in a multitasking, multiprocessor environment• Creating and processing I/O request packets• Taking advantage of Windows 98 and Windows 2000 Plug and Play support • Techniques for reading from and writing to devices• Installation and power management• Creating filter drivers, controlling hardware, and logging errors • Windows Management Instrumentation (WMI)• Developing device drivers for the new universal serial bus (USB) architecture• Installing WDM drivers• Understanding Windows 98 compatibilityAn electronic version of this book is available on the companion CD.
Customer Reviews:
A Must Have.......2006-07-01
I've been working on Linux kernel driver for sometime and recently started porting my driver to Windows platform, which is totally new to me. I started by going through DDK online manual for over a month, during which I spent a ton of energy trying to find the Windows counterparts of the functions I'm using in Linux driver. Then I came across this book, which is saving me a lot.
That's right, this book is no newbie one, but it is definitley well-written, organized, and neat if compared to "Linux Device Driver 3rd", if you happen to have one.
Strongly recommend this book if you are a serious DDK writter. And BTW, use this book with DDK online manual intensively.
Expecting the 3rd edition!
Great book for my needs given my experience........2004-04-08
Oney's book provided the right overview and explanations I needed to get up to speed. I didn't expect a man to pop out of his book and do the work for me. Most any serious development is never done by the purchase of a book alone.
I do recall certain areas where I mumbled a little, where I'd wished he'd elaborated and/or expanded a little more, but this is meant only to hint at a slight criticism.
Oney's book was used in helping to produce successful results for real-world commercial software development. Thanks Mr. Oney!
Be careful.......2004-02-17
I am borrowing a copy of this book at work, and I agree with the other reviewers that its helpful, and it doesnt "talk down"
But it can get quite rambly, the IO Request Chapter is a great example of this.
That being said I actually tried to include his DEVQUEUE in my driver code im using at work...Ive been programming for 10+ years so im not a slouch.
Problems:
1) C code written using C++ rules. This is annoying.
2) Doesn't compile at tighter warning levels...LOTS of warnings
3) Bug in DEVQUEUE initialization sent me on an IRP goosechase for good part of a day, and YES I did download his code service packs first. Watch out for stallcount being initialized to 1, StartNextPacket will refuse to run unless you change this to zero.
Success Story.......2003-04-25
This book was a valuable resource for my successful driver development project.
For newbie's, the book is a great companion to the DDK. The text provides simple and concise sample code. The examples on the CD-ROM are a great way to start exploring driver programming concepts using a kernel debugger. The DDK samples are far too complicated for understanding the fundamentals, so use the book to get started and then the DDK samples will be much easier to comprehend.
I recommend that you read through the entire book at a high enough level that you don't get caught up in the details. Next, find the chapter and sample driver that is most appropriate for your task and get started. Throughout the rest of development, you'll reference various parts of the book to understand the details and avoid the hidden pitfalls in kernel mode programming.
For experts, the book provides comprehensive treatment of the topic. It's full of tips and suggestions based on real-world experience. Many of the driver components on the CD-ROM can be integrated into real drivers in order to reduce development time and complexity. If you are creating a production driver that you intend to ship to real customers, the book will also provide you many options for creating a top-notch user experience during the install process. WHQL and driver security issues are addressed as well.
The author updates the CD-ROM sources in service packs located on the web site. These updates are based on his continuing work and feedback from readers.
Hard going.......2003-03-10
This book is written in an extremely hard to read style, with long and convoluted sentences.
The writing style is almost unbearably boring. It you thought Hardy's "Return of the Native" was too fast paced, this is the book for you!
It also tends to explain the micro details without clearly explaining how it all fits together. In this respect, it almost assumes you have read and understood the Device Driver Kits, although the reader will be generally looking for help getting started with the DDKs.
There also seem to be a lot of omissions, in that it does not do a very good job of getting you started. Want to write a winmodem driver? This book gives you no idea where to start.
Having said all that, you probably need this book if you are writing a WDM driver. It does have a lot of useful information and tips. However it assumes you are a guru already.
