Download e-book for iPad: An introduction to crystal analysis by William Henry Bragg

By William Henry Bragg

This e-book is based on a process lectures which used to be given on the collage collage, Aberystwyth, within the autumn of 1926. The lectures have been meant for a basic viewers ; and consisted, consequently, of a sequence of straightforward illustrations of the most positive factors of crvstal research. it should now not were attainable to do extra in the limits imposed by means of time and the conditions. The therapy during this booklet is just a little fuller and extra assorted than that of the lectures.

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To give the reader a simple illustration of a chain set answer in a classification situation which is preferable to the answer of propositional calculus alone, consider the following interesting example which is treated in detail in sect. 4. 10) and consider the following knowledge base information, info-kb = = (p~q) (IF x is an instance of a cat THEN x is an instance of a mammal). 2. THE IF THEN LOGIC OF HUMAN REASONING 11 Let us now direct, in turn, the following two questions at this knowledge base,13 qu-kb 1?

Chains having a probability 0 are often left out. A 1 'bloc entry' of a chain means the affirmation of the ground universe element in the left margin, 0 means its negation. 20) respectively. Still another advantage of the chain set structures of parts I and II, whether they represent sentences with IF THEN or with other connectives, is their relative simplicity for programming purposes. 2 show examples of chain sets for labels with AND and OR connectives respectively. Chain sets for composite labels which need not be complete sentences are discussed in sect.

1 CHAPTER 1. INTRODUCTION Expressing and Updating Uncertainty and Ignorance the Chain Set System III Probabilistic Answers to Questions Item 4 of sect. 4 concerns means of expressing and updating uncertainty and lack of information. As we have already mentioned, the chain set system gives its inferences or answers to questions in the form answ = P( qu /info), the value of the probability of occurrence of the event specified by the question qu, as inferred from the probability distribution specified by the given information in the knowledge base.

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An introduction to crystal analysis by William Henry Bragg

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