Tham khảo tài liệu 'lập trình c# all chap "numerical recipes in c" part 96', công nghệ thông tin phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 808 Chapter 18. Integral Equations and Inverse Theory The single central idea in inverse theory is the prescription minimize A XB for various values of 0 A 1 along the so-called trade-off curve see Figure and then to settle on a best value of A by one or another criterion ranging from fairly objective . making 2 N to entirely subjective. Successful methods several of which we will now describe differ as to their choices of A and B as to whether the prescription yields linear or nonlinear equations as to their recommended method for selecting a final A and as to their practicality for computer-intensive two-dimensional problems like image processing. They also differ as to the philosophical baggage that they or rather their proponents carry. We have thus far avoided the word Bayesian. Courts have consistently held that academic license does not extend to shouting Bayesian in a crowded lecture hall. But it is hard nor have we any wish to disguise the fact that B has something to do with a priori expectation or knowledge of a solution while A has something to do with a posteriori knowledge. The constant A adjudicates a delicate compromise between the two. Some inverse methods have acquired a more Bayesian stamp than others but we think that this is purely an accident of history. An outsider looking only at the equations that are actually solved and not at the accompanying philosophical justifications would have a difficult time separating the so-called Bayesian methods from the so-called empirical ones we think. The next three sections discuss three different approaches to the problem of inversion which have had considerable success in different fields. All three fit within the general framework that we have outlined but they are quite different in detail and in implementation. CITED REFERENCES AND FURTHER READING Craig . and Brown . 1986 Inverse ProblemsinAstronomy Bristol . Adam Hilger . Twomey S. 1977 Introduction to the .