Book Description
Graphical models, a marriage between probability theory and graph theory, provide a natural tool for dealing with two problems that occur throughout applied mathematics and engineering--uncertainty and complexity. In particular, they play an increasingly important role in the design and analysis of machine learning algorithms. Fundamental to the idea of a graphical model is the notion of modularity: a complex system is built by combining simpler parts. Probability theory serves as the glue whereby the parts are combined, ensuring that the system as a whole is consistent and providing ways to interface models to data. Graph theory provides both an intuitively appealing interface by which humans can model highly interacting sets of variables and a data structure that lends itself naturally to the design of efficient general-purpose algorithms.
This book presents an in-depth exploration of issues related to learning within the graphical model formalism. Four chapters are tutorial chapters--Robert Cowell on Inference for Bayesian Networks, David MacKay on Monte Carlo Methods, Michael I. Jordan et al. on Variational Methods, and David Heckerman on Learning with Bayesian Networks. The remaining chapters cover a wide range of topics of current research interest.
Customer Reviews:
Recommended, but not the place to begin.......2003-06-19
The title of the book is somewhat misleading, in that most of the research papers involve advanced issues concerning one particular graphical model, namely the Bayesian network. For this reason I highly recommend, as a prerequisite to this book, Finn Jensen's "Bayesian Networks and Decision Graphs". Jensen's book is adequate in giving a good introduction and overview of the subject, but not sufficient for calling oneself an "expert" upon successfully digesting it.
To its credit, "Learning in Graphical Models" has several well-written and interesting papers, but the tutorial papers just did not seem enough of an introduction for me to feel comfortable using it as a first source of introduction.
What I find most compelling about Bayesian networks is the fact that they seem both highly modular (which facilitates reusability and network interconnectivity) and can be designed in a semi-rational manner (contrast this with neural-network architectures for which few good algorithms exist for determining size and number of layers). For this reason I imagine they will be important players in future engineering projects that require learning and adaptation.
Simply Superb..........2000-03-31
My area of research revolves around graphical models... Best Book... The book that introduced me as to how effective graphical models are... As stated in the editorial review, graphical model is the marriage between graph theory and probability and this book justifies the sacredness of this marriage!
Book Description
The idea of modelling systems using graph theory has its origin in several scientific areas: in statistical physics (the study of large particle systems), in genetics (studying inheritable properties of natural species), and in interactions in contingency tables. The use of graphical models in statistics has increased considerably over recent years and the theory has been greatly developed and extended. This book provides the first comprehensive and authoritative account of the theory of graphical models and is written by a leading expert in the field. It contains the fundamental graph theory required and a thorough study of Markov properties associated with various type of graphs. The statistical theory of log-linear and graphical models for contingency tables, covariance selection models, and graphical models with mixed discrete-continous variables in developed detail. Special topics, such as the application of graphical models to probabilistic expert systems, are described briefly, and appendices give details of the multivarate normal distribution and of the theory of regular exponential families. The author has recently been awarded the RSS Guy Medal in Silver 1996 for his innovative contributions to statistical theory and practice, and especially for his work on graphical models.
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Bayesian Network Technologies: Applications and Graphical Models
Manufacturer: IGI Publishing
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Bayesian Networks and Decision Graphs (Information Science and Statistics)
ASIN: 1599041413
Release Date: 2007-03-30 |
Product Description
Bayesian networks are now being used in a variety of artificial intelligence applications. These networks are high-level representations of probability distributions over a set of variables that are used for building a model of the problem domain. Bayesian Network Technologies: Applications and Graphical Models provides an excellent and well-balanced collection of areas where Bayesian networks have been successfully applied. This book describes the underlying concepts of Bayesian Networks in an interesting manner with the help of diverse applications, and theories that prove Bayesian networks valid. Bayesian Network Technologies: Applications and Graphical Models provides specific examples of how Bayesian networks are powerful machine learning tools critical in solving real-life problems.
