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Journal of Vacuum Science & Technology B: microelectronics and Nanometer Structures Processing, Measurement, and Phenomena 1994年第1期12卷 219-229页

作者： J. Y. Tsai C. Canovai C. M. Osburn Q. F. Wang J. Rose A. Cowen M. S. Denker Department of Electrical and Computer Engineering North Carolina State University Raleigh North Carolina 27695‐7911 Department of Electrical and Computer Engineering North Carolina State University Raleigh North Carolina MCNC Center for Microlectronics Systems Technologies Research Triangle Park North Carolina 27709‐2889 MCNC Center for Microelectronics Systems Technologies Research Triangle Park North Carolina 27709‐2889

An optimized secondary ion mass spectrometry (SIMS) technique was used to characterize the solid source diffusion of dopants, i.e., arsenic and boron, from agglomerating cobalt disilicide sources. It was found that interface roughness plays a dominant role in determining the dopant profiles observed by SIMS. Double convolution of a step function with an exponential function, which represents the SIMS cascade mixing, and then again with a Gaussian function, which represents the silicide interface roughening, were performed to fit the SIMS silicon signal in the transition region of the silicide/silicon interface. Experimental profiles were then deconvoluted with the same functions to derive the ‘‘true’’ dopant diffusion. This convolution methodology eliminates the broadening factors provided by the measuring instrument and by the sample itself, and therefore results in a more physically meaningful diffusion profile. The broadening of SIMS silicon signal also provides a very precise characterization of the thermal stability of the thin polycrystalline silicide film. An analytical model was established to relate the SIMS silicon broadening and the sheet resistance of the agglomerated silicide film. This model predicts that while the amplitude of the root‐mean‐square roughening goes as the square root of time, the increase in sheet resistance varies linearly with time, provided that the amplitude of roughening is considerably smaller than the thickness of the silicide film.

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ASYNCHRONOUS TRANSFER MODE (ATM) OPERATION VIA SATELLITE - ISSUES, CHALLENGES AND RESOLUTIONS

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INTERNATIONAL JOURNAL OF SATELLITE COMMUNICATIONS 1994年第3期12卷 211-222页

作者： CHITRE, DM GOKHALE, DS HENDERSON, T LUNSFORD, JL MATHEWS, N COMSAT Laboratories 22300 Comsat Drive Clarksburg MD 20871 USA. Received his B.Sc. from the University of Bombay India an M.A. in mathematics from the University of Cambridge U.K. and a Ph.D. in physics from the University of Maryland. He is currently an Associate Executive Director of the Network Technology Division at COMSAT Laboratories. He has been involved in research and development activities in ISDN VSAT networks data communications and network systems and architectures. Prior to his current positions Dr. Chitre was a Principal Scientist in the Network Technology Division at COMSAT Laboratories. Dr. Chitre joined COMSAT Laboratories in 1980. He has made major contributions to the analysis and architecture of data communication ISDN and BISDN via satellite. Dr. Chitre directs and participates in the international and national standards activities in ISDN BISDN and data communication as they apply to satellite communication. He was Chairman of the Working Group on Protocols and Network Timing Function of the CCIR/CCITT Joint Ad Hoc Group on ISDN-Satellite Matters during 1990–1992. Currently he is the Chairman of the Working Group on New Technologies in the ITU Intersector Coordinating Group (ICG) on Satellite Matters. Dr. Chitre was a programme manager during 1990 and 1991 on a contract from INTELSAT on systems studies on satellite communications systems architectures for ISDN and broadband ISDN systems. Currently he is the technical manager of the DoD Contract on ATM via satellite demonstration and the programme manager for the INTELSAT contract on analysis and top-level specification of INTELSAT ISDN subnetworks and SDH compatible transport network. Department manager for ISDN/Data Communications in the Network Technology Division of COMSAT Laboratories. His responsibilities include managing the implementation of next generation telecommunication systems for fixed and mobile satellite systems. Current projects include the development of a high data rate gateway switch that provides for the

Key issues regarding the operation of the broadband integrated services digital network (BISDN) via satellite are presented herein. The specific issues, challenges, and their resolutions are detailed. In particular, the impact of error characteristics and propagation delay on the operation of BISDN via satellite is discussed. Solutions are presented for removing adverse effects and providing high-quality service to users of BISDN via satellite.

关键词： ATM BISDN

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An analytical learning algorithm for the dendro-dendritic artificial neural network via linear programming

An analytical learning algorithm for the dendro-dendritic ar...

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IEEE International Conference on Neural Networks, ICNN 1993

作者： Ling, Bo Salam, Fathi M.A. Circuits and Systems Artificial Neural Nets Laboratories Department of Electrical Engineering Michigan State University East LansingMI48824 United States

ISBN: (纸本)0780309995

We present an analytical learning algorithm to find the weight matrix of the dendro-dendritic neural network. This learning algorithm utilizes linear programming to find all (necessarily) non-negative and small weights. A sufficient stability criterion is given which guarantees all stored patterns to be asymptotically stable. © 1993 IEEE.

关键词： Linear programming

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Parameter determination for an implementable feedback neural network

Parameter determination for an implementable feedback neural...

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IEEE International Symposium on circuits and systems (ISCAS)

作者： B. Ling F.M.A. Salam Circuits and Systems & Artificial Neural Nets Laboratories Department of Electrical Engineering Michigan State University East Lansing MI USA Circuits and Systems & Artificial Neural Nets Laboratories Department of Electrical Engineering Michigan State University East Lansing MI USA

The authors describe a method which ensures a designed neural network to be implementable as an electronic circuit. The approach involves two steps: (1) adjust the slope of the sigmoidal function of each neuron based on a given criterion; (2) find the weight matrix by an analytical learning algorithm. It is shown that the slope of the sigmoidal function around the origin plays an important role in the implementable neural network design. Based on the approach, the resistance in the neural circuit can be made very large, which reduces the network power dissipation.< >

关键词： Neurofeedback Neural networks Power dissipation Neurons CMOS technology Circuit synthesis circuits and systems Laboratories Electronic circuits Very large scale integration

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An adaptive network for blind separation of independent signals

An adaptive network for blind separation of independent sign...

