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IEEE International Conference on Systems engineering

作者： Mitra Yu Signal and Image Processing Laboratory Department of Electrical & Computer Engineering University of California Santa Barbara CA USA

A general approach to the transform-magnitude-shaping-based image enhancement method is advanced. In the method, the magnitude of the input image transform is modified using a nonlinear mapping expressible as a power series, while its phase is kept invariant. The inverse transform of the modified image transform results in a sharpening or smoothing depending on the choice of the power series coefficients. Further improvement in the overall enhancement is achieved by a two-channel processing scheme which is implemented by applying different transform amplitude shaping methods to the low-frequency and high-frequency components. Examples the proposed enhancement method are included.< >

关键词： Filtering image processing Transforms

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ONE-BIT SPECTRAL-CORRELATION ALGORITHMS

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IEEE TRANSACTIONS ON signal processing 1993年第1期41卷 423-427页

作者： GARDNER, WA ROBERTS, RS Signal Processing Group Department of Electrical and Computer Engineering University of California Davis CA USA Los Alamos National Laboratory Los Alamos NM USA Signal Processing Group. Department of Electrical and Computer Engineering University of California Davis CA USA

A technique that greatly simplifies the computational complexity of digital cyclic spectral analysis algorithms is presented. The technique, which is based on Bussgang's theorem, replaces complex multiplications in spectral correlation operations with simple sign-change and data-multiplexing operations. Moreover, the technique is applicable to both time- and frequency-averaging algorithms. A simulation study that compares the computed results obtained using the new technique with results from standard time- and frequency-averaging algorithms shows that the new technique is very promising, particularly for frequency-averaging algorithms.

关键词： signal processing algorithms Frequency estimation Spectral analysis signal analysis Instruments signal processing Bandwidth Aging Phase measurement Laboratories

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Reduction of coding artifacts in transform image coding

Reduction of coding artifacts in transform image coding

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1993 IEEE International Conference on Acoustics, Speech, and signal processing

作者： R.L. Stevenson Laboratory for Image and Signal Processing Department of Electrical Engineering University of Notre Dame Notre Dame IN USA

The problem of image decompression is cast as an ill-posed inverse problem, and a stochastic regularization technique is used to form a well-posed reconstruction algorithm. A statistical model for the image which incorporates the convex Huber minimax function is proposed. The use of the Huber minimax function rho T(.) helps to maintain the discontinuities from the original image which produces high-resolution edge boundaries. Since rho T(.) is convex, the resulting multidimensional minimization problem is a constrained convex optimization problem. The maximum a posteriori (MAP) estimation technique that is proposed results in the constrained optimization of a convex functional. The proposed image decompression algorithm produces reconstructed images which greatly reduced the noticeable artifacts which exist using standard techniques.< >

关键词： image coding image reconstruction Degradation image storage image representation signal processing algorithms Laboratories signal processing Stochastic processes Constraint optimization

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Application of QR decomposition-based least squares technique to improve air traffic control radar

Application of QR decomposition-based least squares techniqu...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： T. Ogunfunmi Nam Ling Signal and Image Processing Laboratory (SIPL) Department of Electrical Engineering Santa Clara University Santa Clara CA USA Computer Systems and Parallel Processing Research Laboratory (CSPPRL) Department of Computer Engineering Santa Clara University Santa Clara CA USA

For real-time radar processing, it is very desirable to have an algorithm that does not assume restricted statistics of the input data and can be implemented for high-speed processing (without a high cost) to meet real-time requirements. We therefore apply the QR decomposition-based least-squares method for linear prediction to the problem of computing the reflection coefficients of a lattice predictor, instead of using the conventional Burg algorithm. We also propose a modified one-dimensional ring architecture for implementing the QR method of least-squares. The particular application considered in this case is that of surveillance radar systems for air traffic control.< >

关键词： Least squares methods Air traffic control Radar applications signal processing algorithms Radar signal processing Statistics Systolic arrays Radar imaging signal processing Surveillance

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Root-loci for periodic linear systems 25

Root-loci for periodic linear systems

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25th Southeastern Symposium on System Theory, SSST 1993

作者： Zhu, J. Vemula, S.K. Louisiana State Univ. Electrical and Computer Engineering Department Baton RougeLA70803 United States Louisiana State Univ. Remote Sensing Aind Image Processing Laboratory Baton RougeLA70803 United States

ISBN: (纸本)0818635606

According to the Floquet theory, an nth-order linear periodic (LP) system of the form yn+αn(t) y/sup n-1/+...+α2(t)dy(t)/dt+α1(t)y=0 can be transformed into an equivalent linear time-invariant (LTI) system whose characteristic roots, known as Floquet characteristic exponents (FCEs), determine the stability of the LP system. A technique for obtaining an approximation of the characteristic equation for the FCEs is developed. Parametric loci of the FCE, similar to the root locus plot for a LTI system, are then developed for the LP system. The technique is exemplified by 2nd-order LP systems. The FCE loci are useful in the stability analysis and control design for LP systems. © 1993 IEEE.

