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This paper investigates tracking control of vehicular ad hoc networks (VANETs) with random switching topologies. The network topology by which the vehicles communicate with each other at any time is a directed graph (or digraph) with a spanning tree. The switching of topology is governed by a Markov chain. A set of distributed switching controllers for tracking control is derived in the context of...
In order to solve the problem of scheduling delay-constrain heterogeneous data traffic in wireless industrial network, we propose the Traffic Aware Multiple Slotframes scheduling algorithm. It includes two main procedures: Compute available slot set and Allocate communication resources according to the requirement of data traffic. And then we give the detail description of the algorithm used in star...
One-dimensional geometric random graphs are constructed by distributing n nodes uniformly and independently on a unit interval and then assigning an undirected edge between any two nodes that have a distance at most rn. These graphs have received much interest and been used in various applications including wireless networks. A threshold of rn for connectivity is known as r*n = ln n/n in the literature...
This work presents an intelligent acoustic methodology for detection of defective porcelain station post insulators, which are widely used in substations in the form of column presenting several sheds. The acoustic emission inspection aims to detect cracks or fissures in a particular shed, which will have its insulating capacity severely decreased, if cracked. The test is done by gently striking the...
A reasonable unit restoration plan is pivotal for the restoration of a power system after blackout. In this paper, the units to be restored are divided into two types: network-layer units and plant-layer units. By analyzing their interactions between each other and the respective contributions to the system restoration, an optimization method of unit restoration based on NNIA for power system restoration...
This paper presents the adaptive analog hardware implementation of a MLP (multilayer perceptron architecture) ANN (artificial neural networks) for online nonlinear system operation. Neurons are implemented by bipolar differential pairs with tangent hyperbolic activation function. A bipolar current multiplier and a linearized differential amplifier are proposed for storing and adjusting the weights...
Extreme Learning Machine (ELM) is a noniterative training method suited for Single Layer Feed Forward Neural Networks (SLFF-NN). Typically, a hardware neural network is trained before implementation in order to avoid additional on-chip occupation, delay and performance degradation. However, ELM provides fixed-time learning capability and simplifies the process of re-training a neural network once...
In this study, a novel common mode multi-phase half-wave semi-synchronous rectifier is investigated for applications in wireless energy transfer. The circuit is intended to alleviate variations of the load resistance or coupling coefficient factor while maintaining high efficiency. The proposed rectifier structure is based on the connection of semi-controlled multiple half-wave rectifier topology...
In this paper we present an advanced software tool designed for a multi-criteria optimization of self-organizing neural networks (SOMs) for their effective implementation in hardware. Problems that we have to deal with in this type of implementations are radically different from those that occur in only pure software realizations. Therefore, although there are many available systems to simulate NNs,...
Colored Petri nets are widely used to model Automated Manufacturing Systems thanks to their compactness to describe complex networked systems. Compared to general Petri nets, they allow many folding techniques so as to condense the system model. With them, many control synthesis problems are reduced to the solution of matrix operations. Supervisory control techniques can be realized in a computationally...
We investigate the problem of real-time self-tracking of tagged objects in a new system with low-cost “smart” tags. These tiny and battery-less devices will play a pivotal role in the infrastructure of the Internet of Things (IoT). With capabilities of low-power computation and tag-to-tag backscattered communication, no readers will be needed for running the Radio Frequency Identification (RFID) system...
Validation of high-speed interface performance in a given design space from a Signal Integrity (SI) perspective requires Bit Error Rate (BER) computation. Eye Height (EH) and Eye Width (EW) are used to determine the quality of an interface for a given set of design parameters and frequency of operation. EH, EW and BER estimation requires Time Domain (TD) simulation of complex channel models over billions...
This paper presents a signal processing technique for segmenting short speech utterances into unvoiced and voiced sections and identifying points where the spectrum becomes steady. The segmentation process is part of a system for deriving musculoskeletal articulation data from disordered utterances, in order to provide training feedback for people with speech articulation problem. The approach implement...
Fast and robust traffic sign recognition is very important but difficult for the safety driving assist systems. This study addresses the fast and robust traffic sign recognition to enhance safety driving. We first adopt the typical Hough transform methods to implement coarse-grained locating of the candidate regions (shapes of rectangle, triangle and circle, etc.) of the traffic signs; and then propose...
The U.S. Army requires the evaluation of new weapon and vehicle systems through the use of experimental testing and Vulnerability/Lethality (V/L) modeling & simulation (M&S). The current M&S methods being utilized often require significant amounts of time and subject matter expertise. This typically means that quick results cannot be provided when needed to address new threats encountered...
Optimization of neural network topology, weights and neuron activation functions for given data set and problem is not an easy task. In this article, a technique for automatic configuration of parameters topology for feedforward artificial neural networks (ANN) is presented. The determination of optimal parameters is formulated as an optimization problem, solved with the use of meta-heuristic Multiple...
The pursuit problem is a conventional benchmark in distributed artificial intelligence research. The focal point of previous work in this domain has been the development of coordination mechanisms for predators that cooperatively hunt prey in a typically discrete grid world. This paper investigates a pursuit problem in a continuous torus field on the basis of swarm robotics. Twenty predator robots...
This paper describes the methodology for implementation of artificial neural networks with adaptable parameters (weights, connections, number of neurons) on fixed-point embedded systems. Components of neuron unit and interconnecting matrix are discussed. Particular example of implementation on PIC18F46K80 is given. Results are discussed in appropriate part.
As wireless networks have pervaded as an access network to the Internet, various contents are delivered also on them. However, the performance of wireless networks suffers from sudden fading or shadowing. When we use TCP for downloading large files as usual, its performance often decreases due to the following three major TCP features: shrunk window size which is caused by congestion avoidance feature,...
In large-scale online complex networks (Wikipedia, Facebook, Twitter, etc.) finding nodes related to a specific topic is a strategic research subject. This article focuses on two central notions in this context: communities (groups of highly connected nodes) and proximity measures (indicating whether nodes are topologically close). We propose a parameterized proximity measure which, given a set of...
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