检索结果-内蒙古大学图书馆

Asilomar Conference on signals, Systems & computers

作者： J.D. Terry D.B. Williams School of Electrical and Computer Engineering Georgia Institute of Technology USA Texas Instruments Inc. Dallas TX USA Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

In this paper, we present a novel array processing technique for co-channel interference reduction for TDMA based mobile satellite communication systems using linear block codes. This technique combines least squares projection with syndrome detection (LSPSD) to compute the optimum multi-antenna linear receiver for a signal of interest (SOI) encoded with a linear block coding scheme. The algorithm is shown to reduce co-channel interference and to improve bit error rate performance. Further, we show that the algorithm achieves SNR improvement by coherently adding multipath components of the SOI.

关键词： Block codes Interchannel interference Time division multiple access Vectors Linear antenna arrays Array signal processing Sensor arrays Wireless communication Least squares methods Fading

来源：评论

学校读者我要写书评

暂无评论

Design of optimal digital FIR filters with arbitrary magnitude and phase responses

Design of optimal digital FIR filters with arbitrary magnitu...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： L.J. Karam J.H. McClellan Telecommunications Research Center Department of Electrical Engineering Arizona State University Tempe AZ USA Digital Signal Processing Laboratory School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

This paper presents a new multiple-exchange ascent algorithm for designing optimal Chebyshev digital FIR filters with arbitrary magnitude and phase specifications. Compared to existing Chebyshev design techniques, the new design algorithm exhibits faster convergence while maintaining high accuracy, and is guaranteed to converge to the optimal solution. In addition, the proposed algorithm reduces to the classic second Remez (Parks-McClellan) algorithm when real-only or imaginary-only filters are designed and is, therefore, a true generalization of the classic Remez algorithm to the complex case.

关键词： Finite impulse response filter Digital filters Chebyshev approximation Algorithm design and analysis signal processing algorithms Frequency response Electronic mail Design optimization Filtering Robustness

来源：评论

学校读者我要写书评

暂无评论

Partially adaptive radar signal processing: The cross-spectral approach 29

Partially adaptive radar signal processing: The cross-spectr...

引用

29th Asilomar Conference on signals, Systems and computers, ACSSC 1995

作者： Goldstein, J. Scott Kogon, Stephen M. Reed, Irving S. Williams, Douglas B. Holder, E. Jeff USAF Rome Laboratory RL/C3BA 525 Brooks Rd. Grifilss AFBNY13441-4505 United States Statistical Signal and Image Processing Laboratory Department of Electrical Engineering University of Southern California Los AngelesCA90089-2565 United States Digital Signal Processing Laboratory School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332-0250 United States

ISBN: (纸本)0818673702

This paper is concerned with reducing the rank of the adaptive weight vector in radar array signal processing. The motivation for reducing the rank is that modern space-time processing requires many more weights than can be supported on airborne and spacesegment platforms. The loss incurred in partially adaptive radar processing is that the steady-state Wiener solution of the lower rank weight vector may not perform as well as the full rank solution. Hence, this paper will be concerned with the Wiener solution of partially adaptive radar arrays and compare the performance of principal component techniques with the recently developed crossspectral technique. © 1996 IEEE.

关键词： Array processing

来源：评论

学校读者我要写书评

暂无评论

Motion compensated compression of computer animation frames 93

Motion compensated compression of computer animation frames

引用

20th International Conference on computer Graphics and Interactive Techniques, SIGGRAPH 1993

作者： Guenter, Brian K. Yun, Hee Cheol Mersereau, Russell M. Computer Animation Laboratory GVU Center College of Computing Georgia Institute of Technology AtlantaGA30332 United States Digital Signal Processing Labratory School of Electrical Engineering Georgia Institute of Technology AtlantaGA30332 United States

ISBN: (纸本)0897916018

This paper presents a new lossless compression algorithm for computer animation image sequences. The algorithm uses transformation information available in the animation script and floating point depth and object number information stored at each pixel to perform highly accurate motion prediction with very low computation. The geometric data, i.e., the depth and object number, is very efficiently compressed using motion prediction and a new technique called direction coding, typically to 1 to 2 bits per pixel. The geometric data is also useful in z-buffer image compositing and this new compression algorithm offers a very low storage overhead method for saving the information needed for z-buffer image compositing. The overall compression ratio of the new algorithm, including the geometric data overhead, is compared to conventional spatial linear prediction compression and is shown to be consistently better, by a factor of 1.4 or more, even with large frame-to-frame motion. © 1993 ACM.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

Optical Memory Elements Based on Hetero-nipi Superlattice Asymmetric Cavity Spatial Light Modulators

Optical Memory Elements Based on Hetero-nipi Superlattice As...