关键词： Root loci

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A robust method for wideband signal separation

A robust method for wideband signal separation

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： V.C. Soon L. Tong Y.F. Huang R. Liu Laboratory for Image and Signal Analysis (LISA) Department of Electrical Engineering University of Notre Dame Notre Dame IN USA Department of Electrical and Computer Engineering West Virginia University Morgantown WV USA

A novel approach to solving the problem of signal separation under model uncertainties and unknown source signal characteristics is proposed. The approach features the incorporation of blind identification with clustering techniques. The approach is capable of estimating source locations and source signals under various uncertain conditions including unknown sensor gains, unknown combinations of near-field and far-field sources, unknown combinations of wideband and narrowband sources, unknown source spectral characteristics (their spectra may be overlapping or non-overlapping), and unknown number of signals.< >

关键词： Robustness Wideband Source separation Sensor arrays Sensor phenomena and characterization Uncertainty Direction of arrival estimation Narrowband Phased arrays Speech enhancement

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A New Method for Evaluating Floquet Characteristic Exponents of Periodic Linear Systems

A New Method for Evaluating Floquet Characteristic Exponents...

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American Control Conference (ACC)

作者： J. Zhu S. K. Vemula Electrical and Computer Engineering Department Remote Sensing and Image Processing Laboratory Louisiana State University Baton Rouge LA USA Electrical and Computer Engineering Department Louisiana State University Baton Rouge LA USA

It is well-known that the stability of linear periodic (LP) systems can be assessed using Floquet Characteristic Exponents (FCE). In this paper, a new method is presented for evaluating FCE for nth-order scalar periodic linear systems based on a recently developed unified eigenvalue theory for linear time-varying (LTV) Systems [1]. The new theory allows FCEs to be evaluated from the DC term of the Fourier series of periodic PD-eigen-values of a LP system. Comparing to the well-known Monodromy Matrix (MM) method and Infinite Dimensional Determinant (IDD) method for evaluating FCE 1 the solutions obtained by the new method have rapid local convergence. This new method also allow stability boundaries in the parameter space of a LP system to be evaluated and plotted directly. The new results shed some light OL the general stability assessment problem for vector periodic linear systems and aperiodic LTV systems. Further studies along this direction are also discussed in this paper.

关键词： Linear systems Eigenvalues and eigenfunctions Vectors Fourier series Frequency Equations Stability analysis Remote sensing image processing Laboratories

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Local estimation of Gaussian-based edge enhancement filters using Fourier analysis

Local estimation of Gaussian-based edge enhancement filters ...

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1993 IEEE International Conference on Acoustics, Speech, and signal processing

作者： B. Wang D.M. Rose A.A. Farag E.J. Delp Engineering Mathematics & Computer Science Department Speed Scientific School University of Louisville Louisville KY USA Computer Vision & Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

An empirical measure for the selection of the edge-enhancement Gaussian filter is developed. The Gaussian filter is specified by its standard deviation sigma ; the filter's spatial support is a function of sigma . An estimation procedure for sigma using Fourier analysis is described. The measure is easy to implement and is based totally on the image at hand. Experimental results suggest that this measure can be used as an aid in deciding the Gaussian filter's spatial support, which is needed to enhance the edges. Other equivalent bandwidth definitions can be used to obtain a measure of the frequency spread in the smoothed image (e.g., the mean-square bandwidth).< >

关键词： Gaussian processes Low pass filters Shape Filtering Frequency Mathematics computer science computer vision image processing image segmentation

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Helicopter gearbox fault detection and diagnosis using analog neural networks

Helicopter gearbox fault detection and diagnosis using analo...

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Asilomar Conference on signals, Systems & computers

作者： P.T. Monsen E.S. Manolakos M. Dzwonczyk Atlantic Aerospace Electronics Corporation Waltham MA USA Communications and Digital Signal Processing Center Electrical And Computer Engineering Department Northeastern University Boston MA USA Information Systems Laboratory Department of Electrical Engineering University of Stanford USA

This paper summarizes the results of two neural hardware implementations of a helicopter gearbox health monitoring system (HMS). Our first hybrid approach and implementation to fault diagnosis is outlined, and our results are summarized using three levels of fault characterization: fault detection (fault or no fault), classification (gear or bearing fault), and identification (fault sub-classes). Our second all-analog implementation exploits the ability, of analog neural hardware to compute the discrete Fourier transform (DFT) as a pre-processor to a neural classifier. Our hardware results compare well with previously published software simulations.< >

关键词： Helicopters Fault detection Fault diagnosis Hardware Discrete Fourier transforms Monitoring Gears Analog computers Computational modeling

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DISCRETE REPRESENTATION OF CONTINUOUS signalS - THE HUGGINS TRANSFORM

DISCRETE REPRESENTATION OF CONTINUOUS SIGNALS - THE HUGGINS ...

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INTERNATIONAL CONF ON ACOUSTICS, SPEECH AND signal processing

作者： SCHONFELD, D Signal and Image Research Laboratory Department of Electrical Engineering and Computer Science University of Illinois at Chicago Chicago IL United States

ISBN: (纸本)0780305329

The discrete representation of continuous linear time-invariant signal processing systems is discussed. The orthogonal Huggins representation is introduced as an important special case of the discrete orthogonal representation. This representation uses an orthogonalized collection of complex exponentials as the orthogonal basis. Additionally, the Huggins representation of continuous linear time-invariant systems is proposed. The Huggins representation is formed as the discrete eigenfunction representation of continuous linear time-invariant systems in terms of a collection of complex exponentials. The orthogonal Huggins representation results in a quadratic computational complexity, whereas the Huggins representation yields a linear computational complexity. © 1992 IEEE.

关键词： Linear time-invariant system

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