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IEEE International Conference on Cognitive Informatics

作者： Zeng-Guang Hou Min Tan M.M. Gupta P.N. Nikiforuk Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China Intelligent Systems Research Laboratory College of Engineering University of Saskatchewan Saskatoon SAS Canada

We present a neural network approach for the real-time optimization and control of interconnected nonlinear systems in the presence of more general constraints, i.e. equality and inequality constraints, and bound-constrained variables. For the interconnected system with bound-constrained variables, we transform it into an equivalent formulation without bound constraints. With the help of auxiliary variables, the inequality constrained problem is reformulated as a problem with only equality constraints. Moreover, an electrocircuit is proposed for implementing the Lagrange neurons in the inequality constrained systems. Simulation studies show that this proposed method is satisfactory for the real-time optimization and control of large-scale systems.

关键词： Real time systems Computer networks Nonlinear systems Neural networks Constraint optimization Nonlinear control systems Control systems Interconnected systems Lagrangian functions Neurons

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Dynamic neural network based training for support vector machines

Dynamic neural network based training for support vector mac...

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： Zeng-Guang Hou M.M. Gupta Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China Intelligent Systems Research Laboratory College of Engineering University of Saskatchewan Saskatoon SAS Canada

Support vector machines are effective tools for pattern classification and nonlinear regression problems. However, efficient training algorithms still need to be investigated. In this paper, we present a dynamic neural network based method for training the support vector machines. The neural computing scheme is designed on the basis of the dual optimization problem for training the support vector machines. The proposed neural network can be implemented by analog circuits, and has the potential to deal with a large number of sample data. We apply the proposed neural network to solve a two-variable XOR problem and a three-variable XOR problem using two different inner-product kernel functions. Simulation studies show that the proposed method is efficient for training support vector machines. Discussions on further researches are given in the paper.

关键词： Neural networks Support vector machines Support vector machine classification Training data Laboratories Intelligent systems Machine intelligence Design optimization Automation Pattern classification

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A hierarchical placement method for standard cell layout based on wire length driven clustering

A hierarchical placement method for standard cell layout bas...

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： H. Kubota S. Wakabayashi T. Koide Department of Artificial Complex Systems Engineering Hiroshima University Higashihiroshima Japan Department of Computer Engineering Faculty of Information Sciences Hiroshima City University Asaminami Hiroshima Japan Research Center for Nanodevices and Systems Hiroshima University Higashihiroshima Japan

This paper presents a new hierarchical placement method for standard cell layout. The proposed method consists of three phases, clustering of cells, hierarchical global cluster placement, and detailed cell placement. First, a set of clusters is constructed considering their internal structures. When cluster placement is determined based on simulated annealing, the wire length between clusters is estimated based on the structural information of each cluster so as to produce a good cluster placement. In the detailed cell placement phase, cells are placed in rows according to the global cluster placement, and cell placement is iteratively improved to get a final cell placement. Experimental results based on benchmark data demonstrate the effectiveness of the proposed method.

关键词： Wire Very large scale integration Circuits Process design Partitioning algorithms systems engineering and theory Simulated annealing Routing Modeling Law

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Abrasive machining process characterization on power consumption when wood is used

Abrasive machining process characterization on power consump...

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IIE Annual Conference and Exhibition 2004

作者： Saloni, Daniel E. F. Lemaster, Richard Jackson, Steven Wood Machining and Tooling Research Program Department of Wood and Paper Science North Carolina State University Raleigh NC 27695-8005 United States Integrated Manufacturing Systems Engineering North Carolina State University Raleigh NC 27695-7915 United States

wood is a unique renewable natural resource. It can be shaped and transformed into many different products, has a long life and a marvelous appearance. Wood processing industries have developed and improved technologies and processes to transform wood to obtain better final product quality and thus increase profits. Abrasive machining is one of the most important of these processes and therefore merits special attention and study. In addition, the United States has recently experienced criticism for its high per capita energy consumption. Various non-profit and governmental organizations are trying to understand and control the energy consumption problem to which the woodworking industry contributes. The woodworking industry, while not the greatest consumer of energy, is considered a larger one. Among the processes used in the wood industry, abrasive machining consumes a substantial quantity of energy. Though woodworking industries and abrasive manufacturers have worked with different abrasive minerals and configurations to obtain the best results during abrasive machining processes, systematic process characterization and optimization are still needed. The objective of this project was to characterize the abrasive machining process to gain a better understanding of the variables that most significantly affect power consumption. The major finding of this research was that power consumption increased approximately linearly with pressure increased.

