Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at     

Accurate estimation of environment parameters from ultrasonic data

This paper describes a robust and accurate ultrasonic sensing system for a mobile robot. The system continuously updates a local map of the environment in which obstacles are represented by straight lines or points in a robot centered coordinate frame. The presented algorithms use a Kalman filter for the reduction of the noise in the ultrasonic data and use a systematical error correction (‘bundle correction’) to reduce the uncertainty in obstacle direction. Experiments are carried out in simulation and with a real mobile robot system. Results show that the accuracy with which line parameters can be estimated is in the order of 1 degree for the orientation and about 2 cm for the position. The effect of the bundle correction is significant and maximal when the robot approaches walls under a small angle.     

运动汽车图像静态视点平滑特征优化仿真

由于运动汽车图像在特征采集过程中,汽车处于高速运动状态,采集的过程无法与汽车完全同步,造成汽车的特征像素分量在高速运动中丢失,产生较大的像素运动噪声,使得汽车图像边缘高频特征因为运动干扰而模糊.传统的平滑过渡方法在对运动汽车图像进行平滑处理时,按照图像中像元灰度值计算突变特性,但受到像素丢失与噪声无法抑制的影响,无法解决运动汽车图像高频分量对图像像元灰度值的干扰问题.提出基于替身运动DR算法的运动汽车图像静态视点平滑过渡方法,用替身像素描述汽车在场景中的运动特征,替身像素在场景中运动并同其它汽车的替身进行交互,采用局部化的车辆模型提高运动汽车场景的逼真度,通过依据替身运动的平滑过渡算法完成归一化线性运动汽车图像静态视点的平滑过渡,解决了运动汽车图像的平滑过渡问题.实验结果说明,所提方法可确保运动汽车图像边缘锐化,有效处理平滑噪声和锐化边缘.     

A fuzzy-based interleaved multi-hop authentication scheme in wireless sensor networks

In sensor networks, a compromised node can either generate fabricated reports with false votes or inject false votes into real reports, which causes severe damage such as false alarms, energy drain and information loss. An interleaved hop-by-hop authentication (IHA) scheme addresses the former attack by detecting and filtering false reports in a deterministic and hop-by-hop fashion. Unfortunately, in IHA, all en-route nodes must join to verify reports while only a few are necessary to the authentication procedure. In this paper, we propose a fuzzy-based interleaved multi-hop authentication scheme based on IHA. In our scheme, the fuzzy logic system only selects some nodes for verification based on the network characteristics. Moreover, we apply a voting method and a hash-based key assignment mechanism to improve network security. Through performance evaluation, the proposed scheme is found to save up to 13% of the energy consumption and to provide more network protection compared to IHA.     

Space and time localization for the estimation of distributed parameters in a finite element model

In this paper we study the problem of estimating the possibly non-homogeneous material coefficients inside a physical system, from transient excitations and measurements made in a few points on the boundary. We assume there is available an adequate Finite Element (FEM) model of the system, whose distributed physical parameters must be estimated from the experimental data.We propose a space–time localization approach that gives a better conditioned estimation problem, without the need of an expensive regularization. Some experimental results obtained on an elastic system with random coefficients are given.     

基于FPGA的高速自适应滤波器的实现

在LMS算法进行变步长处理的基础上,结合驰豫超前流水线技术和时序重构技术提出了创新结构和改进算法,在FPGA的仿真综合环境中设计实现了该高速自适应滤波器,并且在AlteraDE2-70开发板上进行了板级测试。     

探讨基于Linux操作系统下的防火墙技术与应用

文章阐述了防火墙的基本原理、特点和功能,并通过实例实现基于Linux系统环境下,使用防火墙的方法。     

用单片机实现各音色电子琴

介绍了音色概念以及音色的决定性因素。针对传统电子琴采用以滤波网络电路对某次谐波量进行放大或衰减来模拟音色的方法,提出了一种新的实现方案,即采用以单片机为主体的数字电路,"软硬"兼施,模拟音色的波形,再通过D/A输出,从而达到听觉上的模拟音色的目的。解决了传统的模拟音色电子电路的设计的复杂性和多变性问题。给出了具体的实现电路、软件设计方法和步骤。     

谐波滤波装置在化工生产上的应用

本文介绍了谐波滤波装置在化工生产的应用和效果，通过滤波装置对高次谐波进行滤波，降低电网电压的畸变率，减少高次谐波电流对电力系统网络其他电气设备的危害，并且对其低功率因数进行无功功率补偿，以达到节约能源之目的。