引用

Spatial Light Modulators and Applications, SLM 1993

作者： Hibbs-Brenner, M.K. Mukherjee, S.D. Lehman, J. Ruden, P.P. Liu, J.J. Sawchuk, A.A. Hsu, W.-F. Honeywell Systems and Research Center 10701 Lyndale Avenue South BloomingtonMN55420 United States Dept. of Electrical Engineering and Computer Science University of Minnesota MinneapolisMN55455 United States Signal and Image Processing Institute University of Southern California Los AngelesCA90089-2564 United States

来源：评论

学校读者我要写书评

暂无评论

Interactive tools for signal processing education. The signal processing instructional facility (SPIF lab) at Washington State University

引用

computer Applications in engineering Education 1993年第6期1卷 517-517页

作者： Bamberger, R.H. Signal Processing Instructional Facility School of Electrical Engineering and Computer Science Washington State University Pullman WA 99164-2752 Dr. Roberto H. Bamberger:was born on January 30 1965 in Buenos Aires Argentina. He received his B.E.E and PhD from the Georgia Institute of Technology in 1986 and 1990 respectively. Currently Dr. Bamberger is an assistant professor in the School of Electrical Engineering and Computer Science at Washington State University. Dr. Bamberger's research program is focused on the design implementation and application of multidimensional multirate filter banks subband image and video compression analysis of nonstationary data and application of digital signal processing techniques in the design of analog and mixed-mode integrated circuits. Dr. Bamberger is the founder and director of the Signal Processing Instructional Facility (SPIF Lab) at Washington State University. The SPIF Lab features interactive multimedia-based tools for teaching concepts related to linear systems theory. Dr. Bamberger is active in developing multimedia-based instructional laboratories for a variety of other topics as well. In addition to his teaching and research programs Dr. Bamberger is an associate editor for theIEEE Transactions on Signal Processingand a member of the editorial board forComputer Applications in Engineering Education. Dr. Bamberger is also advisor to the WSU Student Branch of the IEEE and assistant director of the WSU Cougar Marching Band. Dr. Bamberger is a member of Phi Eta Sigma Eta Kappa Nu Tau Beta Pi and Kappa Kappa Psi.

The signal processing Instructional Facility (SPIF Lab) is an experiment in using in interactive multimedia for teaching concepts related to linear systems theory and signal processing. The goals of the SPIF lab are to augment, enhance, and interconnect sophomore, junior, and senior level courses with the common thread of linear systems and transforms by unifying the experimentation medium. In this fashion, physical phenomenon is returned to the forefront of engineering education. The laboratory features powerful Mathematica Notebooks (a form of hypertext) and interactive applications that use dedicated DSP microprocessors.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Convergence analysis for the extended-Kalman-filter based algorithm of target tracking and identification

Convergence analysis for the extended-Kalman-filter based al...

引用

Asilomar Conference on signals, Systems & computers

作者： D.S. Cheng A.R. Stubberud Center for High-speed Image/Signal Processing (CHIP) Department of Electrical and Computer Engineering University of California Irvine Irvine CA USA

The joint problem of target tracking and identification was discussed previously by the authors (1991), and a tracking/identification algorithm using an extended-Kalman-filter-based associative memory (EK-FAM) was demonstrated through several examples. The convergence properties of the algorithm are discussed. Under the appropriate conditions, a contraction operator can be developed, using Banach space concepts that guarantee convergence of the algorithm.< >

关键词： Convergence Algorithm design and analysis Target tracking signal processing algorithms Associative memory Functional analysis Vectors Eigenvalues and eigenfunctions Virtual manufacturing Jacobian matrices

来源：评论

学校读者我要写书评

暂无评论

Target Tracking and Identification using Neural Networks and Associative Memories

Target Tracking and Identification using Neural Networks and...