关键词： Machining

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A summating, exponentially-decaying CMOS synapse for spiking neural systems

A summating, exponentially-decaying CMOS synapse for spiking...

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17th Annual Conference on Neural Information Processing systems, NIPS 2003

作者： Shi, Rock Z. Horiuchi, Timothy Electrical and Computer Engineering Department University of Maryland College Park MD 20742 United States Institute for Systems Research University of Maryland College Park MD 20742 United States Neuroscience and Cognitive Science Program University of Maryland College Park MD 20742 United States

ISBN: (纸本)0262201526

Synapses are a critical element of biologically-realistic, spike-based neural computation, serving the role of communication, computation, and modification. Many different circuit implementations of synapse function exist with different computational goals in mind. In this paper we describe a new CMOS synapse design that separately controls quiescent leak current, synaptic gain, and time-constant of decay. This circuit implements part of a commonly-used kinetic model of synaptic conductance. We show a theoretical analysis and experimental data for prototypes fabricated in a commercially-available 1.5μm CMOS process.

关键词： CMOS integrated circuits

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Sensorless control of induction motor with adaptive speed-flux observer

Sensorless control of induction motor with adaptive speed-fl...

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IEEE Conference on Decision and Control

作者： M. Montanari A. Tilli S. Peresada Center for Research on Complex Automated Systems G. Evangelisti (CASY) Department of Electronics Computer Science and Systems (DEIS) University of Bologna Bologna Italy Department of Electrical Engineering Kiev Polytechnic Institute National Technical University Kiev Ukraine

A novel sensorless controller for induction motor is presented. Indirect field oriented control approach and Lyapunov-adaptive design are exploited for the derivation of the controller and the speed-flux observer constituting the proposed solution. No direct integration of the neutrally stable stator flux dynamics is adopted. Persistency of excitation conditions with clear practical interpretation is derived to guarantee local exponential stability with a defined region of attraction for the proposed approach. Simulation results are provided.

关键词： Sensorless control Induction motors programmable control Adaptive control Stators Current measurement Mechanical sensors Sliding mode control Stability Low pass filters

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Fast sum of absolute differences visual landmark detector

Fast sum of absolute differences visual landmark detector

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IEEE International Conference on Robotics and Automation (ICRA)

作者： C. Watman D. Austin N. Barnes G. Overett S. Thompson Robotic Systems Laboratory Department of Systems Engineering RSISE Australian National University Canberra ACT Australia Autonomous Systems and Sensing Technologies Program NICTA Canberra ACT Australia Digital Human Research Center National Institute for Advanced Industrial Science and Technology Koto Japan

This paper presents various optimisation that can be applied to the sum of absolute differences (SAD) correlation algorithm for automated landmark detection. This has applications in mobile robotic navigation and mapping. We show how some assumptions about the environment and the generic form of strong landmarks selected by the SAD correlation algorithm have led to the development of an algorithm to enable near real tune selection of strong landmarks from visual information. The landmarks that have been selected from a series of frames using our optimisation are shown to be stable through the image sequence, demonstration the scale invariance of the landmarks that are selected by the SAD correlation algorithm.

