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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： B. Mirzai H.C. Reddy G.S. Moschytz Signal and Information Processing Laboratory Swiss Federal Institute of Technology Zurich Switzerland Department of Electrical and Computer Engineering University of California Irvine CA USA Department of Electrical Engineering California State University Long Beach CA USA

The delta operator approach to continuous-time cellular neural networks (CT-CNNs) is investigated in terms of a robust realization. It is shown that earlier results concerning the robustness of CT-CNNs can be obtained as a limiting case of this approach, while at the same time, this allows us to formulate robustness considerations for discrete-time CNNs.

关键词： Robustness Cellular neural networks Sampling methods signal processing Limiting Nonlinear equations Information processing Laboratories computer networks image processing

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Three-dimensional analytical and numerical solutions for acousto-optic interaction

Three-dimensional analytical and numerical solutions for aco...

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Southeastern Symposium on System Theory

作者： D.B. Dunn M. McNeill Jiangang Xia Ting-Chung Poon P.P. Banerjee Optical Image Processing Laboratory The Bradley Department of Electrical Engineering Virginia Polytechnic Institute and State University VA USA Department of Elec. Engineering Bucknell University USA York University Canada Center for Applied Optics Department of Electrical and Computer Engineering University of Alabama Huntsville Huntsville AL USA

The authors present an analytical solution to the strong acousto-optic interaction problem in three dimensions. They then compare the analytical results to a split-step numerical algorithm. The algorithm is based on t... 详细信息

关键词： Optical propagation Acoustic beams Transfer functions Diffraction Acoustic propagation USA Councils Gratings image analysis image processing Laboratories

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A new method of Wiener filtering and its application to interference mitigation for communications

A new method of Wiener filtering and its application to inte...

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MILCOM, Military Communications Conference

作者： J.S. Goldstein I.S. Reed Space Communications Branch U. S. AirForce Research Laboratory Rome NY USA Statistical Signal and Image Processing Lab Department of Electrical Engineering (EEB 528) University of Southern California Los Angeles CA USA

A new multistage Wiener filter is introduced which utilizes a decomposition based on orthogonal projections. A reduced-rank Wiener filter is developed based on this new structure which is not basis oriented, but evolves a basis which is a function of the multistage decomposition. The performance of this new Wiener filtering structure is evaluated using a comparative computer analysis model. It is demonstrated that the low-complexity multistage reduced-rank Wiener filter is capable of outperforming the more complex eigendecomposition-based methods.

关键词： Wiener filter Interference Matrix decomposition signal processing Nonlinear filters Covariance matrix USA Councils Random processes Vectors Laboratories

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Performance analysis of reduced-rank STAP

Performance analysis of reduced-rank STAP

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IEEE National Conference on Radar

作者： A.M. Haimovich C. Peckham T. Ayoub J.S. Goldstein I.S. Reed Electrical and Computer Engineering. Department New Jersey Institute of Technology University Heights Newark NJ USA Space Communications Branch USAF Rome Laboratory Rome NY USA Statistical Signal & Image Proc. Laboratory Department of Electrical Engineering University of Southern California Los Angeles CA USA

The space-time radar problem is well suited to the application of techniques that take advantage of the low-rank property of the space-time covariance matrix. In particular, it was shown that when the space-time covariance matrix is estimated from a dataset with limited support, reduced-rank methods outperform full-rank space-time adaptive processing (STAP). We study the application of several reduced-rank methods to the STAP problem and demonstrate their utility by simulations in terms of the output signal-to-noise ratio and detection probability. It is shown that reduced-rank processing has two opposite effects on the performance: increased statistical stability which tends to improve performance, and introduction of a bias which lowers the signal-to-noise ratio. Several reduced-rank methods are analyzed and compared for both cases of known and unknown covariance matrix. While the best performance is obtained using transforms based on the eigendecomposition (data dependent), the loss incurred by the application of fixed transforms (such as the discrete cosine transform) is relatively small. The main advantage of fixed transforms is the availability of efficient computational procedures for their implementation. These findings suggest that reduced-rank methods could facilitate the development of practical, real-time STAP technology.

关键词： Performance analysis Covariance matrix Discrete transforms signal to noise ratio Radar applications Spaceborne radar Probability Stability Performance loss Discrete cosine transforms

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Real-time image processing using cascaded acousto-optic modulators

Real-time image processing using cascaded acousto-optic modu...

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IEEE Southeastcon

作者： D.B. Dunn Jiangang Xia Ting-Chung Poon P.P. Banerjee Optical Image Processing Laboratory The Bradley Department of Electrical Engineering Virginia Polytechnic Institute and State University VA USA Virginia Polytechnic Institute and State University Blacksburg VA US Center for Applied Optics Department of Electrical and Computer Engineering University of Alabama Huntsville Huntsville AL USA

We present a novel and simple cascaded acousto-optic image processing system to perform image processing. The system consists of two imaging lenses and two acousto-optic modulators that are placed in series. Real time image processing is achieved by Bragg diffraction. computer simulation is given and compared to an optical image processing system which uses a single acousto-optic modulator.

