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Cellular mixed signal pixel array for real time image processing

Cellular mixed signal pixel array for real time image proces...

引用

Asilomar Conference on Signals, systems & Computers

作者： G. Erten F.M. Salam IC Tech Inc. Okemos MI USA Circuits Systems and Artificial Neural Nets Lab Michigan State University East Lansing MI USA

Contemporary computing platforms fail to deliver the computational density required for many real-time image processing tasks. On the other hand, even the simplest of living systems are able to perceive and interpret their environment effortlessly using a conglomerate of slow and inaccurate neurons in parallel. Motivated by this observation as well as the cellular neural network paradigm, this paper presents an integrated sensor processor architecture that captures the local connectivity patterns of the vertebrate retina in silicon to perform parallel programmable iconic image operations. Results are presented from simulation of this new cellular network paradigm.

关键词： Signal processing Pixel Image processing Equations Cloning Very large scale integration Sensor arrays Integrated circuit modeling Cellular neural networks Land mobile radio cellular systems

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Real time separation of audio signals using digital signal processors

Real time separation of audio signals using digital signal p...

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Midwest Symposium on circuits and systems (MWSCAS)

作者： G. Erten F.M. Salam IC Technology Inc. Okemos MI USA Circuits Systems and Artificial Neural Nets Lab Michigan State University East Lansing MI USA

This work presents a practical real time execution of a family of dynamic blind signal separation algorithms using commercial digital signal processors (DSP). The implementation adopts discrete-time formulations with ... 详细信息

关键词： Signal processing Digital signal processors Delay Source separation Integrated circuit modeling Blind source separation Digital signal processing Computer interfaces Telephony Filters

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Nonlinear projection to submanifolds using neural networks with circuit realization and its application to data reduction

Nonlinear projection to submanifolds using neural networks w...

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IEEE International Symposium on circuits and systems (ISCAS)

作者： F.M.A. Salam G. Erten S. Vedula Hwa-Joon Oh Circuits and Systems and Artificial Neural Networks Laboratories Department of Electrical Engineering Michigan State University East Lansing MI USA IC Tech Inc. Okemos MI USA

The Principal Component Analysis (PCA) approach and its variations compute eigenvalues and eigenvectors and hence planar surfaces. An extension of the PCA approach, which computes nonplanar (folded) surfaces, is a computational tool that computes submanifolds in higher dimensional spaces. The focus of this work is an application of this nonlinear projection approach to nonlinear data reduction/compression of color images and 3-band radar signals. Results of various image processing from both computer simulations of the circuit model and chip experiments are reported. Furthermore, we describe how certain neural networks can be constructed as computational tools for general submanifold charts and parameterization maps of nonlinear dynamical systems. Moreover, the architectural framework is compatible with basic circuit realization using micropower microelectronic components.

关键词： neural networks Principal component analysis circuits Eigenvalues and eigenfunctions Focusing Application software Image coding Color Radar applications Radar imaging

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Low power analog chips for the computation of the maximal principal component

Low power analog chips for the computation of the maximal pr...

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International Joint Conference on neural Networks (IJCNN)

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

Test results of two prototype circuit implementations that compute the maximal principal component are described. The implementations are designed to be compact and operate in the subthreshold regime for low power consumption. The prototypes use direct realization of a nonlinear self-learning circuit models which we have developed.< >

关键词： Analog computers Computer networks Circuit testing Prototypes Power engineering computing Principal component analysis Feedback circuits Transconductance Equations Voltage

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Subthreshold analog circuit for computing the maximal principal component of 3-D data

Subthreshold analog circuit for computing the maximal princi...

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IEEE International Symposium on circuits and systems (ISCAS)

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

We present the analysis, design, and experimental results of a circuit that computes the maximal principal component of three dimensional data. To reduce power consumption, the implemented model uses circuit elements ... 详细信息

关键词： Analog circuits Analog computers Vectors Principal component analysis Equations Computer networks circuits and systems artificial neural networks laboratories Circuit analysis computing

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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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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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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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