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2005 IEEE International 48th Midwest Symposium on Circuits and systems, MWSCAS 2005

作者： Teli, Purvi S. Abdel-Aty-Zohdy, Hoda S. Line Vogel, F. Ewing, Robert L. Microelectronics System Design Laboratory Department of Electrical and System Engineering Oakland University Rochester MI 48309 GraphiTech Inc. St. Clair Shores MI 48080 Air Force Research Laboratory Information Directorate Wright-Patterson AFB OH 45433

ISBN: (纸本)0780391977

Intelligent power management for dry cell batteries may be accomplished by external circuitry which is connected to the individual power cells. In comparison, the presented Graphite circuit model, along with lead-acid battery technology facilitates the power management of wet cells in sealed packaging. This paper reiterates the Piezo ElectroChemical Transducer (PECT) effect based on the intercalation of graphite with sulfuric acid;Introduces a first attempt at developing a dynamic circuit model which will facilitate for a wide range of smart PECT applications. The paper also addresses the usage of PECT effect device for smart battery management, which operates in sulfuric acid environment. The developed dynamic impedance circuit model of PECT effect device can be used further to understand the changes in resistance and reactance properties of PECT device with the change in the temperature, voltage, current, stages, type of graphite and the concentration of sulfuric acid of electrochemical intercalation of graphite with sulfuric acid. © 2005 IEEE.

关键词： Photoelectrochemical cells

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A genetic algorithm tracking model for product deployment in telecom services

A genetic algorithm tracking model for product deployment in...

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： L. Murphy H.S. Abdel-Aty-Zohdy M. Hashem-Sherif Microelectronics System Design Laboratory Electrical and Systems Engineering Oakland University Rochester MI USA AT and T Bell Laboratories Inc. Middletown NJ USA

Genetic algorithms (GA) are designed to search for, discover and emphasize good solutions by applying selection and crossover techniques, inspired by nature, to supply solutions to engineering systems. Genetic algorithms operate on pieces of information like nature does on genes in the course of evolution. All individuals of one generation are evaluated by a fitness function. This paper presents an approach to implement a genetic algorithm to depict a recently developed "Integrated Model" for defect tracking for product deployment in telecommunication systems by means of a solution space representing target variables. The genetic algorithm inputs these target values as dynamic input measurements. From these measurements, the best possible fused values are found for the target variables. The goal of the genetic algorithm is dynamically to update the parameters applied to the input measurements to find the optimum solution for the defect tracking model system. Focus will be given to one dimension of sensor input measurements consisting of three four-bit binary sensor inputs varying within a given range of data points. The genetic algorithm is applied to these inputs by means of a 64 6-bit random member binary population using the "half-sibling and a clone" (HSAC) technique of crossover and mutation. The population members are evaluated using a fitness function where the fittest individuals are retained to survive and produce offspring for the next generation and the remainder is discarded. Genetic diversity is maintained through using a roulette wheel technique. The simulation tool MATLAB will be used to simulate the genetic algorithm. The genetic algorithm will be completed in VLSI using Verilog and the Mentor Graphics tools. The first stage components have been designed and completed using the Mentor Graphics toolset

关键词： Genetic algorithms Telecommunication services Mathematical model Target tracking Graphics Algorithm design and analysis Genetic engineering design engineering systems engineering and theory Cloning

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Plasticity recurrent spiking neural networks for olfactory pattern recognition

Plasticity recurrent spiking neural networks for olfactory p...