Book Description
Graphic modelling is a form of multivariate analysis that uses graphs to represent models. These graphs display the structure of dependencies, both associational and causal, between the variables in the model. This textbook provides an introduction to graphical modelling with emphasis on applications and practicalities rather than on a formal development. It is based on the popular software package for graphical modelling, MIM, a freeware version of which can be downloaded from the Internet. Following an introductory chapter which sets the scene and describes some of the basic ideas of graphical modelling, subsequent chapters describe particular families of models, including log-linear models, Gaussian models, and models for mixed discrete and continuous variables. Further chapters cover hypothesis testing and model selection. Chapters 7 and 8 are new to the second edition. Chapter 7 describes the use of directed graphs, chain graphs, and other graphs. Chapter 8 summarizes some recent work on causal inference, relevant when graphical models are given a causal interpretation. This book will provide a useful introduction to this topic for students and researchers.
Customer Reviews:
this is about directed graphs not graphics.......2001-04-22
Because graphic methods are very popular in statistics, when you read the title you might think this is a book on the use of graphics in statistics. That is not what the book is about. The directed graph on the cover might be a hint for some. The book deals with the theory of undirected and directed graphs which has applications to causal modeling in statistics and the development of expert systems (which Edwards claim are now more commonly referred to as probabilistic networks).
This subject is being made popular again based on the recent work of Edwards, Pearl and a few others. The book incorporate the approach in many classical statistical problems. This is not commonly seen except in specialized texts on latent variable models.
Edwards discusses implementation of the methods with the freeware MIMS that is available in Denmark and on the web. The book is very well written and applications in MIMS are given throughout the text. Edwards also provides us with an excellent list of references (over 200 with many on causal modeling).
The software LISREL produced by researchers in the US at UCLA for latent variable and path analyses is only briefly mentioned on page 217. The lack of coverage of American and British publications on this topic is the only drawback I see.
Average customer rating:
- Engineering Design Communication And Modeling Using Unigraphics Nx
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Engineering Design Communication and Modeling Using Unigraphics NX
Gang Qi
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Practical Unigraphics NX3 Modeling, Drafting and Assemblies
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Practical Unigraphics NX Modeling for Engineers
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Theory and Design for Mechanical Measurements
ASIN: 1418011495 |
Book Description
This book takes an original approach to engineering design communication by combining traditional engineering graphical communication with design modeling, and incorporating the assistance of a CAD tool. Through the use of practical examples and a straightforward writing style, Engineering Design Communication and Modeling Using Unigraphics® NX provides readers with a basic knowledge of traditional engineering graphical communication and design modeling. The subsequent introduction of the CAD system enhances this knowledge, providing readers with a solid understanding of how engineering design communication is accomplished. "Neutral" language that is not CAD system-specific is used throughout, making this an ideal resource for readers of all backgrounds.
Customer Reviews:
Engineering Design Communication And Modeling Using Unigraphics Nx.......2005-11-23
I found the book very informative. I have two issues with the book though. The part files on the CD that came with the book were created on a newer revision of Unigraphics and as a result any version earlier can not open them (I am using NX2). The other issue I have is that there are many examples and activities that show using "Multiple Base Features" ( I call them Primitives). It is a bad idea to use multiple primitives for the simple reason is that they are not associative. When designing anything mechanical the only sure thing is that is that something will change as the design progresses. Using multiple primitives in a solid would almost guarantee that any change would require starting over.
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Graphical Models for Machine Learning and Digital Communication (Adaptive Computation and Machine Learning)
Brendan J. Frey
Manufacturer: The MIT Press
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ASIN: 026206202X |
Book Description
A variety of problems in machine learning and digital communication deal with complex but structured natural or artificial systems. In this book, Brendan Frey uses graphical models as an overarching framework to describe and solve problems of pattern classification, unsupervised learning, data compression, and channel coding. Using probabilistic structures such as Bayesian belief networks and Markov random fields, he is able to describe the relationships between random variables in these systems and to apply graph-based inference techniques to develop new algorithms. Among the algorithms described are the wake-sleep algorithm for unsupervised learning, the iterative turbodecoding algorithm (currently the best error-correcting decoding algorithm), the bits-back coding method, the Markov chain Monte Carlo technique, and variational inference.
