神经网络在图像处理中的应用

近几年，随着神经网络理论的深入研究，神经网络技术的并行性计算能力、非线性映射和自适应能力等优点得到了充分的认识，各种神经网络模型在图像处理领域中得到了广泛的应用．本文对各种流行的神经网络模型在图像处理领域中的应用进行了汇总，根据图像处理的具体内容对这些应用进行分类叙述，阐明了神经网络技术在图像处理领域中的优点和不足之处，并对将来神经网络技术在图像处理领域中的应用提出了几点期望．     

混合算术运算膜系统模块化设计方法

膜计算作为一种新兴的计算模型,现在已经得到很多学者的关注,但现阶段很多膜计算研究都是偏重于基础理论,应用研究很少。为了拓宽膜计算的应用研究领域,本文将基本的算术运算膜系统作为研究对象,提出一种运算膜系统模块化设计方法,得到了令人满意的结果,同时还给出后期研究的方向和研究中发现的待解决的问题。     

皮肤显微图像自动识别系统的研究

皮肤显微图像处理是医学图像处理的一个重要分支,在医疗卫生美容领域有非常广泛的应用价值和实际意义,本系统运用图像处理技术提取皮肤症状形状、大小、颜色特征,运用遗传算法和支持向量机相结合的方法进行特征选择。在此基础上用支持向量机建立分类器,对皮肤显微图像进行分类识别,实验结果表明该系统的识别性能较好。     

脉冲神经膜计算系统的研究进展及展望(英文)

脉冲神经膜计算系统是膜计算的一个新分支,不仅具有计算机科学研究意义,而且在生物建模和仿真方面有潜在的应用价值．文中介绍了脉冲神经膜计算系统的基本概念并给出了脉冲神经膜计算系统的一个例子;除了介绍标准脉冲神经膜计算系统外,还介绍若干广义的脉冲神经膜计算系统;概述了脉冲神经膜计算系统计算完备性和计算有效性两个方面的主要结果;指出了进一步研究脉冲神经膜计算系统的两个方向．     

自然计算的新分支——膜计算

作为自然计算的新分支,膜计算是当前计算机科学、数学、生物学和人工智能等多学科交叉的研究热点.概述膜计算的最新动态,以一个简单膜系统为例介绍膜计算的基本概念和基本原理,从细胞型、组织型和神经型三类膜系统以及它们的计算能力和计算效率方面介绍膜计算理论研究进展,通过概括膜计算国内外应用研究成果讨论其应用前景和方向,并从软硬件发展历程分析膜系统软硬实现研究现状.最后给出有关膜计算研究的重要网络资源、热点研究领域和重点关注的问题.     

智能监控系统中的图像识别与分析

当前,随着计算机通信技术和网络技术的快速发展,图像处理技术在科学技术领域中的地位愈来愈重要。图像识别属于智能监控设备中的重要技术组成部分,本文在概述智能监控系统的基础上,研究智能监控系统图像识别的关键技术,并对智能图像监控系统的图像识别与分类进行分析。     

基于最小PC构架的可配置计算平台及应用

在机器视觉、军事、航空照相等领域需要在有限的空间内设计出小型化、灵活的、能够完成图像处理功能的系统。文中设计了一种以裁剪了的PC1 0 4构架为基础的可配置计算平台 ,该系统的PCB电路板面积只有 90mm× 6 8mm。以一个目标识别图像处理应用系统为例 ,给出了图像协处理器的7个乘法器并行、7级流水的内部结构设计方案。能够实现任意小于 7× 7模板的 2维图像卷积处理算法 ,获得了较高的图像处理性能     

基于阈值的医学图像分割技术的计算机模拟及应用

随着现代计算机技术及图像处理技术的快速发展,图像分割作为图像分析、理解的基础,在诸多领域具有广泛的应用,尤其在医学方面。医学图像分割是医学图像处理和分析的关键步骤,也是其它高级医学图像分析和解释系统的核心组成部分。本文针对医学图像分割的分类、特征等进行了简要的介绍,对基于阈值的分割方法进行详尽的讨论并以计算机实际处理效果分析了各种基于阈值的分割方法的优缺点。     

