参数稀疏信号非均匀采样性能分析

提出了一种参数稀疏信号的时间交替周期非均匀采样方案。相对于非均匀采样,周期非均匀采样可以在降低系统复杂度的前提下依然保持较高的转换速率。通过仿真证明,非均匀采样样本的超分辨率特性可以提高非线性最小二乘周期图谱估计的重构性能。     

新型军械装备损坏程度评估方法研究

根据新型军械装备损坏程度具有不确定性的特点,提出了基于D-S证据理论的新型军械装备损坏程度评估方法,并求出了新型军械装备损坏程度区分.通过对典型新型军械装备损坏程度的评估,验证了该方法的有效性和实用性.     

平均保障延误时间（MLDT）建模方法研究

针对现代装备系统的精确化保障要求,对装备保障的主要参数指标MLDT进行了建模分析,主要分析了三种计算方法：图估法、解析法和基于排队论的MLDT建模理论,解决了评估MLDT指标时的定量计算问题。     

一种改进的生物模糊记忆入侵检测模型

入侵检测技术是保证计算机网络安全的核心技术之一,在网络安全领域内发挥着重要的作用。但是目前的入侵检测系统不够完善,文章通过对记忆原理和模糊理论的分析将其应用在已有的入侵检测系统中,提出了一种新的基于生物模糊记忆的入侵检测系统模型,并用实验证明该模型具有更好的检测效果。     

基于粗糙集的进化神经网络入侵检测系统研究

针对目前实时入侵检测系统所处理的网络数据具有的非线性和高维的特点,提出基于粗糙集理论的进化神经网络入侵检测方法。对网络中截获的数据,利用粗糙集属性约简方法对其属性集进行约简,得到影响分类精度的重要属性。把约简后形成的训练样本进行数值化和归一化处理,作为神经网络的输入数据,再利用遗传算法较强的宏观搜索能力和全局寻优的特点,优化神经网络权值,并在此基础上进行神经网络学习,从而建立入侵检测系统的优化分析模型。实验结果表明,该算法学习速度快,有效提高了入侵检测系统的检测效率。     

Theory and techniques of data mining in CGF behavior modeling

For the large quantity of data,rules and models generated in the course of computer generated forces (CGFs) behavior modeling,the common analytical methods are statistical methods based on the tactical rules,tactical doctrine and empirical knowledge.However,from the viewpoint of data mining,we can find many of these analytical methods are also each-and-every different data mining methods.In this paper,we survey the data mining theory and techniques that have appeared in the course of CGF behavior modeling f...     

Restrictive mechanism of flow control among non-cooperative Internet users

The flow and congestion control methods based on one-shot game model with non-cooperative game theory can explain the non-cooperative behavior of Internet users.However,the low effciency of equilibrium solutions affects their utility.Here the behavior of flow and congestion control based on infinitely repeated game models is addressed;the repeated and infinitely repeated flow and congestion control game model is presented; the existence and optimization of the Nash equilibrium point are proved;the discount ...     

校园网网络事件源定位技术研究

为了解决在校园网内部分网络安全事件和故障事件中只能确认攻击和事故的发生,而无法确定攻击和事故的源头这一问题.文章提出一种三步骤的校园网内网网络事件源定位模型.该模型将神经网络和证据理论相结合应用于攻击源定位.提高了校园网内网攻击定位的效率和准确性.     

Measuring universal intelligence: Towards an anytime intelligence test

In this paper, we develop the idea of a universal anytime intelligence test. The meaning of the terms “universal” and “anytime” is manifold here: the test should be able to measure the intelligence of any biological or artificial system that exists at this time or in the future. It should also be able to evaluate both inept and brilliant systems (any intelligence level) as well as very slow to very fast systems (any time scale). Also, the test may be interrupted at any time, producing an approximation to the intelligence score, in such a way that the more time is left for the test, the better the assessment will be. In order to do this, our test proposal is based on previous works on the measurement of machine intelligence based on Kolmogorov complexity and universal distributions, which were developed in the late 1990s (C-tests and compression-enhanced Turing tests). It is also based on the more recent idea of measuring intelligence through dynamic/interactive tests held against a universal distribution of environments. We discuss some of these tests and highlight their limitations since we want to construct a test that is both general and practical. Consequently, we introduce many new ideas that develop early “compression tests” and the more recent definition of “universal intelligence” in order to design new “universal intelligence tests”, where a feasible implementation has been a design requirement. One of these tests is the “anytime intelligence test”, which adapts to the examinee's level of intelligence in order to obtain an intelligence score within a limited time.     

Robust solutions to Stackelberg games: Addressing bounded rationality and limited observations in human cognition

How do we build algorithms for agent interactions with human adversaries? Stackelberg games are natural models for many important applications that involve human interaction, such as oligopolistic markets and security domains. In Stackelberg games, one player, the leader, commits to a strategy and the follower makes her decision with knowledge of the leader's commitment. Existing algorithms for Stackelberg games efficiently find optimal solutions (leader strategy), but they critically assume that the follower plays optimally. Unfortunately, in many applications, agents face human followers (adversaries) who — because of their bounded rationality and limited observation of the leader strategy — may deviate from their expected optimal response. In other words, human adversaries' decisions are biased due to their bounded rationality and limited observations. Not taking into account these likely deviations when dealing with human adversaries may cause an unacceptable degradation in the leader's reward, particularly in security applications where these algorithms have seen deployment. The objective of this paper therefore is to investigate how to build algorithms for agent interactions with human adversaries.To address this crucial problem, this paper introduces a new mixed-integer linear program (MILP) for Stackelberg games to consider human adversaries, incorporating: (i) novel anchoring theories on human perception of probability distributions and (ii) robustness approaches for MILPs to address human imprecision. Since this new approach considers human adversaries, traditional proofs of correctness or optimality are insufficient; instead, it is necessary to rely on empirical validation. To that end, this paper considers four settings based on real deployed security systems at Los Angeles International Airport (Pita et al., 2008 [35]), and compares 6 different approaches (three based on our new approach and three previous approaches), in 4 different observability conditions, involving 218 human subjects playing 2960 games in total. The final conclusion is that a model which incorporates both the ideas of robustness and anchoring achieves statistically significant higher rewards and also maintains equivalent or faster solution speeds compared to existing approaches.