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IEEE International Symposium on circuits and systems (ISCAS)

作者： F.M.A. Salam Systems and Circuits & Artificial Neural Nets Laboratories Department of Electrical Engineering Michigan State University East Lansing MI USA

The problem of separating two or several independent signals (or independent speakers) from an array of sensors within the framework of adaptive systems is formulated. The delayed signals are modeled as a dynamic state model. The crucial aspect of this formulation is to quantify the property of independence of signals in terms of an explicit function to be optimized. Then, the derived adaptive dynamics will work to minimize (or maximize) the explicit function. The convergence of this newly derived adaptive scheme is shown. As the dynamics converge, the network will succeed in identifying the mixing and the delays in the original signals, and will reproduce the original independent signals.< >

关键词： Adaptive systems Sensor arrays Delay Convergence Signal processing Power generation Nonlinear dynamical systems Symmetric matrices circuits Artificial neural networks

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Data-driven subthreshold analog circuit that computes principal components

Data-driven subthreshold analog circuit that computes princi...

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Midwest Symposium on circuits and systems (MWSCAS)

作者： F.M.A. Salam S.S. Vedula Circuits and Systems and Artificial Neural Networks Laboratories Department of Electrical Engineering Michigan State University East Lansing MI USA

We present a model for the computation of principal components that is tailored for circuit realization. The model uses MOS elements and differential pairs which operate in the subthreshold regime of MOS operation. Co... 详细信息

关键词： Analog circuits Analog computers Equations Vectors Symmetric matrices Eigenvalues and eigenfunctions Power system modeling Computer networks Remuneration circuits and systems

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Subthreshold analog feature matching circuits with large output voltages

Subthreshold analog feature matching circuits with large out...

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Midwest Symposium on circuits and systems (MWSCAS)

作者： B. Ling S.S. Vedula F.M.A. Salam Circuits and Systems and Artificial Neural Networks Laboratories Department of Electrical Engineering Michigan State University East Lansing MI USA

We present (subthreshold) analog bump circuits with a view towards obtaining large output voltage swings. These large swings can be useful in transferring voltage information to the outside world or to a (digital) computer. We also use some of these circuits to compare the similarity of patches in two images as part of the solution to stereo vision. In this case, considering two n/spl times/n patches, the circuit consists of n/sup 2/ building blocks. Each block operates in the subthreshold region with analog input voltages and analog output currents/voltages.< >

关键词： Stereo vision Circuit simulation Pixel Mirrors Shape Threshold voltage circuits and systems Artificial neural networks Laboratories Windows

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state Feedback Stabilization of Nonlinear systems via the Neural Network Approach

State Feedback Stabilization of Nonlinear Systems via the Ne...

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American Control Conference (ACC)

作者： Bo Ling Fathi M.A. Salam Circuits and Systems & Artificial Neural Nets Laboratory Department of Electrical Engineering Michigan State University East Lansing MI USA

We consider the state feedback stabilization of autonomous nonlinear systems described by dx/dt = Ax + Bu - f(x), where f(x) is a memoryless nonlinearity and does not necessarily satisfy the sector conditions. Classical results can not be used to infer stability of the closed loop system. By using neural network techniques, however, we find a state feedback gain matrix that ensures the asymptotic stabilit for any specified equilibrium.

关键词： state feedback Nonlinear systems Neural networks Hopfield neural networks Artificial neural networks Asymptotic stability circuits and systems Laboratories Control theory Bifurcation

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Persistence of equilibria under weight variation of feedback continuous-time neural network

Persistence of equilibria under weight variation of feedback...

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IEEE International Symposium on circuits and systems (ISCAS)

作者： B. Ling F.M.A. Salam Circuits and Systems & Artificial Neural Nets Laboratories Department of Electrical Engineering Michigan State University East Lansing MI USA

For binary patterns, the authors consider the variation of equilibria of the Hopfield-type feedback continuous-time neural network due to perturbations. They show that the equilibria of the feedback continuous-time neural network and its perturbed network are very close as long as the variation of weights is relatively small. The variation of the equilibria can be estimated given the upper bound of the variation of weights.< >

关键词： Neurofeedback Neural networks Artificial neural networks Hopfield neural networks Upper bound Hardware Bifurcation Stability Feedforward neural networks circuits

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A modular analog chip for feed-forward networks with on-chip learning

A modular analog chip for feed-forward networks with on-chip...

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Midwest Symposium on circuits and systems (MWSCAS)

作者： Hwa-Joon Oh F.M.A. Salam Circuits and systems and Artificial neural networks Laboratory Department of Electrical Engineering Michigan State University East Lansing MI USA Michigan State University East Lansing MI US Dept. of Electr. Eng. Michigan State Univ. East Lansing MI USA

A feedforward artificial neural network (ANN) with learning capability in modular design is presented using CMOS circuits. We employ a modified error backpropagation continuous-time learning rule. A (nonlinear) analog Gilbert multiplier is used as a synapse and a wide-range transconductance amplifier is used as soma. For learning circuits, the, same multiplier is used for updating the weights. Test results demonstrate the successful operation of the chip. Finally, a modular chip design for a large scale implementation of feedforward ANN with learning is described.< >

关键词： Feedforward systems Network-on-a-chip Artificial neural networks Equations Large-scale systems Neurons circuits and systems Laboratories Electronic mail Circuit testing

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