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： J.N. Allen H.S. Abdel-Aty-Zohdy R.L. Ewing Microelectronics System Design Laboratory Department of Electrical and System Engineering Oakland University Rochester MI USA Information Directorate Air Force Research Laboratory OH USA

This paper introduces a novel spiking neural network methodology, and applies it to an odorant learning and detection application. Spike-time dependent plasticity can support coding schemes that are based on spatio-temporal spike patterns. Spiking (or pulsed) neural networks (SNNs) are models which explicitly take into account the timing of inputs. The network input and output are usually represented as series of spikes (delta function or more complex shapes). Plasticity SNNs have an advantage of being able to recurrently process information. Spike-time dependent plasticity can enhance signal transmission by selectively strengthening synaptic connections that transmit precisely timed spikes at the expense of those synapses that transmit poorly timed spikes. Complete theory describes the spiking network's digital implementation. Theory is verified using simulation of a biologically plausible odor environment with 1023 odor receptor inputs. Stochastic on-chip learning uses sampling and a correlation filter to learn odors despite noisy environment conditions. Simulation and Verilog chip design are tested on a field programmable gate array. A scalable field programmable gate array implementation with 1024 inputs, 1 output, and expansion capability for unlimited outputs is synthesized into 87,062 gates

关键词： Neural networks Recurrent neural networks Olfactory Pattern recognition Biological system modeling Field programmable gate arrays Timing Shape Stochastic processes Sampling methods

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Exploring the biocomputing frontier

Exploring the biocomputing frontier

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： R.L. Ewing H.S. Abdel-Aty-Zohdy F. Schuermeyer L. Liou J.B. Moncrief M. Rubeiz M. Williamson Air Force Research Laboratory OH USA Microelectronics System Design Laboratory Department of Electrical and System Engineering Oakland University Rochester MI USA Department of Electrical Engineering Wright State University Dayton OH USA

Stop thinking that the universe is best described by Boolean order operations, consider the world of biocomputing. The idea in exploring the multidimensional characteristics of biocomputing systems involves multilevel protein logic interaction with hybrid digital systems (bio/digital/analog systems). In the protein biocomputing world, all models are multilevel and nonlinear exponential in nature. These biocomputing systems are linearized by boundary limited frequency, time response and dimensional ranges. The protein model and its correct development is probably the most difficult aspect for biocomputing issues. Previous protein models were not dealing with 2 and 3 dimensional models, while the current protein models are now faced with high frequency design, due to the emergence of bio-nanodevices. These future biocomputing devices will be chemical sensors, fluidic computer systems, optical switches, nanoactuators, self-repairing polymorphic computing systems, cognitive processors and biorobotics

关键词： Frequency Optical computing Multidimensional systems Logic Digital systems Time factors Protein engineering Chemical sensors Optical switches Nanoscale devices

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B-system: New solution for seamlessly interconnecting track-side and on-board systems over network

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Hitachi Review 2005年第4期54卷 169-173页

作者： Koiwa, Hiroaki Ito, Satoru Matsuo, Masakazu Okura, Yoshinori Ishifuji, Tomoaki Ebata, Tomoichi System Solution Department Transportation System Division Industrial Systems Rolling Stock Electrical Systems Design Department Mito Transportation Systems Product Division Industrial Systems Transportation Control Systems Engineering Department Transportation Information Systems Division Information and Telecommunication Systems Systems Research Department Hitachi Research Laboratory Wireless Radio System Division Central Research Laboratory 4th Research Department Systems Development Laboratory

The fundamental concept of the ubiquitous information society is the ability to obtain needed information whenever and wherever one wants. In the context of enhanced railway passenger services, this means above all providing passengers with access to the network anytime and anywhere whether in railway stations or on-board trains. Equally important considering the greater intelligence of railcars themselves, is the need for more advanced on-board operating systems that are seamlessly connected to track-side systems. As a comprehensive rail system integrator, Hitachi has responded to these needs and at the same time contributed to more convenient and efficient rail systems through the development of a sophisticated broadband network system for trains - dubbed the B-system - that not only significantly increases the capacity of on-board networks but also supports seamless continuous interconnection between on-board and track-side systems.

关键词： Railroad transportation

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Dynamic impedance model of piezoelectrochemical transducer effect for a smart battery

Dynamic impedance model of piezoelectrochemical transducer e...

