METASYSTEMS AND THE MAXIMUM ENTROPY PRINCIPLE

Abstract

A probabilistic model of data that is an extension of the standard relational model predominant in database management applications is introduced in [Cavallo and Pittarelli. 1987] and elaborated in [Pittarelli, 1993 and 1994]. A probabilistic database instance is identical to what, in the GSPS hierarchy of systems types [Klir, 1985], is referred to as a probabilistic structure behavior system.

We discuss the problem of modifying a probabilistic structure system to accommodate new information. This corresponds to what, in the literature on databases, is referred to as an update. A sequence of probabilistic structure systems, each the result of modifying its predecessor, may be regarded as a metasystem [Klir, 1985]. We will focus on computational aspects of replacing one structure system with its successor. A distinction is made between global and local updating of a structure system, using Bayesian or quasi-Bayesian methods. A global update consists of selecting an element of the reconstruction family, updating it appropriately, then projecting. A local update propagates the effect of updating a single behavior function to the other elements of the structure system. It is shown that Bayesian local updating produces the same structure system that results when the maximum entropy element of the reconstruction family is selected as the basis for a Bayesian global update.     

基于特征聚合与最大熵的文本分类算法

网络信息浩如烟海又纷繁芜杂,从中掌握最有效的信息是信息处理的一大目标,而文本分类是组织和管理数据的有力手段.由于最大熵模型可以综合观察到的各种相关或不相关的概率知识,具有对许多问题的处理都可以达到较好的结果的优势,将最大熵模型引入到中文文本分类的研究中,并通过使用一种特征聚合的算法改进特征选择的有效性.实验表明与Bayes、KNN和SVM这三种性能优越的算法相比,基于最大熵的文本分类算法可取得较之更优的分类精度.     

Vague集的偏熵与关联熵

在文献[1]的基础上,定义Vague集的偏熵,关联熵和关联熵系数等新概念.对其主要性质进行讨论,并给出了关联熵系数在相似度量中的应用.     

残损模糊图像的最大熵恢复

模糊图像存在较大的信息冗余,这一特点有助于残损模糊图像的恢复处理。最大熵恢复是复原残损模糊图像的理想法之一。本文在简单描述基于微分方程初值问题的最大熵恢复方法的基础上,对其进行了推广,给出了在非周期反卷积模型下该方法的一个实现算法,并用实验验证了其在处理局部受损的模糊图像时的有效性。该算法计算量适中,恢复效果好,可在一段的PC机上快速进行。     

基于信息熵的图像分割阈值迭代改进算法

将信息熵理论和分割阚值迭代法融合,提出一种基于图像目标信息熵的阈值迭代选取方法,并将这种改进的迭代法与目前常见的最大类间方差法和最大熵法进行比较.实验表明,此算法具有速度快,总体分割效果好的优点.     

改进的非线性连续－离散系统的极大似然参数估计及其应用

对Ｊａｔｅｇａｏｎｋａｒ等人给出的同时计及过程及观测噪声的非线性连续－离散系统的极大似然算法从两个方面进行了改进：１）给出了计算灵敏度的最佳摄动有限差分算法，避免了普通有限差分法计算灵敏度矩阵时需人为选择参数摄动量大小而带来的缺点；２）给出了具有快速三角化平方根滤波的极大似然算法，提高了原算法的数值稳定性．上述改进算法经应用于飞行器系统参数估计证明了方法的有效性。