关键词： Navigation Robot sensing systems Mobile robots Detectors Service robots Robot vision systems Indoor environments Feature extraction Pixel Laboratories

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Intelligent control for the vision-based indoor navigation of an A-life mobile robot

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Artificial Life and Robotics 2004年第1期8卷 29-33页

作者： Wang, Jiwu Kimura, Hidenori Sugisaka, Masanori Department of Electrical and Electronics Engineering Oita University Oita Japan Institute of Physical and Chemical Research (RIKEN) Bio-Mimetric Control Research Center Nagoya Japan Complex Systems Department of Complexity Science and Engineering Graduate School of Frontier Science University of Tokyo Tokyo Japan

Realizing steady and reliable navigation is a prerequisite for a mobile robot, but this facility is often weakened by an unavoidable slip or some irreparable drift errors of sensors in long-distance navigation. Although perceptual landmarks were solutions to such problems, it is impossible not to miss landmarks occasionally at some specific spots when the robot moves at different speeds, especially at higher speeds. If the landmarks are put at random intervals, or if the illumination conditions are not good, the landmarks will be easier to miss. In order to detect and extract artificial landmarks robustly under multiple illumination conditions, some low-level but robust image processing techniques were implemented. The moving speed and self-location were controlled by the visual servo control method. In cases where a robot suddenly misses some specific landmarks when it is moving, it will find them again in a short time based on its intelligence and the inertia of the previous search motion. These methods were verified by the reliable vision-based indoor navigation of an A-life mobile robot.

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Phase-field modeling of binary alloy solidification with coupled heat and solute diffusion

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Physical Review E 2004年第5期69卷 051607-051607页

作者： J. C. Ramirez C. Beckermann A. Karma H.-J. Diepers Department of Mechanical and Industrial Engineering The University of Iowa Iowa City Iowa 52242 USA Department of Physics and Center for Interdisciplinary Research on Complex Systems Northeastern University Boston Massachusetts 02115 USA ACCESS e.V. D-52056 Aachen Germany

A phase-field model is developed for simulating quantitatively microstructural pattern formation in solidification of dilute binary alloys with coupled heat and solute diffusion. The model reduces to the sharp-interface equations in a computationally tractable thin-interface limit where (i) the width of the diffuse interface is about one order of magnitude smaller than the radius of curvature of the interface but much larger than the real microscopic width of a solid-liquid interface, and (ii) kinetic effects are negligible. A recently derived antitrapping current [A. Karma, Phys. Rev. Lett. 87, 115701 (2001)] is used in the solute conservation equation to recover precisely local equilibrium at the interface and to eliminate interface stretching and surface diffusion effects that arise when the solutal diffusivities are unequal in the solid and liquid. Model results are first compared to analytical solutions for one-dimensional steady-state solidification. Two-dimensional thermosolutal dendritic growth simulations with vanishing solutal diffusivity in the solid show that both the microstructural evolution and the solute profile in the solid are accurately modeled by the present approach. Results are then presented that illustrate the utility of the model for simulating dendritic solidification for the large ratios of the liquid thermal to solutal diffusivities (Lewis numbers) typical of alloys.

关键词： .dendritic solutal Phase-field coupled heat Diffuse interface phase field model solute diffusion sharp-interface thin-interface

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A low-power CMOS neural amplifier with amplitude measurements for spike sorting

A low-power CMOS neural amplifier with amplitude measurement...

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2004 IEEE International Symposium on Circuits and systems - Proceedings

作者： Horiuchi, T. Swindell, T. Sander, D. Abshire, P. Electrical Engineering Department University of Maryland College Park MD 20742 United States Institute for Systems Research University of Maryland College Park MD 20742 United States Neurosci./Cognitive Science Program University of Maryland College Park MD 20742 United States Electrical Engineering Department Pennsylvania State University State College PA 16801 United States

Integrated, low-power, low-noise CMOS neural amplifiers have recently grown in importance as large microelectrode arrays have begun to be practical. With an eye to a future where thousands of signals must be transmitted over a limited bandwidth link or be processed in situ, we are developing low-power neural amplifiers with integrated pre-filtering and measurements of the spike signal to facilitate spike-sorting and data reduction prior to transmission to a data-acquisition system. We have fabricated a prototype circuit in a commercially-available 1.5μm, 2-metal, 2-poly CMOS process that occupies approximately 91,000 square μm. We report circuit characteristics for a 1.5V power supply, suitable for single cell battery operation. In one specific configuration, the circuit bandpass filters the incoming signal from 22Hz to 6.7kHz while providing a gain of 42.5dB. With an amplifier power consumption of 0.8 μW, the rms input-referred noise is 20.6μV.

关键词： Biomedical engineering

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