prior information
3.The establishment of the prior distribution is most important for Bayesian statistics,which contains two aspects , one is how to establish the prior distribution of parameters by a bit of non-information or prior information, the other is how to choose a proper prior distribution from so many ones.
4.The definition of the maximum likelihood estimator with the prior information (PMLE) is given in this paper, and the consistency and asymptotic normality of PMLE are proved.
5.For the more efficient use of prior information to decrease the cost of acceptance test, based on the reliability qualification test, a method about how to compose prior information provided in qualification test is put forward and a scheme of reliability acceptance test in binomial case is formulated in view of the meaning of sampling risk actually concerned by users and producers in acceptance test.
6.Thereby, the prior information in the product type test is utilized more sufficiently, and the volume of test work is reduced considerably in comparison with the traditional acceptance test under presupposition of quality assurance. Furthermore, the economical effect is gained.
7.An SNR estimation algorithm was d eveloped based on eigenvalue decomposition of the correlation matrix of the rece ived signals and the principle of minimum description length (MDL) in informatio n theory. The algorithm can estimate the SNR of digital modulation signals commo nly used in additional white Gaussian noise (AWGN) channels and multipath channe ls without prior information of the modulation type, baud rate or carrier freque ncy of the signals.
8.The last one is Local Area Accelerating Convergence (LAAC) method, which is based on prior known information of the conductivity distribution.
9.What makes the robots unique is that they learned to walk on different surfaces without any prior programming information from their inventors at the Massachusetts Institute of Technology in Boston , Cornell University in New York in the United States and Delft University of Technology in the Netherland.
10.We developed the concept of Shannon entropy function by employing prior distribution information and Kullback entropy concepts to obtain the maximum entropy function of the max-min problem and the gap function for VIP, equilibrium programming problem and the NLP are the special parametric optimizationproblems in chapter 3.In chapter 4, the mixed network equilibrium model is derived directly from the equilibrium programming and EP models for combined Wardrop principles under different information conditions are analyzed.
