空变菲涅耳联合变换相关器

提出了菲涅耳联合变换相关器(Fresnel Joint Transform Correlator,FnJTC)结构,给出了数学推导过程,并通过计算机模拟验证了可行性及其与传统相关器所不同的相关特性。在相关过程第一阶段中,菲涅耳联合变换相关器对输入的联合图像作菲涅耳变换,代替了传统联合变换相关器(JTC)的傅里叶变换。与传统相关器相比,菲涅耳联合变换相关器是空变系统,相关峰值依赖于输入参考图像与目标图像的相似性、两图像之间的相对位置及参考图像(或目标图像)的线性相位调制。     

显微镜中的可变式假彩色编码

将可变式空间滤波器应用到显微镜中,不仅能实时地从显微镜视场里观察到无色标本的彩色图象,还能根据需要突出图象中某些特征.     

A Method for Neutralizing Entropy Measurement-Based Ransomware Detection Technologies Using Encoding Algorithms

Ransomware consists of malicious codes that restrict users from accessing their own files while demanding a ransom payment. Since the advent of ransomware, new and variant ransomwares have caused critical damage around the world, thus prompting the study of detection and prevention technologies against ransomware. Ransomware encrypts files, and encrypted files have a characteristic of increasing entropy. Due to this characteristic, a defense technology has emerged for detecting ransomware-infected files by measuring the entropy of clean and encrypted files based on a derived entropy threshold. Accordingly, attackers have applied a method in which entropy does not increase even if the files are encrypted, such that the ransomware-infected files cannot be detected through changes in entropy. Therefore, if the attacker applies a base64 encoding algorithm to the encrypted files, files infected by ransomware will have a low entropy value. This can eventually neutralize the technology for detecting files infected from ransomware based on entropy measurement. Therefore, in this paper, we propose a method to neutralize ransomware detection technologies using a more sophisticated entropy measurement method by applying various encoding algorithms including base64 and various file formats. To this end, we analyze the limitations and problems of the existing entropy measurement-based ransomware detection technologies using the encoding algorithm, and we propose a more effective neutralization method of ransomware detection technologies based on the analysis results.     

数字彩色编码方法研究

本文提出的数字彩色编码方法，利用数字图像处理技术实现光力学条纹的彩色编码，得到具有特定色序的直观性强的彩色条纹图，并通过对编码彩色条纹图的分析提出了条纹级次的自动识别方法，使彩色编码成为一种更加实用而有效的方法。     

短波差分跳频通信系统抗多音干扰的性能分析

针对应用于军事通信的短波差分跳频系统中存存敌意多音干扰的问题，建立了系统的多音干扰模型，采用一种联合一切尔诺大限的方法，从理论上导出了该系统（无编码）在加性高斯白噪声信道和瑞利衰落信道条件下抗多音干扰的比特误码率性能上界；并采用RS信道编码方法，对尢编码系统在瑞利衰落信道下误码率为10^-3时出现的差错平板进行了改善．数值结果表明编码后的系统较无编码系统能获得约7dB的性能增益，有效提高了抗多音干扰的能力．     

The Hardness of Polynomial Equation Solving

Elimination theory was at the origin of algebraic geometry in the nineteenth century and now deals with the algorithmic solving of multivariate polynomial equation systems over the complex numbers or, more generally, over an arbitrary algebraically closed field. In this paper we investigate the intrinsic sequential time complexity of universal elimination procedures for arbitrary continuous data structures encoding input and output objects of elimination theory (i.e., polynomial equation systems) and admitting the representation of certain limit objects. Our main result is the following: let there be given such a data structure and together with this data structure a universal elimination algorithm, say P, solving arbitrary parametric polynomial equation systems. Suppose that the algorithm P avoids unnecessary branchings and that P admits the efficient computation of certain natural limit objects (as, e.g., the Zariski closure of a given constructible algebraic set or the parametric greatest common divisor of two given algebraic families of univariate polynomials). Then P$ cannot be a polynomial time algorithm. The paper contains different variants of this result and discusses their practical implications.     

动态微粒场双脉冲全息图再现像的分离技术

双脉全息图可应用于动态微粒场中粒子形状、尺寸、密度和速度等分布参数的测定。但由于两个脉冲时刻所拍摄的粒子像只能同时再现,不能判断粒子运动速度的方向,在运动情况较复杂时,粒子的“配对”也很困难。本文提出一种技术,可以分别再现两个脉冲时刻的粒子场图像,从而实现粒子速度方向的判定,同时减小了配对困难。     

一种基于局部信息统计的虹膜分块编码方法

由于虹膜自身的稳定性、非侵犯性、不可更改性等优点,虹膜识别已经成为生物特征身份鉴别领域中的研究热点。但虹膜丰富的纹理和复杂的结构给特征提取和编码带来了很大困难。为尽可能地简化特征提取和编码方法,提高虹膜识别效率,提出了一种基于局部信息统计的虹膜分块编码方法。对原始人眼图像进行虹膜定位等预处理操作,得到归一化的虹膜纹理图像;分别根据虹膜局部信息与全局信息、局部信息与局部信息之间的比较关系进行分块编码;计算了不同虹膜代码之间的汉明(Hamming)距离。根据汉明距离给出识别结果。实验证明该方法有效、可行,具有较高的识别率和识别速度。