基于Q—learning的一种多Agent系统结构模型

多Agent系统是近年来比较热门的一个研究领域,而Q-learning算法是强化学习算法中比较著名的算法,也是应用最广泛的一种强化学习算法。以单Agent强化学习Qlearning算法为基础,提出了一种新的学习协作算法,并根据此算法提出了一种新的多Agent系统体系结构模型,该结构的最大特点是提出了知识共享机制、团队结构思想和引入了服务商概念,最后通过仿真实验说明了该结构体系的优越性。     

基于频谱分析的Procrustes统计步态识别算法

在信息安全越加重要的现代社会,步态识别以其特有的优势作为一种身份识别手段,得到了很多关注.提出一种基于Procrustes均值形状的傅里叶频谱分析(FSAOPMS)的适用于多视角的步态识别方法.利用Procrustes统计形状分析方法将步态序列中人体轮廓的连续步态变化表示成一个紧致的Procrustes均值形状(PMS...     

基于FPGA的谐波检测装置设计

利用现场可编程门阵列(FPGA)运算速度快、效率高的特点,使用FIR硬件IP核实现前置线性相位低通滤波通道,使用FFT硬件IP核实现加窗插值修正FFT算法,设计针对电力系统的高次谐波检测装置。     

A verifiable multi-secret sharing scheme based on cellular automata

In this paper, we propose a verifiable (t, n)-threshold multi-secret sharing scheme, based on one-dimensional cellular automata where the number of secrets is not restricted by n or t. We show that our scheme can be used to solve an open problem proposed recently in Alvarez et al. (2008) [G. Alvarez, L. Hernández Encinas, A. Martín del Rey, A multisecret sharing scheme for color images based on cellular automata, Information Sciences 178 (2008) 4382-4395].     

基于嵌入式系统的电机振动分析仪设计

本文介绍了一种利用触控式面板模块工具在WindowsCE系统上开发LabVIEW程序的方法,并将该方法运用到对电机振动测量与分析上,构成了以嵌入式系统为平台的便携式电机振动分析设备。应用LabVIEW软件的强大数学运算功能对振动信号作频谱分析,作为电机故障的预防和诊断依据,具有重要的意义。     

基于Pro/Intralink的协同设计

Pro/Engineer三维设计软件的应用越来越普遍,由于其数据的相互关联性及复杂性的原因,在进行协同设计时,出现了一些问题。如因某零件的丢失或改名导致整个系统模型打开失败、模型的及时更新、重复性设计、数据的共享及数据安全等等。基于Pro/Intralink系统的结构设计则可以很好地实现协同设计。该文介绍了基于Pro/Intralink下的协同设计。     

Phototherapy and the benefits of LEDs

Abstract— Light sources with wavelengths from near‐UV to near‐IR can cure skin diseases, relieve pain in the body, reduce wrinkles on the skin, treat acne on the face, grow hairs on head, and heal various kinds of other diseases. This is called phototherapy. Near‐UV, visible, and near‐IR LEDs now enable phototherapy viable for personal use because of the possibility of controlling the intensity of LED light with specific wavelengths. The medical applications of LEDs for phototherapy are reviewed.     

A high quality and small shadow size visual secret sharing scheme based on hybrid strategy for grayscale images

Many secret sharing schemes for digital images have been developed in recent decades. Traditional schemes typically must deal with the problem of computational complexity, and other visual secret sharing schemes come with a higher transmission cost and storage cost; that is, each shadow size is m times as big as the original secret image. The new (2,n) secret sharing scheme for grayscale images proposed in this paper is based a combination of acceptable image quality using block truncation coding (BTC), high compression ratio discrete wavelet transform (DWT) and good subjective performance of the vector quantization (VQ) technique. Experimental results confirm that our proposed scheme not only generates a high quality reconstructed original image but also generates small, random-like grayscale shadows.     

A novel Parzen probabilistic neural network based noncoherent detection algorithm for distributed ultra-wideband sensors

Ultra-wideband (UWB) has been widely recommended for significant commercial and military applications. However, the well-derived coherent structures for UWB signal detection are either computationally complex or hardware impractical in the presence of the intensive multipath propagations. In this article, based on the nonparametric Parzen window estimator and the probabilistic neural networks, we suggest a low-complexity and noncoherent UWB detector in the context of distributed wireless sensor networks (WSNs). A novel characteristic spectrum is firstly developed through a sequence of blind signal transforms. Then, from a pattern recognition perspective, four features are extracted from it to fully exploit the inherent property of UWB multipath signals. The established feature space is further mapped into a two-dimensional plane by feature combination in order to simplify algorithm complexity. Consequently, UWB signal detection is formulated to recognize the received patterns in this formed 2-D feature plane. With the excellent capability of fast convergence and parallel implementation, the Parzen Probabilistic Neural Network (PPNN) is introduced to estimate a posteriori probability of the developed patterns. Based on the underlying Bayesian rule of PPNN, the asymptotical optimal decision bound is finally determined in the feature plane. Numerical simulations also validate the advantages of our proposed algorithm.     

无线传感器网络动态频谱分配方案

针对无线传感器网络带宽与能量受限问题,以最大化频谱利用和最小化频谱切换为目标,兼顾优先级和公平性指标,构造最大化系统整体性能的目标函数。在此基础上,提出一种适合无线传感器网络的动态频谱分配方案。仿真结果表明,该频谱分配方案在考虑优先级的同时能够公平地分配频谱资源,实现最小化频谱切换。