带膜分裂和促进剂的通讯膜系统求解QSAT问题

膜计算是自然计算的一个分支,膜计算中所研究的模型均称为膜系统,而细胞间通讯是膜系统的一个重要特征。带膜分裂的通讯膜系统是一种分布式并行计算模型,可以在多项式时间内解决计算困难问题。文中将促进剂引入带膜分裂的类细胞型通讯膜系统,提出了膜系统的一种变型——带膜分裂和促进剂的通讯膜系统,其中,一个促进剂可以同时控制多条规则,而促进剂本身不参与该条规则的进化。文中研究了带膜分裂和促进剂的通讯膜系统的计算效率,证明该类膜系统在使用同向规则长度为2,每条规则中促进剂的个数最多为1时,可以在多项式时间内求解PSPACE完全问题(QSAT问题)的统一解。     

模糊推理在MBR膜通量仿真中的研究

当前,将MBR大规模推广并加以应用的过程中最大的阻碍是膜污染问题。运用模糊推理方法将MBR系统的混合液污泥浓度(MLSS)、操作压力、温度等输入参数转换成模糊集,并用改进的基于梯度的实时学习算法进行模糊计算;将通过计算得到的膜通量的模糊值反模糊化,得出系统膜通量的明确评价值。这样就可以找出在膜通量最大情况下的输入参数,以便改进输入参数,达到更好的出水水质。该方法能够使传统的梯度下降方法中所存在的收敛速度和震荡之间的冲突问题从根本上得到解决,并且仿真计算结果与实际实验情况相符。     

Optimal multi-level thresholding with membrane computing

The conventional methods are not effective and efficient for image multi-level thresholding due to time-consuming and expensive computation cost. The multi-level thresholding problem can be posed as an optimization problem, optimizing some thresholding criterion. In this paper, membrane computing is introduced to propose an efficient and robust multi-level thresholding method, where a cell-like P system with the nested structure of three layers is designed as its computing framework. Moreover, an improved velocity-position model is developed to evolve the objects in membranes based on the special membrane structure and communication mechanism of objects. Under the control of evolution-communication mechanism of objects, the cell-like P system can efficiently exploit the best multi-level thresholds for an image. Simulation experiments on nine standard images compare the proposed multi-level thresholding method with several state-of-the-art multi-level thresholding methods and demonstrate its superiority.     

Systematic evaluation of peer‐to‐peer systems using PeerfactSim.KOM

Comparative evaluations of peer‐to‐peer protocols through simulations are a viable approach to judge the performance and costs of the individual protocols in large‐scale networks. In order to support this work, we present the peer‐to‐peer system simulator PeerfactSim.KOM, which we extended over the last years. PeerfactSim.KOM comes with an extensive layer model to support various facets and protocols of peer‐to‐peer networking. In this article, we describe PeerfactSim.KOM and show how it can be used for detailed measurements of large‐scale peer‐to‐peer networks. We enhanced PeerfactSim.KOM with a fine‐grained analyzer concept, with exhaustive automated measurements and gnuplot generators as well as a coordination control to evaluate sets of experiment setups in parallel. Thus, by configuring all experiments and protocols only once and starting the simulator, all desired measurements are performed, analyzed, evaluated, and combined, resulting in a holistic environment for the comparative evaluation of peer‐to‐peer systems. An immediate comparison of different configurations and overlays under different aspects is possible directly after the execution without any manual post‐processing. Copyright © 2015 John Wiley & Sons, Ltd.     

On the Computational Complexity of P Automata

We characterize the classes of languages over finite alphabets which may be described by P automata, i.e., accepting P systems with communication rules only. Motivated by properties of natural computing systems, and the actual behavior of P automata, we study computational complexity classes with a certain restriction on the use of the available workspace in the course of computations and relate these to the language classes described by P automata. We prove that if the rules of the P system are applied sequentially, then the accepted language class is strictly included in the class of languages accepted by one-way Turing machines with a logarithmically bounded workspace, and if the rules are applied in the maximally parallel manner, then the class of context-sensitive languages is obtained.     

非结构化P2P系统Overlay优化技术综述

非结构化P2P Overlay网络的结构松散, 网络中资源的分布没有明确的限制, 这使得非结构化P2P Overlay网络中的资源搜索在很大程度上依赖于通信开销巨大的泛洪法, 因而非结构化P2P系统在伸缩性, 可用性等方面, 存在明显的不足. 非结构化P2POverlay网络的上述特点决定了非结构化P2P Overlay优化技术的重要性. 本文分四大类别, 对非结构化P2P Overlay优化技术进行了介绍, 分析比较了各类方法的优劣以及它们的适用场合, 并在此基础上对未来工作进行了展望.     