关键词： image processing Optical imaging Lenses Optical modulation Fourier transforms Transfer functions Equations Laboratories computer simulation Acoustic beams

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Performance enhancement in acousto-optic image processing

Performance enhancement in acousto-optic image processing

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IEEE Southeastcon

作者： P.P. Banejee D. Cao T.-C. Poon Dept. of Electr. & Comput. Eng. Alabama Univ. Huntsville AL USA Department of Electrical and Computer Engineering University of Alabama Huntsville Huntsville AL USA Optical Image Processing Laboratory The Bradley Department of Electrical Engineering Virginia Polytechnic Institute and State University Blacksburg VA USA

From the transfer functions of an acousto-optic (AO) cell, it is found that some basic image processing can be accomplished by using AO cells. Instead of frequency-plane filters, the AO cells are placed directly behind the object. The one dimensional edge enhancement results using one AO cell can be improved by using two acousto-optic cells which are put in tandem and with contra-propagating sound. The dominant second derivative operation obtained from the transfer function of the undiffracted order works like a one-dimensional Laplacian operator which enables improved edge enhancement.

关键词： image processing Numerical simulation Digital images image edge detection Propagation delay Laplace equations

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A simulator construction methodology for the Shiva multiprocessor system

A simulator construction methodology for the Shiva multiproc...

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IEEE International Conference on Algorithms and Architectures for Parallel processing (ICAP)

作者： S. Slomka K.F. Sterzl V. Lakshmi Narasimhan The Speech Research Laboratory Signal Processing Research Center Queensland University of Technology Brisbane QLD Australia The PA SE Research Laboratory Department of Electrical and Computer Engineering University of Queensland Saint Lucia QLD Australia Information Management Group ITD DSTO Salisbury SA Australia

This paper describes a simulator for the Shiva multiprocessor system and the simulator construction methodology (SCM) used in its creation. The SCM, based on the active functional unit (AFU) construct, is a modern SCM which is flexible, accurate, fast, easy to use, capable of dynamic reconfigurability at run-time, and most of all simple and capable of quick simulator construction. The AFU SCM is capable of all these things through the use of object-oriented software techniques. The Shiva simulator constructed using the AFU SCM is program-driven and capable of micro and macro architectural simulation.

关键词： Multiprocessing systems Computational modeling Object oriented modeling signal generators Laboratories computer simulation Discrete event simulation Speech processing signal processing Information management

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A new time series classification approach

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signal processing 1996年第2期54卷 191-199页

作者： Plataniotis, KN Androutsos, D Venetsanopoulos, AN Lainiotis, DG Department of Electrical and Computer Engineering Digital Signal & Image Processing Laboratory University of Toronto 10 King's College Rd. Toronto Ontario M5S 3G4 Canada Intelligent Systems Technology 3207 S. Hwy. A1A Melbourne Beach FL-32951 USA

A new, robust and computationally attractive approach to the problem of time series classification is discussed in this paper. Both the Bayesian as well as a new adaptive classification scheme for source selection are... 详细信息

关键词： time series classification neural networks logistic function

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3D segmentation and labeling using self-organizing Kohonen network for volumetric measurements on brain CT imaging to quantify TBI recovery

3D segmentation and labeling using self-organizing Kohonen n...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： M.N. Ahmed A.A. Farag Computer Vision and Image Processing Laboratory Department of Electrical Engineering University of Louisville Louisville KY USA

In this paper, we present a new system to segment and label CT brain slices using a self-organizing Kohonen network. Our aim is to extract reliable and robust measures from CT images of Traumatic Brain Injury (TBI) patients that can accurately describe the morphological changes in the brain as recovery progresses. Segmentation is performed by assigning a feature pattern to each voxel, consisting of a scaled family of differential geometrical invariant features. The invariant feature pattern is input to Kohonen network for an unsupervised classification of the voxels into regions.

关键词： Labeling Volume measurement image segmentation Computed tomography Layout Electric variables measurement engineering in Medicine and Biology Society Brain injuries Data mining Filters

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Neural network classification of spatio-temporal EEG readiness potentials

Neural network classification of spatio-temporal EEG readine...

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Southern Biomedical engineering Conference

作者： A.B. Barreto A.M. Taberner L.M. Vicente Digital Signal Processing Laboratory Electrical & Computer Engineering Department Florida International University Miami FL USA

The detection of spatio-temporal scalp EEG patterns associated with voluntary motion preparation towards the development of a brain-computer interface (BCI) is explored. The rationale for the use of a spatio-temporal approach to this detection problem is explained. The need for a temporal or dynamic classifier is confirmed by demonstration of the lack of robustness in static neural network classifiers with respect to time alignment of the patterns under analysis. The results from dynamic classifiers, such as the Time Delay Neural Network (TDNN) and the Gamma Neural Network are presented in terms of their Receiver Operating Characteristic (ROC) Curves.

关键词： Neural networks Electroencephalography Rhythm Biological neural networks Motion detection Eyes Digital signal processing Brain computer interfaces computer interfaces Scalp

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