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： P.S. Teli H.S. Abdel-Aty-Zohdy F. Line Vogel R.L. Ewing Microelectronics System Design Laboratory Department of Electrical and System Engineering Oakland University Rochester MI USA Graphi Tech Inc. Saint Clair Shores MI USA Information Directorate Air Force Research Laboratory OH USA

Intelligent power management for dry cell batteries may be accomplished by external circuitry which is connected to the individual power cells. In comparison, the presented graphite circuit model, along with lead-acid battery technology facilitates the power management of wet cells in sealed packaging. This paper reiterates the piezoelectrochemical transducer (PECT) effect based on the intercalation of graphite with sulfuric acid. It introduces a first attempt at developing a dynamic circuit model which will facilitate for a wide range of smart PECT applications. The paper also addresses the usage of PECT effect device for smart battery management, which operates in sulfuric acid environment. The developed dynamic impedance circuit model of PECT effect device can be used further to understand the changes in resistance and reactance properties of PECT device with the change in the temperature, voltage, current, stages, type of graphite and the concentration of sulfuric acid of electrochemical intercalation of graphite with sulfuric acid

关键词： Impedance Piezoelectric transducers Circuits Battery management systems Energy management Technology management Packaging Environmental management Temperature Voltage

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PHD filter multi-target tracking in 3D sonar

PHD filter multi-target tracking in 3D sonar

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OCEANS - Europe

作者： D.E. Clark J. Bell Y. de Saint-Pern Y. Petillot Ocean Systems Lab Electrical and Computer Engineering Heriot-Watt University Edinburgh UK Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System Xi'an Jiaotong University Xi'an PR China Shenji Kunming Machine Tool Company Limited

The Probability Hypothesis Density (PHD) Filter was developed as a method for tracking a time varying number of targets without data association. The first order statistical moment of the multiple target posterior distribution called the Probability Hypothesis Density which is represented by discrete samples or particles gives the expected locations of the targets. This property is used instead of the full multi-target posterior distribution as it is rcquires significantly less computation and particle tilter implementations have demonstrated lhe potential of the algorithm to be used for real-time tracking applications. In this article, an application of the Particle PHD Filler is demonstrated to track a variable number of objects in threedimensiond sonar images estimating both the number of targets and their locations. The number of targets is estimated at each iteration by computing the mass of lhe particle weights. The locations of the targets are determined by extracting peaks of the PHD which is a distinct task from the computation of the particles. Previous approaches have used the Expectation Maximisation (EM) algorithm to fit a Gaussian mixture model whose time complexity is quadratic in the number of targets which is not ideal for a real-time tracking appiication and so alternative clustering techniques are considered here. A comparison is made between the methods for the accuracy of estimation, robustness and the time taken.

关键词： Filters Target tracking Sonar navigation Probability Particle tracking Underwater tracking Robustness Underwater vehicles Acoustic sensors Distributed computing

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Appointments for 2005-2006 term

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IEEE Transactions on Very Large Scale Integration (VLSI) systems 2005年第7期13卷 773-782页