A flexible command generation technique for application in dialogue systems

An important problem in the design of image processing systems is the specification of appropriate command structures for control of dedicated hardware and software functions. This paper describes a general and flexible method for the definition and processing of specialized commands. The idea is to generalize the specification of parameters within procedures by allowing—in a well-controlled way—a few syntactic extensions. The paper presents the extension mechanism, demonstrates the power of the command processor by practical examples and discusses some critical points.     

Adaptive fuzzy spiking neural P systems for fuzzy inference and learning

Fuzzy spiking neural P systems (in short, FSN P systems) are a novel class of distributed parallel computing models, which can model fuzzy production rules and apply their dynamic firing mechanism to achieve fuzzy reasoning. However, these systems lack adaptive/learning ability. Addressing this problem, a class of FSN P systems are proposed by introducing some new features, called adaptive fuzzy spiking neural P systems (in short, AFSN P systems). AFSN P systems not only can model weighted fuzzy production rules in fuzzy knowledge base but also can perform dynamically fuzzy reasoning. It is important to note that AFSN P systems have learning ability like neural networks. Based on neuron's firing mechanisms, a fuzzy reasoning algorithm and a learning algorithm are developed. Moreover, an example is included to illustrate the learning ability of AFSN P systems.     

Membrane automata with priorities

In this paper the one-way P automata with priorities are introduced. Such automata are P systems where the membranes are only allowed to consume objects from parent membranes, under the given conditions. The result of computation of these systems is the set of multiset sequences consumed by skin membrane into the system. The rules associated in some order with each membrane cannot modify any objects, they can only move them through membrane. We show that P automata with priorities and two membranes can accept every recursively enumerated language.     

A generic decentralized trust management framework

This paper describes TRUSTPACK , a decentralized trust management framework that provides trust management as a generic service. TRUSTPACK is unique in that it does not provide a central service. Instead, it is run by many autonomous services. This design enables TRUSTPACK to alleviate privacy concerns, as well as potentially provide better personalization and scalability when compared with current centralized solutions. A major component of TRUSTPACK is a generic decentralized graph query processing framework called GRAPHPACK , which was also developed as part of this work. GRAPHPACK consists of a decentralized graph processing language as well as an execution engine, as elaborated in this paper. The paper also presents several examples and a case study showing how TRUSTPACK can be used to handle various trust management scenarios, as well as its incorporation in an existing third party P2P file sharing application. Prototypes of TRUSTPACK and GRAPHPACK are available as open source projects at http://code.google.com/p/trustpack/ and http://code.google.com/p/graphpack/ , respectively. Copyright © 2013 John Wiley & Sons, Ltd.     

基于DHT的P2P系统的负载均衡算法

在基于DHT的结构化P2P系统中，DHT的使用以及节点处理能力的不同导致系统中节点的负载不均衡．现有的负载均衡算法存在两个不足：①负载的转移没有考虑节点之间的链路延迟；②算法依赖于系统中固定位置的某些节点．提出了分布式负载均衡算法：每个节点周期性的收集系统局部负载信息，然后选择链路延迟较小的节点进行负载转移．算法依赖于系统中的所有节点，解决了单点失败问题．同时，负载的转移是在链路延迟较小的节点之间进行的．仿真实验表明，①对于各种系统利用率，该算法都可以获得理想的负载均衡效果；②算法可以使负载转移开销减少45％以上．     

Superpipelined high-performance optical-flow computation architecture

Optical-flow computation is a well-known technique and there are important fields in which the application of this visual modality commands high interest. Nevertheless, most real-world applications require real-time processing, an issue which has only recently been addressed. Most real-time systems described to date use basic models which limit their applicability to generic tasks, especially when fast motion is presented or when subpixel motion resolution is required. Therefore, instead of implementing a complex optical-flow approach, we describe here a very high-frame-rate optical-flow processing system. Recent advances in image sensor technology make it possible nowadays to use high-frame-rate sensors to properly sample fast motion (i.e. as a low-motion scene), which makes a gradient-based approach one of the best options in terms of accuracy and consumption of resources for any real-time implementation. Taking advantage of the regular data flow of this kind of algorithm, our approach implements a novel superpipelined, fully parallelized architecture for optical-flow processing. The system is fully working and is organized into more than 70 pipeline stages, which achieve a data throughput of one pixel per clock cycle. This computing scheme is well suited to FPGA technology and VLSI implementation. The developed customized DSP architecture is capable of processing up to 170 frames per second at a resolution of 800 × 600 pixels. We discuss the advantages of high-frame-rate processing and justify the optical-flow model chosen for the implementation. We analyze this architecture, measure the system resource requirements using FPGA devices and finally evaluate the system’s performance and compare it with other approaches described in the literature.