| 1. | Maximum entropy method for nonlinear l1 problem
1问题的极大熵方法 |
| 2. | Maximum entropy method for linear programming with bounded variables
变量有界线性规划的极大熵方法 |
| 3. | Maximum entropy method and quadratic programming sub - problem ' s explicit solution
极大熵方法与二次规划子问题的显式解 |
| 4. | In this thesis the basic principle of maximum entropy method ( mem ) and its applications in image restoration are thoroughly discussed
最大熵方法是一种非线性的图像恢复方法，过去的研究主要围绕天文图像的处理而进行。 |
| 5. | A context - dependent polyphone disambiguation technology was proposed , combined with the decision tree and maximum entropy methods , the accuracy can be improved to 99 . 82 %
采取结合上下文信息及语法信息的多音字消歧技术，利用决策树和最大熵等模式识别方法，使注音正确率达到99 . 82 % 。 |
| 6. | According to the maximum entropy method , a program applied to compute reliability of cwr dynamic stability is worked out and put into practice to analyze reliability of cwr dynamic stability , getting the safety allowable temperature under design reliability index
根据反应极值最大熵拟合法编制了无缝线路动力稳定性可靠度计算程序，分析了高速铁路无缝线路动力稳定性的可靠度，得到满足目标可靠指标的允许温升。 |
| 7. | Maximum entropy method is an effective smoothing one for the finite min - max problem , which , by adding shannon ' s informational entropy as a regularizing term to the lagrangian function of min - max problem , yields a smooth function that uniformly approaches the non - smooth max - valued function
极大熵方法是解有限极大极小问题的一种有效光滑化法，它通过在极大极小问题的拉格朗日函数上引进shannon信息熵作正则项，给出一致逼近极大值函数的光滑函数。 |
| 8. | The second chapter reveals the mathematical essence of entropy regularization method for the finite min - max problem , through exploring the relationship between entropy regularization method and exponential penalty function method . the third chapter extends maximum entropy method to a general inequality constrained optimization problem and establishes the lagrangian regularization approach . the fourth chapter presents a unified framework for constructing penalty functions by virtue of the lagrangian regularization approach , and illustrates it by some specific penalty and barrier function examples
第一章为绪论，简单描述了熵正则化方法与罚函数法的研究现状；第二章，针对有限极大极小问题，通过研究熵正则化方法与指数(乘子)罚函数方法之间的关系，揭示熵正则方法的数学本质；第三章将极大熵方法推广到一般不等式约束优化问题上，建立了拉格朗日正则化方法；第四章利用第三章建立的拉格朗日正则化方法，给出一种构造罚函数的统一框架，并通过具体的罚和障碍函数例子加以说明。 |
| 9. | Further , some knowledge of information theory are introduced to describe the regularity of process system calls such as the sequential dependency relationship between neighboring system calls . the use of information theory provides theoretic proof for creating more effective detecting models . in the end , applying for the maximum entropy method in information theory , a maximum entropy model of intrusion detection is presented
同时，为了提高入侵检测的准确性，又在原有的马尔可夫链模型的基础上，引进信息理论中的信息熵，条件熵等概念来更好地刻画进程系统调用序列的时序依赖关系，从而为建立更好的检测模型提供信息理论依据。 |