引用

IJCNN International Joint Conference on Neural Networks

作者： Dan S.Cheng Allen R.Stubberud Center for High-Speed Image/Signal Processing（CHIP） Department of Electrical and Computer Engineering University of California Irvine IrvineCA 92717

＜正＞The joint problem of tracking and identification of a target from an airplane was discussed in[1].In this paper the problem is discussed using a different system structure which uses a neural *** assume that a set of targets are distinguishable where indistinguishability between any two targets implies that their feature vectors are *** associative memory,which is implemented with an artificial neural network in a feedback loop,is developed as an *** the associative memory is presented with a feature vector it recalls the corresponding *** mathematical concepts in Hilbert space show that perfect identification is possible by using such an identifier in the noise free *** estimate is used to identify correct targets when targets are subject to certain conditions of noise corruption of the feature *** can combine this identifier with a modified extended Kalman filter to solve the combined target tracking and identification *** result of this technique is promising,and fast identification is *** demonstrate this technique through an example.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A ROBUST APPROACH FOR HIGH-RESOLUTION FREQUENCY ESTIMATION

引用

IEEE TRANSACTIONS ON signal processing 1991年第3期39卷 627-643页

作者： SANG, GO KASHYAP, RL School of Electrical Engineering Purdue University West Lafayette IN USA Signal Processing Branch Computer Science Center Texas Instruments Inc. Dallas TX USA

We investigate a robust estimation method for estimating frequencies of received signals. The received signals can be represented as a sum of sinusoidal signals and an additive noise process. The additive noise is assumed to be a mixture of a Gaussian and an outlier process. It is known that a robust estimate performs much better than conventional estimates such as least square estimates (LSE) or Gaussian maximum likelihood estimates (MLE-G), when the noise has a mixture distribution or when the observations have a low signal-to-noise ratio (SNR). Even a single outlier can cause large errors in conventional estimation methods because they are sensitive to minor deviations from the underlying assumptions. Among the family of robust estimates, we consider the M-estimate which is obtained by the minimization of a nonquadratic function of normalized residuals. The following are the topics considered in our paper. First, the influence function of a robust estimate is derived for time varying (sinusoidal) signals. Second, the variance of the robust estimate is derived through the influence function. It is found that the robust estimate attains the Cramer-Rao lower bound (CRLB) for the contaminated Gaussian distribution. It is of order O(N-3) and is close to the CRLB for the perfect Gaussian distribution. Finally, we introduce some basic definitions for the high resolution frequency estimation method and prove that the robust estimate has the high resolution property. This property is not possessed by estimation methods, such as autoregressive based methods.

关键词： Frequency estimation Maximum likelihood estimation Noise robustness Gaussian noise signal to noise ratio signal processing Additive noise Least squares approximation Gaussian distribution signal resolution

来源：评论

学校读者我要写书评

暂无评论

Statistically consistent frequency estimation using linear prediction

Statistically consistent frequency estimation using linear p...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： S. Oh R.L. Kashyap Signal Processing Speech and Image Understanding Laboratories Computer Science Center Texas Instruments Inc. Dallas TX USA School of Electrical Engineering Purdue University West Lafayette IN USA

A new statistically consistent frequency estimation method has been developed and presented using linear prediction (LP) method. The observed signal is assumed to be a sum of complex exponentials with white random noise process. The number of complex exponentials is assumed to be known. A statistically consistent estimator is an estimator that converges to the true value as the number of observations increases to infinite. It is shown that conventional LP-based estimation methods such as Prony's method are not consistent statistically. It is also proved that the new estimation method provides statistically consistent estimates and performs better than Prony's estimation method. Numerical simulation is provided to confirm the performance of the new estimation method and its statistical consistency.< >

关键词： Frequency estimation Polynomials signal processing Maximum likelihood estimation signal to noise ratio White noise Gaussian noise Speech processing computer science Instruments

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：