作者： Ranganathan, Nagarajan Agrawal, Vishwani D. Chakradhar, Srimat T. Chakrabarty, Krishnendu Courtois, Bernard DeMara, Ronald Hu, Xiaobo Sharon Ismail, Yehea I. Jha, Niraj K. John, Lizy Kurian Ker, Ming-Dou Koren, Israel Liu, Bin-Da Marculescu, Diana Marculescu, Radu Narayanan, Vijaykrishnan Nassif, Sani R. Nowick, Steven M. Sapatnekar, Sachin S. Sherlekar, Sunil Sylvester, Dennis Vemuri, Ranga Pham, Michael Department of Computer Science and Engineering University of South Florida Tampa FL 33620 United States Department of Computer Science and Engineering Nanomaterials and Nanomanufacturing Research Center University of South Florida Tampa United States IEEE United States Systems United States Department of Electrical and Computer Engineering Rutgers University New Brunswick NJ United States IETE India ACM NEC Laboratories America Inc. Princeton NJ United States Duke University Durham NC United States ACM SIGDA Sigma Xi United States Laboratory of Techniques of Informatics and Microelectronics for Computer Architectecture ASME IMAPS IEEE Computer Society University of Central Florida Orlando United States Computer Engineering Program SEECS Department of Computer Science and Engineering University of Notre Dame Notre Dame IN United States Northwestern University Evanston IL United States Department of Electrical Engineering Princeton University Princeton NJ United States Association for Computing Machinery Austin United States UT Austin Engineering Foundation United States Department of Electronics Engineering National Chiao-Tung University Taiwan Department of Electrical and Computer Engineering University of Massachusetts Amherst United States Department of Electrical Engineering Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States Electrical and Computer Engineering Faculty Carnegie Mellon University Pittsburgh PA United States Computer Science and Engineering Department Pennsylvania State University University Park United States IBM Austin Research Laboratory Austin TX United States Columbia University New York NY United States Department of Electrical and Computer Engineering University of Minnesota Minneapolis United States Tata Consultancy Services Centre of Excellence for Embedded Systems India Department of Electrical Engineering IIT Bombay India Department of Electrical Engineering Uni

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An artificial immune system strategy for robust chemical spectra classification via distributed heterogeneous sensors

An artificial immune system strategy for robust chemical spe...

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Congress on Evolutionary Computation

作者： M.A. Esslinger G.B. Lamont H.S. Abdel-Aty-Zohdy R.L. Ewing Department of Electrical and Computer Engineering Air Force Institute of Technology Dayton OH USA Microelectronics System Design Laboratory Oakland University Rochester MI Information Directorate Wright-Patterson AFB Air Force Research Laboratory Dayton Ohio USA

The timely detection and classification of biological agents in a hostile environment is critical for increasing protection in critical areas. This paper proposes a strategy for identifying biological agents via distributed sensors with an artificial immune system (AIS). The proposed system is composed of networked sensors and nodes, communicating via wireless or wired connections. Measurements are continually taken via dispersed redundant sensors strategically placed in threat areas. These sensors continually measure and categorize air or liquid samples, alerting surrounding nodes when possible biological agents are detected. Detection is based upon the biological immune system (BIS) model of antigens and antibodies, and alerts are generated when a measured sample is determined to be a valid biological agent (antigen). Biological agent signatures (antibodies) are continually distributed throughout the system to adapt to changes in the environment or to new antigens.

关键词： Chemical sensors Artificial immune systems Robustness Sensor systems Biosensors Chemical and biological sensors Wireless sensor networks Protection Wireless communication Area measurement

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Bio-inspired integrated circuits for signal perception and processing

Bio-inspired integrated circuits for signal perception and p...

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2003 Nanotechnology Conference and Trade Show - Nanotech 2003

作者： Abdel-Aty-Zohdy, Hoda S. Ewing, Robert L. Microelectronics System Design Lab Department of Electrical Engineering Rochester MI 48309 United States Information Directorate Air Force Research Laboratory Wright-Patterson AFB OH 45433 United States

ISBN: (纸本)0972842209

Bio-inspired systems utilizing neural networks (NNs) and genetic algorithms (GAs) are presented for communications, networking information dissemination, and real-time control in signal perception and processing (SPP). VLSI and nano circuits and systems will provide affordable, reproducible, and reliable front-end high performance SPP. Sample applications are presented for integrated intelligent E-Nose systems, and Communication systems which include: i-Self-Organizing feature Map for discovery, ii- Recurrent Dynamic Neural Networks (NNs), with output neurons feedback and feed forward arrays for noisy signals, iii- Reinforcement NNs for applications with only key features, rather than a known model, iv- Spiking NNs that adjust their synapses subject to changes in the environment, and v- Genetic Algorithms for characterization and optimization.

关键词： Integrated circuits

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