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OSI: A Model for Computer Communications Standards
Uyless D. Black
Manufacturer: Prentice Hall
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ASIN: 0136371337 |
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M->CREATED
Customer Reviews:
The best book on osi.......2000-05-22
open system interconnection has always been a challenging area for students as well as software developers. This perticular book by Uyless Black is very good for its wide coverage and lucid explanation with diagrams. I would like to recommend this book for students interested in OSI since this will provide them with the best foundation for computer communication.
Average customer rating:
- interesting & clearly written
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Probabilistic Reasoning in Multiagent Systems: A Graphical Models Approach
Yang Xiang
Manufacturer: Cambridge University Press
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Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
ASIN: 0521813085 |
Book Description
Probalistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become an active field of research and practice in artifical intelligence, operations research and statistics in the last two decades. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradim has been striking. In this book, the author extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results gleaned from a decade's research.
Customer Reviews:
interesting & clearly written.......2003-02-06
This book can be placed in the area of research in AI that brings single agent, centralised techniques to a distributed multi-agent context. The central idea of the multi-agent paradigm is to solve complex problems with a collection of autonomous and possibly distributed agents.
In the first 5 chapters this book gives a thorough understanding of exact inference in Bayesian networks.
In the 6th chapter Y. Xiang introduces Multiply Sectioned Bayesian networks (MSBN), a knowledge representation formalism for probabilistic inference in multi-agent systems. He clearly informs the reader of the constraints that are associated with MSBNs and how they are the unevitable consequence of a few high level choices.
Some of the choices are:
- the beliefs of the agents are represented by probabilities
- the internal representation of an individual agent is a DAG
- the least amount of communication between agents possible
Some of the contraints that follow from these choices are:
- a hypertree agent organisation which prevents agents from communicating with any other agent
- only communication between agents on variables they share between their local models
In subsequent chapters the author introduces algorithms for cooperative, distributed probabilistic inference. First how to compile an MSBN to a linked junction forest (= the multi-agent version of a junction tree) through moralization, triangulation, and the construction of linkage trees. Then, how to perform the actual probabilistic inference in such a linked junction forest.
In the 9th chapter algorithms are shown that allow to verify whether a structure does not violate the constraints imposed by the MSBN paradigm.
Finally, in the last chapter Xiang gives an overview of all the possible extensions and future work, such as dynamic formation, learning, negotiation etc.
The book is clearly written and very understandable, even for people with little knowledge of probabilistic reasoning. In my opinion this is because of the clear and not unnecessarily complicated language and because throughout the entire book the same example is used (monitoring of digital circuits ).
A few points of critique are that some more space could have been devoted to possible applications and related work.
To conclude, a very interesting and clear book on a new and promising paradigm, suited for everyone interested in Bayesian networks and multi-agent systems.
Book Description
PRINCE2 Process Model(2005): A Comprehensive Graphical View of All the Standard PRINCE2 Processes and Products(Map)
Customer Reviews:
small and printed on both sides.......2007-09-04
I was disappointed with this - while the content of the poster is good - it is small (A3) and has print on both sides so you will need 2 if you really wish to post it up!
A great product ! I recommend it !.......2006-03-13
A great product ! I recommend it !
Updated Process Map.......2005-11-17
The Process map has been updated with minor changes, and is just waiting for publication of the new 2005 PRINCE2 manual from the OGC, due out by the end of November. All process maps shipped from the 17th November 2005 will contain the updates. However for existing customers the changes do not effect anyone taking exams upto January 2006, when the new changes will be reflected in the exams.
Great but out of date!.......2005-09-30
The idea of this product is great. It clearly & easily presents a large amount of information about the Prince 2 method, and should be a great reference for those looking to take the Practitioners exam. Note however, the word should ... unfortunately on receiving the item I discovered that it is in fact out of date, as it does not reflect the changes to the Method as released in the 2005 edition.. and as it is this latest version of the method that candidates for the exam are now being tested on ... well, you get the picture!
clear and concise.......2004-06-09
excellent overview of the PRINCE2- I HAVE PAID $17 for the same map through my company. A huge colorful Process Map, clearly setting out the different stages.
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Writing Windows WDM Device Drivers
